Development and Evaluation of a Parallel Reaction Monitoring Strategy for Large-Scale Targeted Metabolomics Quantification.

PubMed

Zhou, Juntuo; Liu, Huiying; Liu, Yang; Liu, Jia; Zhao, Xuyang; Yin, Yuxin

2016-04-19

Recent advances in mass spectrometers which have yielded higher resolution and faster scanning speeds have expanded their application in metabolomics of diverse diseases. Using a quadrupole-Orbitrap LC-MS system, we developed an efficient large-scale quantitative method targeting 237 metabolites involved in various metabolic pathways using scheduled, parallel reaction monitoring (PRM). We assessed the dynamic range, linearity, reproducibility, and system suitability of the PRM assay by measuring concentration curves, biological samples, and clinical serum samples. The quantification performances of PRM and MS1-based assays in Q-Exactive were compared, and the MRM assay in QTRAP 6500 was also compared. The PRM assay monitoring 237 polar metabolites showed greater reproducibility and quantitative accuracy than MS1-based quantification and also showed greater flexibility in postacquisition assay refinement than the MRM assay in QTRAP 6500. We present a workflow for convenient PRM data processing using Skyline software which is free of charge. In this study we have established a reliable PRM methodology on a quadrupole-Orbitrap platform for evaluation of large-scale targeted metabolomics, which provides a new choice for basic and clinical metabolomics study.

Simultaneous measurement of NAD metabolome in aged mice tissue using liquid chromatography tandem-mass spectrometry.

PubMed

Yaku, Keisuke; Okabe, Keisuke; Nakagawa, Takashi

2018-06-01

Nicotinamide adenine dinucleotide (NAD) is a major co-factor that mediates multiple biological processes including redox reaction and gene expression. Recently, NAD metabolism has received considerable attention because administration of NAD precursors exhibited beneficial effects against aging-related metabolic disorders in animals. Although numerous studies have reported that NAD levels decline with aging in multiple animal tissues, the pathway and kinetics of NAD metabolism in aged organs are not completely understood. To determine the NAD metabolism upon aging, we developed targeted metabolomics based on an LC/MS/MS system. Our method is simple and applicable to crude biological samples, including culture cells and animal tissues. Unlike a conventional enzymatic cycling assay, our approach can determine NAD and NADH (reduced form of NAD) by performing a single sample preparation. Further, we validated our method using biological samples and investigated the alteration of the NAD metabolome during aging. Consistent with previous reports, the NAD levels in the liver and skeletal muscle decreased with aging. Further, we detected a significant increase in nicotinamide mononucleotide and nicotinamide riboside in the kidney upon aging. The LC/MS/MS-based NAD metabolomics that we have developed is extensively applicable to biomedical studies, and the results will present innovative ideas for the aging studies, especially for that of NAD metabolism. Copyright © 2018 John Wiley & Sons, Ltd.

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD).

PubMed

Rhoades, Seth D; Weljie, Aalim M

2016-12-01

Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD)

PubMed Central

Rhoades, Seth D.

2017-01-01

Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). Methods We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. Results LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. Conclusions The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method. PMID:28348510

Counting missing values in a metabolite-intensity data set for measuring the analytical performance of a metabolomics platform.

PubMed

Huan, Tao; Li, Liang

2015-01-20

Metabolomics requires quantitative comparison of individual metabolites present in an entire sample set. Unfortunately, missing intensity values in one or more samples are very common. Because missing values can have a profound influence on metabolomic results, the extent of missing values found in a metabolomic data set should be treated as an important parameter for measuring the analytical performance of a technique. In this work, we report a study on the scope of missing values and a robust method of filling the missing values in a chemical isotope labeling (CIL) LC-MS metabolomics platform. Unlike conventional LC-MS, CIL LC-MS quantifies the concentration differences of individual metabolites in two comparative samples based on the mass spectral peak intensity ratio of a peak pair from a mixture of differentially labeled samples. We show that this peak-pair feature can be explored as a unique means of extracting metabolite intensity information from raw mass spectra. In our approach, a peak-pair peaking algorithm, IsoMS, is initially used to process the LC-MS data set to generate a CSV file or table that contains metabolite ID and peak ratio information (i.e., metabolite-intensity table). A zero-fill program, freely available from MyCompoundID.org , is developed to automatically find a missing value in the CSV file and go back to the raw LC-MS data to find the peak pair and, then, calculate the intensity ratio and enter the ratio value into the table. Most of the missing values are found to be low abundance peak pairs. We demonstrate the performance of this method in analyzing an experimental and technical replicate data set of human urine metabolome. Furthermore, we propose a standardized approach of counting missing values in a replicate data set as a way of gauging the extent of missing values in a metabolomics platform. Finally, we illustrate that applying the zero-fill program, in conjunction with dansylation CIL LC-MS, can lead to a marked improvement in finding significant metabolites that differentiate bladder cancer patients and their controls in a metabolomics study of 109 subjects.

Metabolome and proteome profiling of complex I deficiency induced by rotenone.

PubMed

Gielisch, Ina; Meierhofer, David

2015-01-02

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.

PubMed

Avtonomov, Dmitry M; Raskind, Alexander; Nesvizhskii, Alexey I

2016-08-05

Mass spectrometry (MS) coupled to liquid chromatography (LC) is a commonly used technique in metabolomic and proteomic research. As the size and complexity of LC-MS-based experiments grow, it becomes increasingly more difficult to perform quality control of both raw data and processing results. In a practical setting, quality control steps for raw LC-MS data are often overlooked, and assessment of an experiment's success is based on some derived metrics such as "the number of identified compounds". The human brain interprets visual data much better than plain text, hence the saying "a picture is worth a thousand words". Here, we present the BatMass software package, which allows for performing quick quality control of raw LC-MS data through its fast visualization capabilities. It also serves as a testbed for developers of LC-MS data processing algorithms by providing a data access library for open mass spectrometry file formats and a means of visually mapping processing results back to the original data. We illustrate the utility of BatMass with several use cases of quality control and data exploration.

BatMass: a Java software platform for LC/MS data visualization in proteomics and metabolomics

PubMed Central

Avtonomov, Dmitry; Raskind, Alexander; Nesvizhskii, Alexey I.

2017-01-01

Mass spectrometry (MS) coupled to liquid chromatography (LC) is a commonly used technique in metabolomic and proteomic research. As the size and complexity of LC/MS based experiments grow, it becomes increasingly more difficult to perform quality control of both raw data and processing results. In a practical setting, quality control steps for raw LC/MS data are often overlooked and assessment of an experiment's success is based on some derived metrics such as “the number of identified compounds”. Human brain interprets visual data much better than plain text, hence the saying “a picture is worth a thousand words”. Here we present BatMass software package which allows to perform quick quality control of raw LC/MS data through its fast visualization capabilities. It also serves as a testbed for developers of LC/MS data processing algorithms by providing a data access library for open mass spectrometry file formats and a means of visually mapping processing results back to the original data. We illustrate the utility of BatMass with several use cases of quality control and data exploration. PMID:27306858

Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics.

PubMed

Baniasadi, Hamid; Vlahakis, Chris; Hazebroek, Jan; Zhong, Cathy; Asiago, Vincent

2014-02-12

We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

High Resolution Separations and Improved Ion Production and Transmission in Metabolomics

PubMed Central

Metz, Thomas O.; Page, Jason S.; Baker, Erin S.; Tang, Keqi; Ding, Jie; Shen, Yufeng; Smith, Richard D.

2008-01-01

The goal of metabolomics analyses is the detection and quantitation of as many sample components as reasonably possible in order to identify compounds or “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is important that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize ionization suppression and thereby extend the dynamic range of the measurement, as well as the coverage of the metabolome. Similarly, optimization of the MS inlet and interface can lead to increased measurement sensitivity. This perspective review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics. Additional emphasis will be placed on the compromise between metabolome coverage and sample analysis throughput. PMID:19255623

Investigation on biochemical compositional changes during the microbial fermentation process of Fu brick tea by LC-MS based metabolomics.

PubMed

Xu, Jie; Hu, Feng-Lin; Wang, Wei; Wan, Xiao-Chun; Bao, Guan-Hu

2015-11-01

Fu brick tea (FBT) is a unique post-fermented tea product which is fermented with fungi during the manufacturing process. In this study, we investigated the biochemical compositional changes occurring during the microbial fermentation process (MFP) of FBT based on non-targeted LC-MS, which was a comprehensive and unbiased methodology. Our data analysis took a two-phase approach: (1) comparison of FBT with other tea products using PCA analysis to exhibit the characteristic effect of MFP on the formation of Fu brick tea and (2) comparison of tea samples throughout the MFP of FBT to elucidate the possible key metabolic pathways produced by the fungi. Non-targeted LC-MS analysis clearly distinguished FBT with other tea samples and highlighted some interesting metabolic pathways during the MFP including B ring fission catechin. Our study demonstrated that those fungi had a significant influence on the biochemical profiles in the FBT and consequently contributed to its unique quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

NASA Astrophysics Data System (ADS)

Chen, Deying; Su, Xiaoling; Wang, Nan; Li, Yunong; Yin, Hua; Li, Liang; Li, Lanjuan

2017-01-01

We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models.

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

PubMed Central

Chen, Deying; Su, Xiaoling; Wang, Nan; Li, Yunong; Yin, Hua; Li, Liang; Li, Lanjuan

2017-01-01

We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models. PMID:28091618

Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women.

PubMed

Luan, Hemi; Meng, Nan; Liu, Ping; Fu, Jin; Chen, Xiaomin; Rao, Weiqiao; Jiang, Hui; Xu, Xun; Cai, Zongwei; Wang, Jun

2015-01-01

Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy. In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy. As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics.

PubMed

Shen, Weifeng; Han, Wei; Li, Yunong; Meng, Zhiqi; Cai, Leiming; Li, Liang

2016-10-26

Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential 12 C-/ 13 C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N-Methyl-D-aspartic and tyrosine were identified. The changes of these biomarkers were likely due to the disruption of the endocrine system of silkworm by DDT. This work illustrates that the method of CIL LC-MS is useful to generate quantitative submetabolome profiles from a small volume of silkworm hemolymph with much higher coverage than conventional LC-MS methods, thereby facilitating the discovery of potential metabolite biomarkers related to EDC or other chemical exposure. Copyright © 2016 Elsevier B.V. All rights reserved.

An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics.

PubMed

Wang, Yang; Feng, Ruibing; He, Chengwei; Su, Huanxing; Ma, Huan; Wan, Jian-Bo

2018-08-05

The narrow linear range and the limited scan time of the given ion make the quantification of the features challenging in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics with the full-scan mode. And metabolite identification is another bottleneck of untargeted analysis owing to the difficulty of acquiring MS/MS information of most metabolites detected. In this study, an integrated workflow was proposed using the newly established multiple ion monitoring mode with time-staggered ion lists (tsMIM) and target-directed data-dependent acquisition with time-staggered ion lists (tsDDA) to improve data acquisition and metabolite identification in UHPLC/Q-TOF MS-based untargeted metabolomics. Compared to the conventional untargeted metabolomics, the proprosed workflow exhibited the better repeatability before and after data normalization. After selecting features with the significant change by statistical analysis, MS/MS information of all these features can be obtained by tsDDA analysis to facilitate metabolite identification. Using time-staggered ion lists, the workflow is more sensitive in data acquisition, especially for the low-abundant features. Moreover, the metabolites with low abundance tend to be wrongly integrated and triggered by full scan-based untargeted analysis with MS E acquisition mode, which can be greatly improved by the proposed workflow. The integrated workflow was also successfully applied to discover serum biosignatures for the genetic modification of fat-1 in mice, which indicated its practicability and great potential in future metabolomics studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Cerebrospinal Fluid Metabolomics After Natural Product Treatment in an Experimental Model of Cerebral Ischemia.

PubMed

Huan, Tao; Xian, Jia Wen; Leung, Wing Nang; Li, Liang; Chan, Chun Wai

2016-11-01

Cerebrospinal fluid (CSF) is an important biofluid for diagnosis of and research on neurological diseases. However, in-depth metabolomic profiling of CSF remains an analytical challenge due to the small volume of samples, particularly in small animal models. In this work, we report the application of a high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) workflow for CSF metabolomics in Gastrodia elata and Uncaria rhynchophylla water extract (GUW)-treated experimental cerebral ischemia model of rat. The GUW is a commonly used Traditional Chinese Medicine (TCM) for hypertension and brain disease. This study investigated the amine- and phenol-containing biomarkers in the CSF metabolome. After GUW treatment for 7 days, the neurological deficit score was significantly improved with infarct volume reduction, while the integrity of brain histological structure was preserved. Over 1957 metabolites were quantified in CSF by dansylation LC-MS. The analysis of this comprehensive list of metabolites suggests that metabolites associated with oxidative stress, inflammatory response, and excitotoxicity change during GUW-induced alleviation of ischemic injury. This work is significant in that (1) it shows CIL LC-MS can be used for in-depth profiling of the CSF metabolome in experimental ischemic stroke and (2) identifies several potential molecular targets (that might mediate the central nervous system) and associate with pharmacodynamic effects of some frequently used TCMs.

Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

PubMed

Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

2017-02-08

Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only holistically provide qualitative information, but also straightforwardly generate accurate quantitative dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

Chemical Isotope Labeling LC-MS for High Coverage and Quantitative Profiling of the Hydroxyl Submetabolome in Metabolomics.

PubMed

Zhao, Shuang; Luo, Xian; Li, Liang

2016-11-01

A key step in metabolomics is to perform accurate relative quantification of the metabolomes in comparative samples with high coverage. Hydroxyl-containing metabolites are an important class of the metabolome with diverse structures and physical/chemical properties; however, many of them are difficult to detect with high sensitivity. We present a high-performance chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) technique for in-depth profiling of the hydroxyl submetabolome, which involves the use of acidic liquid-liquid extraction to enrich hydroxyl metabolites into ethyl acetate from an aqueous sample. After drying and then redissolving in acetonitrile, the metabolite extract is labeled using a base-activated 12 C- or 13 C-dansylation reaction. A fast step-gradient LC-UV method is used to determine the total concentration of labeled metabolites. On the basis of the concentration information, a 12 C-labeled individual sample is mixed with an equal mole amount of a 13 C-labeled pool or control for relative metabolite quantification. The 12 C-/ 13 C-labeled mixtures are individually analyzed by LC-MS, and the resultant peak pairs of labeled metabolites in MS are measured for relative quantification and metabolite identification. A standard library of 85 hydroxyl compounds containing MS, retention time, and MS/MS information was constructed for positive metabolite identification based on matches of two or all three of these parameters with those of an unknown. Using human urine as an example, we analyzed samples of 1:1 12 C-/ 13 C-labeled urine in triplicate with triplicate runs per sample and detected an average of 3759 ± 45 peak pairs or metabolites per run and 3538 ± 71 pairs per sample with 3093 pairs in common (n = 9). Out of the 3093 peak pairs, 2304 pairs (75%) could be positively or putatively identified based on metabolome database searches, including 20 pairs positively identified using the dansylated hydroxyl standards library. The majority of detected metabolites were those containing hydroxyl groups. This technique opens a new avenue for the detailed characterization of the hydroxyl submetabolome in metabolomics research.

LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

PubMed Central

Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

2014-01-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

PubMed

Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

2012-03-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

Development of Chemical Isotope Labeling LC-MS for Milk Metabolomics: Comprehensive and Quantitative Profiling of the Amine/Phenol Submetabolome.

PubMed

Mung, Dorothea; Li, Liang

2017-04-18

Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 12 C-/ 13 C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome. Since milk and milk products are consumed in large quantities on a daily basis, the intake of these milk metabolites even at low concentrations can be cumulatively high. The high-coverage analysis of the milk metabolome using CIL LC-MS should be very useful in future research involving the study of the effects of these metabolites on human health. It should also be useful in the dairy industry in areas such as improving milk production, developing new processing technologies, developing improved nutritional products, quality control, and milk product authentication.

Impact of exercise on fecal and cecal metabolome over aging: a longitudinal study in rats.

PubMed

Deda, Olga; Gika, Helen; Panagoulis, Theodoros; Taitzoglou, Ioannis; Raikos, Nikolaos; Theodoridis, Georgios

2017-01-01

Physical exercise can reduce adverse conditions during aging, while both exercise and aging act as metabolism modifiers. The present study investigates rat fecal and cecal metabolome alterations derived from exercise during rats' lifespan. Groups of rats trained life-long or for a specific period of time were under study. The training protocol consisted of swimming, 15-18 min per day, 3-5 days per week, with load of 4-0% of rat's weight. Fecal samples and cecal extracts were analyzed by targeted and untargeted metabolic profiling methods (GC-MS and LC-MS/MS). Effects of exercise and aging on the rats' fecal and cecal metabolome were observed. Fecal and cecal metabolomics are a promising field to investigate exercise biochemistry and age-related alterations.

An Artifact in LC-MS/MS Measurement of Glutamine and Glutamic Acid: In-Source Cyclization to Pyroglutamic Acid

PubMed Central

2015-01-01

Advances in metabolomics, particularly for research on cancer, have increased the demand for accurate, highly sensitive methods for measuring glutamine (Gln) and glutamic acid (Glu) in cell cultures and other biological samples. N-terminal Gln and Glu residues in proteins or peptides have been reported to cyclize to pyroglutamic acid (pGlu) during liquid chromatography (LC)-mass spectrometry (MS) analysis, but cyclization of free Gln and Glu to free pGlu during LC-MS analysis has not been well-characterized. Using an LC-MS/MS protocol that we developed to separate Gln, Glu, and pGlu, we found that free Gln and Glu cyclize to pGlu in the electrospray ionization source, revealing a previously uncharacterized artifact in metabolomic studies. Analysis of Gln standards over a concentration range from 0.39 to 200 μM indicated that a minimum of 33% and maximum of almost 100% of Gln was converted to pGlu in the ionization source, with the extent of conversion dependent on fragmentor voltage. We conclude that the sensitivity and accuracy of Gln, Glu, and pGlu quantitation by electrospray ionization-based mass spectrometry can be improved dramatically by using (i) chromatographic conditions that adequately separate the three metabolites, (ii) isotopic internal standards to correct for in-source pGlu formation, and (iii) user-optimized fragmentor voltage for acquisition of the MS spectra. These findings have immediate impact on metabolomics and metabolism research using LC-MS technologies. PMID:24892977

An artifact in LC-MS/MS measurement of glutamine and glutamic acid: in-source cyclization to pyroglutamic acid.

PubMed

Purwaha, Preeti; Silva, Leslie P; Hawke, David H; Weinstein, John N; Lorenzi, Philip L

2014-06-17

Advances in metabolomics, particularly for research on cancer, have increased the demand for accurate, highly sensitive methods for measuring glutamine (Gln) and glutamic acid (Glu) in cell cultures and other biological samples. N-terminal Gln and Glu residues in proteins or peptides have been reported to cyclize to pyroglutamic acid (pGlu) during liquid chromatography (LC)-mass spectrometry (MS) analysis, but cyclization of free Gln and Glu to free pGlu during LC-MS analysis has not been well-characterized. Using an LC-MS/MS protocol that we developed to separate Gln, Glu, and pGlu, we found that free Gln and Glu cyclize to pGlu in the electrospray ionization source, revealing a previously uncharacterized artifact in metabolomic studies. Analysis of Gln standards over a concentration range from 0.39 to 200 μM indicated that a minimum of 33% and maximum of almost 100% of Gln was converted to pGlu in the ionization source, with the extent of conversion dependent on fragmentor voltage. We conclude that the sensitivity and accuracy of Gln, Glu, and pGlu quantitation by electrospray ionization-based mass spectrometry can be improved dramatically by using (i) chromatographic conditions that adequately separate the three metabolites, (ii) isotopic internal standards to correct for in-source pGlu formation, and (iii) user-optimized fragmentor voltage for acquisition of the MS spectra. These findings have immediate impact on metabolomics and metabolism research using LC-MS technologies.

Quantitative Metabolome Analysis Based on Chromatographic Peak Reconstruction in Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.

PubMed

Huan, Tao; Li, Liang

2015-07-21

Generating precise and accurate quantitative information on metabolomic changes in comparative samples is important for metabolomics research where technical variations in the metabolomic data should be minimized in order to reveal biological changes. We report a method and software program, IsoMS-Quant, for extracting quantitative information from a metabolomic data set generated by chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). Unlike previous work of relying on mass spectral peak ratio of the highest intensity peak pair to measure relative quantity difference of a differentially labeled metabolite, this new program reconstructs the chromatographic peaks of the light- and heavy-labeled metabolite pair and then calculates the ratio of their peak areas to represent the relative concentration difference in two comparative samples. Using chromatographic peaks to perform relative quantification is shown to be more precise and accurate. IsoMS-Quant is integrated with IsoMS for picking peak pairs and Zero-fill for retrieving missing peak pairs in the initial peak pairs table generated by IsoMS to form a complete tool for processing CIL LC-MS data. This program can be freely downloaded from the www.MyCompoundID.org web site for noncommercial use.

Application of Fourier-transform ion cyclotron resonance mass spectrometry to metabolic profiling and metabolite identification.

PubMed

Ohta, Daisaku; Kanaya, Shigehiko; Suzuki, Hideyuki

2010-02-01

Metabolomics, as an essential part of genomics studies, intends holistic understanding of metabolic networks through simultaneous analysis of a myriad of both known and unknown metabolites occurring in living organisms. The initial stage of metabolomics was designed for the reproducible analyses of known metabolites based on their comparison to available authentic compounds. Such metabolomics platforms were mostly based on mass spectrometry (MS) technologies enabled by a combination of different ionization methods together with a variety of separation steps including LC, GC, and CE. Among these, Fourier-transform ion cyclotron resonance MS (FT-ICR/MS) is distinguished from other MS technologies by its ultrahigh resolution power in mass to charge ratio (m/z). The potential of FT-ICR/MS as a distinctive metabolomics tool has been demonstrated in nontargeted metabolic profiling and functional characterization of novel genes. Here, we discuss both the advantages and difficulties encountered in the FT-ICR/MS metabolomics studies.

Metabolomic Profiling of Plasma Samples from Women with Recurrent Spontaneous Abortion.

PubMed

Li, XiaoCui; Yin, MingHong; Gu, JinPing; Hou, YanYan; Tian, FuJu; Sun, Feng

2018-06-13

BACKGROUND Gas chromatography coupled with mass spectrometry (GC-MS) and liquid chromatography coupled with mass spectrometry (LC-MS) metabolomics have been deployed to detect novel differential metabolites in cases with recurrent spontaneous abortion (RSA). MATERIAL AND METHODS Fifty patients who had recurrent spontaneous abortions (RSAs) and 51 control patients (age, gestational age, and body mass index (BMI) match) were enrolled in this study. Untargeted GC-MS and targeted LC-MS were combined to discover and validate the different metabolomic profiles between groups. Score plots of orthogonal partial least-squares discriminant analysis (OPLS-DA) clearly separated the RSA group from the control group. The variable importance in projection (VIP) generated in OPLS-DA processing represented the contribution to the discrimination of each metabolite ion between groups. Variables with a VIP >1 and P<0.05 were considered to be different variables. We also used MetaboAnalyst 3.0 to analyze the pathway impact of potential metabolite biomarkers. RESULTS Fifty-four metabolites were significantly different between the two groups, as indicated by a VIP >1 and P<0.05. The metabolic pathways involving glycine, serine, threonine (P=0.00529, impact=0.26), beta-alanine (P=0.0284, impact=0.27), and phenylalanine metabolism (P=0.0217, impact=0.17), along with the tricarboxylic acid (TCA) cycle (P=0.0113, impact=0.19) and the glycolysis pathway (P=0.037, impact=0.1) are obviously related to RSA. Verification by LC-MS showed that the concentration of lactic acid in RSA was higher than that in the control group (P<0.05), while the concentration of 5-methoxytryptamine was significantly lower in the RSA group (P<0.05). CONCLUSIONS In our study, untargeted GC-MS was used to detect disturbance of metabolism occurs in RSA and targeted LC-MS further was used to show that plasma concentrations of two metabolites (lactic acid and 5-methoxytryptamine) were different in the RSA compared to the control group.

Effect of Antibiotics and Diet on Enterolactone Concentration and Metabolome Studied by Targeted and Nontargeted LC-MS Metabolomics.

PubMed

Bolvig, Anne K; Nørskov, Natalja P; Hedemann, Mette S; Foldager, Leslie; McCarthy-Sinclair, Brendan; Marco, Maria L; Lærke, Helle N; Bach Knudsen, Knud E

2017-06-02

High plant lignan intake is associated with a number of health benefits, possibly induced by the lignan metabolite enterolactone (ENL). The gut microbiota plays a crucial role in converting dietary lignans into ENL, and epidemiological studies have shown that use of antibiotics is associated with lower levels of ENL. Here we investigate the link between antibiotic use and lignan metabolism in pigs using LC-MS/MS. The effect of lignan intake and antibiotic use on the gut microbial community and the pig metabolome is studied by 16S rRNA sequencing and nontargeted LC-MS. Treatment with antibiotics resulted in substantially lower concentrations of ENL compared with concentrations detected in untreated animals, whereas the plasma concentrations of plant lignans were unchanged. Both diet and antibiotic treatment affected the clustering of urinary metabolites and significantly altered the proportions of taxa in the gut microbiota. Diet, but not antibiotic treatment, affected the plasma lipid profile, and a lower concentration of LDL cholesterol was observed in the pigs fed a high lignan diet. This study provides solid support for the associations between ENL concentrations and use of antibiotics found in humans and indicates that the lower ENL concentration may be a consequence of the ecological changes in the microbiota.

The Human Serum Metabolome

PubMed Central

Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

2011-01-01

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

The Impact of GFP Reporter Gene Transduction and Expression on Metabolomics of Placental Mesenchymal Stem Cells Determined by UHPLC-Q/TOF-MS.

PubMed

Yang, Jinfeng; Wang, Nan; Chen, Deying; Yu, Jiong; Pan, Qiaoling; Wang, Dan; Liu, Jingqi; Shi, Xiaowei; Dong, Xiaotian; Cao, Hongcui; Li, Liang; Li, Lanjuan

2017-01-01

Green fluorescent protein (GFP) is widely used as a reporter gene in regenerative medicine research to label and track stem cells. Here, we examined whether expressing GFP gene may impact the metabolism of human placental mesenchymal stem cells (hPMSCs). The GFP gene was transduced into hPMSCs using lentiviral-based infection to establish GFP + hPMSCs. A sensitive 13 C/ 12 C-dansyl labeling LC-MS method targeting the amine/phenol submetabolome was used for in-depth cell metabolome profiling. A total of 1151 peak pairs or metabolites were detected from 12 LC-MS runs. Principal component analysis and partial least squares discriminant analysis showed poor separation, and the volcano plots demonstrated that most of the metabolites were not significantly changed when hPMSCs were tagged with GFP. Overall, 739 metabolites were positively or putatively identified. Only 11 metabolites showed significant changes. Metabolic pathway analyses indicated that three of the identified metabolites were involved in nine pathways. However, these metabolites are unlikely to have a large impact on the metabolic pathways due to their nonessential roles and limited hits in pathway analysis. This study indicated that the expression of ectopic GFP reporter gene did not significantly alter the metabolomics pathways covered by the amine/phenol submetabolome.

Quality evaluation of extracted ion chromatograms and chromatographic peaks in liquid chromatography/mass spectrometry-based metabolomics data

PubMed Central

2014-01-01

Background Extracted ion chromatogram (EIC) extraction and chromatographic peak detection are two important processing procedures in liquid chromatography/mass spectrometry (LC/MS)-based metabolomics data analysis. Most commonly, the LC/MS technique employs electrospray ionization as the ionization method. The EICs from LC/MS data are often noisy and contain high background signals. Furthermore, the chromatographic peak quality varies with respect to its location in the chromatogram and most peaks have zigzag shapes. Therefore, there is a critical need to develop effective metrics for quality evaluation of EICs and chromatographic peaks in LC/MS based metabolomics data analysis. Results We investigated a comprehensive set of potential quality evaluation metrics for extracted EICs and detected chromatographic peaks. Specifically, for EIC quality evaluation, we analyzed the mass chromatographic quality index (MCQ index) and propose a novel quality evaluation metric, the EIC-related global zigzag index, which is based on an EIC's first order derivatives. For chromatographic peak quality evaluation, we analyzed and compared six metrics: sharpness, Gaussian similarity, signal-to-noise ratio, peak significance level, triangle peak area similarity ratio and the local peak-related local zigzag index. Conclusions Although the MCQ index is suited for selecting and aligning analyte components, it cannot fairly evaluate EICs with high background signals or those containing only a single peak. Our proposed EIC related global zigzag index is robust enough to evaluate EIC qualities in both scenarios. Of the six peak quality evaluation metrics, the sharpness, peak significance level, and zigzag index outperform the others due to the zigzag nature of LC/MS chromatographic peaks. Furthermore, using several peak quality metrics in combination is more efficient than individual metrics in peak quality evaluation. PMID:25350128

Quality evaluation of extracted ion chromatograms and chromatographic peaks in liquid chromatography/mass spectrometry-based metabolomics data.

PubMed

Zhang, Wenchao; Zhao, Patrick X

2014-01-01

Extracted ion chromatogram (EIC) extraction and chromatographic peak detection are two important processing procedures in liquid chromatography/mass spectrometry (LC/MS)-based metabolomics data analysis. Most commonly, the LC/MS technique employs electrospray ionization as the ionization method. The EICs from LC/MS data are often noisy and contain high background signals. Furthermore, the chromatographic peak quality varies with respect to its location in the chromatogram and most peaks have zigzag shapes. Therefore, there is a critical need to develop effective metrics for quality evaluation of EICs and chromatographic peaks in LC/MS based metabolomics data analysis. We investigated a comprehensive set of potential quality evaluation metrics for extracted EICs and detected chromatographic peaks. Specifically, for EIC quality evaluation, we analyzed the mass chromatographic quality index (MCQ index) and propose a novel quality evaluation metric, the EIC-related global zigzag index, which is based on an EIC's first order derivatives. For chromatographic peak quality evaluation, we analyzed and compared six metrics: sharpness, Gaussian similarity, signal-to-noise ratio, peak significance level, triangle peak area similarity ratio and the local peak-related local zigzag index. Although the MCQ index is suited for selecting and aligning analyte components, it cannot fairly evaluate EICs with high background signals or those containing only a single peak. Our proposed EIC related global zigzag index is robust enough to evaluate EIC qualities in both scenarios. Of the six peak quality evaluation metrics, the sharpness, peak significance level, and zigzag index outperform the others due to the zigzag nature of LC/MS chromatographic peaks. Furthermore, using several peak quality metrics in combination is more efficient than individual metrics in peak quality evaluation.

Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

NASA Astrophysics Data System (ADS)

Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

2016-12-01

The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34-80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics.

Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

PubMed Central

Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

2016-01-01

The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34–80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics. PMID:28000704

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

PubMed

Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

2017-03-01

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017. © 2015 Wiley Periodicals, Inc.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine.

PubMed

Zhang, Tong; Watson, David G

2015-05-07

The applications of metabolomics as a methodology for providing better treatment and understanding human disease continue to expand rapidly. In this review, covering the last two years, the focus is on liquid chromatography-mass spectrometry (LC-MS) profiling of metabolites in urine. In LC-MS based metabolomics there are still problems with regard to: chromatographic separation, peak picking and alignment, metabolite identification, metabolite coverage, instrument sensitivity and data interpretation and in the case of urine sample normalisation. Progress has been made with regard to all of these issues during the period of the review. Of particular interest are the increasing use of orthogonal chromatographic methods for optimal metabolite coverage and the increasing adoption of receiver operator characteristic (ROC) curves for biomarker validation.

A metabolomics guided exploration of marine natural product chemical space.

PubMed

Floros, Dimitrios J; Jensen, Paul R; Dorrestein, Pieter C; Koyama, Nobuhiro

2016-09-01

Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

Qualitative metabolome analysis of human cerebrospinal fluid by 13C-/12C-isotope dansylation labeling combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Guo, Kevin; Bamforth, Fiona; Li, Liang

2011-02-01

Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner. © American Society for Mass Spectrometry, 2011

Qualitative Metabolome Analysis of Human Cerebrospinal Fluid by 13C-/12C-Isotope Dansylation Labeling Combined with Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

NASA Astrophysics Data System (ADS)

Guo, Kevin; Bamforth, Fiona; Li, Liang

2011-02-01

Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by 13C-dansyl and 12C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

Differentiation of Panax quinquefolius grown in United States and China using LC/MS-based chromatographic fingerprinting and metabolomic approaches

USDA-ARS?s Scientific Manuscript database

American ginseng (Panax quinquefolius) is one of the most commonly used herbal medicines in the world. Discriminating between P. quinquefolius grown in different countries is difficult using the traditional quantitation methods. In this study, a liquid chromatographic mass spectrometry (LC-MS) fing...

LC-MS based metabolomics and chemometrics study of the toxic effects of copper on Saccharomyces cerevisiae.

PubMed

Farrés, Mireia; Piña, Benjamí; Tauler, Romà

2016-08-01

Copper containing fungicides are used to protect vineyards from fungal infections. Higher residues of copper in grapes at toxic concentrations are potentially toxic and affect the microorganisms living in vineyards, such as Saccharomyces cerevisiae. In this study, the response of the metabolic profiles of S. cerevisiae at different concentrations of copper sulphate (control, 1 mM, 3 mM and 6 mM) was analysed by liquid chromatography coupled to mass spectrometry (LC-MS) and multivariate curve resolution-alternating least squares (MCR-ALS) using an untargeted metabolomics approach. Peak areas of the MCR-ALS resolved elution profiles in control and in Cu(ii)-treated samples were compared using partial least squares regression (PLSR) and PLS-discriminant analysis (PLS-DA), and the intracellular metabolites best contributing to sample discrimination were selected and identified. Fourteen metabolites showed significant concentration changes upon Cu(ii) exposure, following a dose-response effect. The observed changes were consistent with the expected effects of Cu(ii) toxicity, including oxidative stress and DNA damage. This research confirmed that LC-MS based metabolomics coupled to chemometric methods are a powerful approach for discerning metabolomics changes in S. cerevisiae and for elucidating modes of toxicity of environmental stressors, including heavy metals like Cu(ii).

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Multi-profile Bayesian alignment model for LC-MS data analysis with integration of internal standards

PubMed Central

Tsai, Tsung-Heng; Tadesse, Mahlet G.; Di Poto, Cristina; Pannell, Lewis K.; Mechref, Yehia; Wang, Yue; Ressom, Habtom W.

2013-01-01

Motivation: Liquid chromatography-mass spectrometry (LC-MS) has been widely used for profiling expression levels of biomolecules in various ‘-omic’ studies including proteomics, metabolomics and glycomics. Appropriate LC-MS data preprocessing steps are needed to detect true differences between biological groups. Retention time (RT) alignment, which is required to ensure that ion intensity measurements among multiple LC-MS runs are comparable, is one of the most important yet challenging preprocessing steps. Current alignment approaches estimate RT variability using either single chromatograms or detected peaks, but do not simultaneously take into account the complementary information embedded in the entire LC-MS data. Results: We propose a Bayesian alignment model for LC-MS data analysis. The alignment model provides estimates of the RT variability along with uncertainty measures. The model enables integration of multiple sources of information including internal standards and clustered chromatograms in a mathematically rigorous framework. We apply the model to LC-MS metabolomic, proteomic and glycomic data. The performance of the model is evaluated based on ground-truth data, by measuring correlation of variation, RT difference across runs and peak-matching performance. We demonstrate that Bayesian alignment model improves significantly the RT alignment performance through appropriate integration of relevant information. Availability and implementation: MATLAB code, raw and preprocessed LC-MS data are available at http://omics.georgetown.edu/alignLCMS.html Contact: hwr@georgetown.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24013927

Metabolite profiling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources.

PubMed

Simón-Manso, Yamil; Lowenthal, Mark S; Kilpatrick, Lisa E; Sampson, Maureen L; Telu, Kelly H; Rudnick, Paul A; Mallard, W Gary; Bearden, Daniel W; Schock, Tracey B; Tchekhovskoi, Dmitrii V; Blonder, Niksa; Yan, Xinjian; Liang, Yuxue; Zheng, Yufang; Wallace, William E; Neta, Pedatsur; Phinney, Karen W; Remaley, Alan T; Stein, Stephen E

2013-12-17

Recent progress in metabolomics and the development of increasingly sensitive analytical techniques have renewed interest in global profiling, i.e., semiquantitative monitoring of all chemical constituents of biological fluids. In this work, we have performed global profiling of NIST SRM 1950, "Metabolites in Human Plasma", using GC-MS, LC-MS, and NMR. Metabolome coverage, difficulties, and reproducibility of the experiments on each platform are discussed. A total of 353 metabolites have been identified in this material. GC-MS provides 65 unique identifications, and most of the identifications from NMR overlap with the LC-MS identifications, except for some small sugars that are not directly found by LC-MS. Also, repeatability and intermediate precision analyses show that the SRM 1950 profiling is reproducible enough to consider this material as a good choice to distinguish between analytical and biological variability. Clinical laboratory data shows that most results are within the reference ranges for each assay. In-house computational tools have been developed or modified for MS data processing and interactive web display. All data and programs are freely available online at http://peptide.nist.gov/ and http://srmd.nist.gov/ .

12-months metabolic changes among gender dysphoric individuals under cross-sex hormone treatment: a targeted metabolomics study

PubMed Central

Auer, Matthias K.; Cecil, Alexander; Roepke, Yasmin; Bultynck, Charlotte; Pas, Charlotte; Fuss, Johannes; Prehn, Cornelia; Wang-Sattler, Rui; Adamski, Jerzy; Stalla, Günter K.; T’Sjoen, Guy

2016-01-01

Metabolomic analyses in epidemiological studies have demonstrated a strong sexual dimorphism for most metabolites. Cross-sex hormone treatment (CSH) in transgender individuals enables the study of metabolites in a cross-gender setting. Targeted metabolomic profiling of serum of fasting transmen and transwomen at baseline and following 12 months of CSH (N = 20/group) was performed. Changes in 186 serum metabolites and metabolite ratios were determined by targeted metabolomics analysis based on ESI-LC-MS/MS. RandomForest (RF) analysis was applied to detect metabolites of highest interest for grouping of transwomen and transmen before and after initiation of CSH. Principal component analysis (PCA) was performed to check whether group differentiation was achievable according to these variables and to see if changes in metabolite levels could be explained by a priori gender differences. PCA predicted grouping of individuals-determined by the citrulline/arginine-ratio and the amino acids lysine, alanine and asymmetric dimethylarginine - in addition to the expected grouping due to changes in sex steroids and body composition. The fact that most of the investigated metabolites did, however, not change, indicates that the majority of sex dependent differences in metabolites reported in the literature before may primarily not be attributable to sex hormones but to other gender-differences. PMID:27833161

Metabolomics Characterization of Two Apocynaceae Plants, Catharanthus roseus and Vinca minor, Using GC-MS and LC-MS Methods in Combination.

PubMed

Chen, Qi; Lu, Xueyan; Guo, Xiaorui; Guo, Qingxi; Li, Dewen

2017-06-17

Catharanthus roseus ( C. roseus ) and Vinca minor ( V. minor ) are two common important medical plants belonging to the family Apocynaceae. In this study, we used non-targeted GC-MS and targeted LC-MS metabolomics to dissect the metabolic profile of two plants with comparable phenotypic and metabolic differences. A total of 58 significantly different metabolites were present in different quantities according to PCA and PLS-DA score plots of the GC-MS analysis. The 58 identified compounds comprised 16 sugars, eight amino acids, nine alcohols and 18 organic acids. We subjected these metabolites into KEGG pathway enrichment analysis and highlighted 27 metabolic pathways, concentrated on the TCA cycle, glycometabolism, oligosaccharides, and polyol and lipid transporter (RFOS). Among the primary metabolites, trehalose, raffinose, digalacturonic acid and gallic acid were revealed to be the most significant marker compounds between the two plants, presumably contributing to species-specific phenotypic and metabolic discrepancy. The profiling of nine typical alkaloids in both plants using LC-MS method highlighted higher levels of crucial terpenoid indole alkaloid (TIA) intermediates of loganin, serpentine, and tabersonine in V. minor than in C. roseus . The possible underlying process of the metabolic flux from primary metabolism pathways to TIA synthesis was discussed and proposed. Generally speaking, this work provides a full-scale comparison of primary and secondary metabolites between two medical plants and a metabolic explanation of their TIA accumulation and phenotype differences.

Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

PubMed Central

Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

2014-01-01

Nicotinamide phosphoribosyltransferase (NAMPT) plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide–consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry–based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer) and HCT-116 (colorectal cancer) cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA), and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC)-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level. PMID:25486521

IsoMS: automated processing of LC-MS data generated by a chemical isotope labeling metabolomics platform.

PubMed

Zhou, Ruokun; Tseng, Chiao-Li; Huan, Tao; Li, Liang

2014-05-20

A chemical isotope labeling or isotope coded derivatization (ICD) metabolomics platform uses a chemical derivatization method to introduce a mass tag to all of the metabolites having a common functional group (e.g., amine), followed by LC-MS analysis of the labeled metabolites. To apply this platform to metabolomics studies involving quantitative analysis of different groups of samples, automated data processing is required. Herein, we report a data processing method based on the use of a mass spectral feature unique to the chemical labeling approach, i.e., any differential-isotope-labeled metabolites are detected as peak pairs with a fixed mass difference in a mass spectrum. A software tool, IsoMS, has been developed to process the raw data generated from one or multiple LC-MS runs by peak picking, peak pairing, peak-pair filtering, and peak-pair intensity ratio calculation. The same peak pairs detected from multiple samples are then aligned to produce a CSV file that contains the metabolite information and peak ratios relative to a control (e.g., a pooled sample). This file can be readily exported for further data and statistical analysis, which is illustrated in an example of comparing the metabolomes of human urine samples collected before and after drinking coffee. To demonstrate that this method is reliable for data processing, five (13)C2-/(12)C2-dansyl labeled metabolite standards were analyzed by LC-MS. IsoMS was able to detect these metabolites correctly. In addition, in the analysis of a (13)C2-/(12)C2-dansyl labeled human urine, IsoMS detected 2044 peak pairs, and manual inspection of these peak pairs found 90 false peak pairs, representing a false positive rate of 4.4%. IsoMS for Windows running R is freely available for noncommercial use from www.mycompoundid.org/IsoMS.

The combination of four analytical methods to explore skeletal muscle metabolomics: Better coverage of metabolic pathways or a marketing argument?

PubMed

Bruno, C; Patin, F; Bocca, C; Nadal-Desbarats, L; Bonnier, F; Reynier, P; Emond, P; Vourc'h, P; Joseph-Delafont, K; Corcia, P; Andres, C R; Blasco, H

2018-01-30

Metabolomics is an emerging science based on diverse high throughput methods that are rapidly evolving to improve metabolic coverage of biological fluids and tissues. Technical progress has led researchers to combine several analytical methods without reporting the impact on metabolic coverage of such a strategy. The objective of our study was to develop and validate several analytical techniques (mass spectrometry coupled to gas or liquid chromatography and nuclear magnetic resonance) for the metabolomic analysis of small muscle samples and evaluate the impact of combining methods for more exhaustive metabolite covering. We evaluated the muscle metabolome from the same pool of mouse muscle samples after 2 metabolite extraction protocols. Four analytical methods were used: targeted flow injection analysis coupled with mass spectrometry (FIA-MS/MS), gas chromatography coupled with mass spectrometry (GC-MS), liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) analysis. We evaluated the global variability of each compound i.e., analytical (from quality controls) and extraction variability (from muscle extracts). We determined the best extraction method and we reported the common and distinct metabolites identified based on the number and identity of the compounds detected with low analytical variability (variation coefficient<30%) for each method. Finally, we assessed the coverage of muscle metabolic pathways obtained. Methanol/chloroform/water and water/methanol were the best extraction solvent for muscle metabolome analysis by NMR and MS, respectively. We identified 38 metabolites by nuclear magnetic resonance, 37 by FIA-MS/MS, 18 by GC-MS, and 80 by LC-HRMS. The combination led us to identify a total of 132 metabolites with low variability partitioned into 58 metabolic pathways, such as amino acid, nitrogen, purine, and pyrimidine metabolism, and the citric acid cycle. This combination also showed that the contribution of GC-MS was low when used in combination with other mass spectrometry methods and nuclear magnetic resonance to explore muscle samples. This study reports the validation of several analytical methods, based on nuclear magnetic resonance and several mass spectrometry methods, to explore the muscle metabolome from a small amount of tissue, comparable to that obtained during a clinical trial. The combination of several techniques may be relevant for the exploration of muscle metabolism, with acceptable analytical variability and overlap between methods However, the difficult and time-consuming data pre-processing, processing, and statistical analysis steps do not justify systematically combining analytical methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Profile-Based LC-MS Data Alignment—A Bayesian Approach

PubMed Central

Tsai, Tsung-Heng; Tadesse, Mahlet G.; Wang, Yue; Ressom, Habtom W.

2014-01-01

A Bayesian alignment model (BAM) is proposed for alignment of liquid chromatography-mass spectrometry (LC-MS) data. BAM belongs to the category of profile-based approaches, which are composed of two major components: a prototype function and a set of mapping functions. Appropriate estimation of these functions is crucial for good alignment results. BAM uses Markov chain Monte Carlo (MCMC) methods to draw inference on the model parameters and improves on existing MCMC-based alignment methods through 1) the implementation of an efficient MCMC sampler and 2) an adaptive selection of knots. A block Metropolis-Hastings algorithm that mitigates the problem of the MCMC sampler getting stuck at local modes of the posterior distribution is used for the update of the mapping function coefficients. In addition, a stochastic search variable selection (SSVS) methodology is used to determine the number and positions of knots. We applied BAM to a simulated data set, an LC-MS proteomic data set, and two LC-MS metabolomic data sets, and compared its performance with the Bayesian hierarchical curve registration (BHCR) model, the dynamic time-warping (DTW) model, and the continuous profile model (CPM). The advantage of applying appropriate profile-based retention time correction prior to performing a feature-based approach is also demonstrated through the metabolomic data sets. PMID:23929872

A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism.

PubMed

Jacob, Minnie; Malkawi, Abeer; Albast, Nour; Al Bougha, Salam; Lopata, Andreas; Dasouki, Majed; Abdel Rahman, Anas M

2018-09-26

Metabolome, the ultimate functional product of the genome, can be studied through identification and quantification of small molecules. The global metabolome influences the individual phenotype through clinical and environmental interventions. Metabolomics has become an integral part of clinical research and allowed for another dimension of better understanding of disease pathophysiology and mechanism. More than 95% of the clinical biochemistry laboratory routine workload is based on small molecular identification, which can potentially be analyzed through metabolomics. However, multiple challenges in clinical metabolomics impact the entire workflow and data quality, thus the biological interpretation needs to be standardized for a reproducible outcome. Herein, we introduce the establishment of a comprehensive targeted metabolomics method for a panel of 220 clinically relevant metabolites using Liquid chromatography-tandem mass spectrometry (LC-MS/MS) standardized for clinical research. The sensitivity, reproducibility and molecular stability of each targeted metabolite (amino acids, organic acids, acylcarnitines, sugars, bile acids, neurotransmitters, polyamines, and hormones) were assessed under multiple experimental conditions. The metabolic tissue distribution was determined in various rat organs. Furthermore, the method was validated in dry blood spot (DBS) samples collected from patients known to have various inborn errors of metabolism (IEMs). Using this approach, our panel appears to be sensitive and robust as it demonstrated differential and unique metabolic profiles in various rat tissues. Also, as a prospective screening method, this panel of diverse metabolites has the ability to identify patients with a wide range of IEMs who otherwise may need multiple, time-consuming and expensive biochemical assays causing a delay in clinical management. Copyright © 2018 Elsevier B.V. All rights reserved.

Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: Investigation of nicotinic acid receptor agonists

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zgoda-Pols, Joanna R., E-mail: joanna.pols@merck.com; Chowdhury, Swapan; Wirth, Mark

2011-08-15

An investigative renal toxicity study using metabolomics was conducted with a potent nicotinic acid receptor (NAR) agonist, SCH 900424. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques were used to identify small molecule biomarkers of acute kidney injury (AKI) that could aid in a better mechanistic understanding of SCH 900424-induced AKI in mice. The metabolomics study revealed 3-indoxyl sulfate (3IS) as a more sensitive marker of SCH 900424-induced renal toxicity than creatinine or urea. An LC-MS assay for quantitative determination of 3IS in mouse matrices was also developed. Following treatment with SCH 900424, 3IS levels were markedly increasedmore » in murine plasma and brain, thereby potentially contributing to renal- and central nervous system (CNS)-related rapid onset of toxicities. Furthermore, significant decrease in urinary excretion of 3IS in those animals due to compromised renal function may be associated with the elevation of 3IS in plasma and brain. These data suggest that 3IS has a potential to be a marker of renal and CNS toxicities during chemically-induced AKI in mice. In addition, based on the metabolomic analysis other statistically significant plasma markers including p-cresol-sulfate and tryptophan catabolites (kynurenate, kynurenine, 3-indole-lactate) might be of toxicological importance but have not been studied in detail. This comprehensive approach that includes untargeted metabolomic and targeted bioanalytical sample analyses could be used to investigate toxicity of other compounds that pose preclinical or clinical development challenges in a pharmaceutical discovery and development. - Research Highlights: > Nicotinic acid receptor agonist, SCH 900424, caused acute kidney injury in mice. > MS-based metabolomics was conducted to identify potential small molecule markers of renal toxicity. > 3-indoxyl-sulfate was found to be as a more sensitive marker of renal toxicity than creatinine or urea. > 3-IS levels were increased not only in murine plasma but also in the brain. > 3-IS potentially contributes to renal-and CNS-related rapid onset of toxicities.« less

Impacts on the metabolome of down-regulating polyphenol oxidase in transgenic potato tubers

USDA-ARS?s Scientific Manuscript database

Tubers of potato (Solanum tuberosum L. cv. Estima) genetically modified (GM) to reduce polyphenol oxidase (PPO) activity and enzymatic discolouration were assessed for changes in the metabolome using Liquid Chromatography-Mass Spectrometry (LC-MS) and Gas Chromatography (GC)-MS. Metabolome changes ...

Comprehensive Analysis of LC/MS Data Using Pseudocolor Plots

NASA Astrophysics Data System (ADS)

Crutchfield, Christopher A.; Olson, Matthew T.; Gourgari, Evgenia; Nesterova, Maria; Stratakis, Constantine A.; Yergey, Alfred L.

2013-02-01

We have developed new applications of the pseudocolor plot for the analysis of LC/MS data. These applications include spectral averaging, analysis of variance, differential comparison of spectra, and qualitative filtering by compound class. These applications have been motivated by the need to better understand LC/MS data generated from analysis of human biofluids. The examples presented use data generated to profile steroid hormones in urine extracts from a Cushing's disease patient relative to a healthy control, but are general to any discovery-based scanning mass spectrometry technique. In addition to new visualization techniques, we introduce a new metric of variance: the relative maximum difference from the mean. We also introduce the concept of substructure-dependent analysis of steroid hormones using precursor ion scans. These new analytical techniques provide an alternative approach to traditional untargeted metabolomics workflow. We present an approach to discovery using MS that essentially eliminates alignment or preprocessing of spectra. Moreover, we demonstrate the concept that untargeted metabolomics can be achieved using low mass resolution instrumentation.

Sample preparation prior to the LC-MS-based metabolomics/metabonomics of blood-derived samples.

PubMed

Gika, Helen; Theodoridis, Georgios

2011-07-01

Blood represents a very important biological fluid and has been the target of continuous and extensive research for diagnostic, or health and drug monitoring reasons. Recently, metabonomics/metabolomics have emerged as a new and promising 'omics' platform that shows potential in biomarker discovery, especially in areas such as disease diagnosis, assessment of drug efficacy or toxicity. Blood is collected in various establishments in conditions that are not standardized. Next, the samples are prepared and analyzed using different methodologies or tools. When targeted analysis of key molecules (e.g., a drug or its metabolite[s]) is the aim, enforcement of certain measures or additional analyses may correct and harmonize these discrepancies. In omics fields such as those performed by holistic analytical approaches, no such rules or tools are available. As a result, comparison or correlation of results or data fusion becomes impractical. However, it becomes evident that such obstacles should be overcome in the near future to allow for large-scale studies that involve the assaying of samples from hundreds of individuals. In this case the effect of sample handling and preparation becomes very serious, in order to avoid wasting months of work from experts and expensive instrument time. The present review aims to cover the different methodologies applied to the pretreatment of blood prior to LC-MS metabolomic/metabonomic studies. The article tries to critically compare the methods and highlight issues that need to be addressed.

Comparison of peak-picking workflows for untargeted liquid chromatography/high-resolution mass spectrometry metabolomics data analysis.

PubMed

Rafiei, Atefeh; Sleno, Lekha

2015-01-15

Data analysis is a key step in mass spectrometry based untargeted metabolomics, starting with the generation of generic peak lists from raw liquid chromatography/mass spectrometry (LC/MS) data. Due to the use of various algorithms by different workflows, the results of different peak-picking strategies often differ widely. Raw LC/HRMS data from two types of biological samples (bile and urine), as well as a standard mixture of 84 metabolites, were processed with four peak-picking softwares: Peakview®, Markerview™, MetabolitePilot™ and XCMS Online. The overlaps between the results of each peak-generating method were then investigated. To gauge the relevance of peak lists, a database search using the METLIN online database was performed to determine which features had accurate masses matching known metabolites as well as a secondary filtering based on MS/MS spectral matching. In this study, only a small proportion of all peaks (less than 10%) were common to all four software programs. Comparison of database searching results showed peaks found uniquely by one workflow have less chance of being found in the METLIN metabolomics database and are even less likely to be confirmed by MS/MS. It was shown that the performance of peak-generating workflows has a direct impact on untargeted metabolomics results. As it was demonstrated that the peaks found in more than one peak detection workflow have higher potential to be identified by accurate mass as well as MS/MS spectrum matching, it is suggested to use the overlap of different peak-picking workflows as preliminary peak lists for more rugged statistical analysis in global metabolomics investigations. Copyright © 2014 John Wiley & Sons, Ltd.

Effect of Genetics, Environment, and Phenotype on the Metabolome of Maize Hybrids Using GC/MS and LC/MS.

PubMed

Tang, Weijuan; Hazebroek, Jan; Zhong, Cathy; Harp, Teresa; Vlahakis, Chris; Baumhover, Brian; Asiago, Vincent

2017-06-28

We evaluated the variability of metabolites in various maize hybrids due to the effect of environment, genotype, phenotype as well as the interaction of the first two factors. We analyzed 480 forage and the same number of grain samples from 21 genetically diverse non-GM Pioneer brand maize hybrids, including some with drought tolerance and viral resistance phenotypes, grown at eight North American locations. As complementary platforms, both GC/MS and LC/MS were utilized to detect a wide diversity of metabolites. GC/MS revealed 166 and 137 metabolites in forage and grain samples, respectively, while LC/MS captured 1341 and 635 metabolites in forage and grain samples, respectively. Univariate and multivariate analyses were utilized to investigate the response of the maize metabolome to the environment, genotype, phenotype, and their interaction. Based on combined percentages from GC/MS and LC/MS datasets, the environment affected 36% to 84% of forage metabolites, while less than 7% were affected by genotype. The environment affected 12% to 90% of grain metabolites, whereas less than 27% were affected by genotype. Less than 10% and 11% of the metabolites were affected by phenotype in forage and grain, respectively. Unsupervised PCA and HCA analyses revealed similar trends, i.e., environmental effect was much stronger than genotype or phenotype effects. On the basis of comparisons of disease tolerant and disease susceptible hybrids, neither forage nor grain samples originating from different locations showed obvious phenotype effects. Our findings demonstrate that the combination of GC/MS and LC/MS based metabolite profiling followed by broad statistical analysis is an effective approach to identify the relative impact of environmental, genetic and phenotypic effects on the forage and grain composition of maize hybrids.

Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis.

PubMed

Hamerly, Timothy; Tripet, Brian P; Tigges, Michelle; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

2015-08-01

Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans , including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans 's consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans . Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.

Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

PubMed Central

Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle; Giannone, Richard J.; Wurch, Louie; Hettich, Robert L.; Podar, Mircea; Copié, Valerie; Bothner, Brian

2014-01-01

Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites. PMID:26273237

Annotation of the human serum metabolome by coupling three liquid chromatography methods to high-resolution mass spectrometry.

PubMed

Boudah, Samia; Olivier, Marie-Françoise; Aros-Calt, Sandrine; Oliveira, Lydie; Fenaille, François; Tabet, Jean-Claude; Junot, Christophe

2014-09-01

This work aims at evaluating the relevance and versatility of liquid chromatography coupled to high resolution mass spectrometry (LC/HRMS) for performing a qualitative and comprehensive study of the human serum metabolome. To this end, three different chromatographic systems based on a reversed phase (RP), hydrophilic interaction chromatography (HILIC) and a pentafluorophenylpropyl (PFPP) stationary phase were used, with detection in both positive and negative electrospray modes. LC/HRMS platforms were first assessed for their ability to detect, retain and separate 657 metabolite standards representative of the chemical families occurring in biological fluids. More than 75% were efficiently retained in either one LC-condition and less than 5% were exclusively retained by the RP column. These three LC/HRMS systems were then evaluated for their coverage of serum metabolome. The combination of RP, HILIC and PFPP based LC/HRMS methods resulted in the annotation of about 1328 features in the negative ionization mode, and 1358 in the positive ionization mode on the basis of their accurate mass and precise retention time in at least one chromatographic condition. Less than 12% of these annotations were shared by the three LC systems, which highlights their complementarity. HILIC column ensured the greatest metabolome coverage in the negative ionization mode, whereas PFPP column was the most effective in the positive ionization mode. Altogether, 192 annotations were confirmed using our spectral database and 74 others by performing MS/MS experiments. This resulted in the formal or putative identification of 266 metabolites, among which 59 are reported for the first time in human serum. Copyright © 2014 Elsevier B.V. All rights reserved.

The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

PubMed Central

Kriebel, Anita; Dörr, Claudia; Bandt, Susanne; Rist, Manuela; Roth, Alexander; Hummel, Eva; Kulling, Sabine; Hoffmann, Ingrid; Watzl, Bernhard

2016-01-01

Background The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible. Objective The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and1H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics. Methods Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,1H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods. Results The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway. Conclusions We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and1H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study. Trial Registration German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx) PMID:27421387

Metabolomics of Small Numbers of Cells: Metabolomic Profiling of 100, 1000, and 10000 Human Breast Cancer Cells.

PubMed

Luo, Xian; Li, Liang

2017-11-07

In cellular metabolomics, it is desirable to carry out metabolomic profiling using a small number of cells in order to save time and cost. In some applications (e.g., working with circulating tumor cells in blood), only a limited number of cells are available for analysis. In this report, we describe a method based on high-performance chemical isotope labeling (CIL) nanoflow liquid chromatography mass spectrometry (nanoLC-MS) for high-coverage metabolomic analysis of small numbers of cells (i.e., ≤10000 cells). As an example, 12 C-/ 13 C-dansyl labeling of the metabolites in lysates of 100, 1000, and 10000 MCF-7 breast cancer cells was carried out using a new labeling protocol tailored to handle small amounts of metabolites. Chemical-vapor-assisted ionization in a captivespray interface was optimized for improving metabolite ionization and increasing robustness of nanoLC-MS. Compared to microflow LC-MS, the nanoflow system provided much improved metabolite detectability with a significantly reduced sample amount required for analysis. Experimental duplicate analyses of biological triplicates resulted in the detection of 1620 ± 148, 2091 ± 89 and 2402 ± 80 (n = 6) peak pairs or metabolites in the amine/phenol submetabolome from the 12 C-/ 13 C-dansyl labeled lysates of 100, 1000, and 10000 cells, respectively. About 63-69% of these peak pairs could be either identified using dansyl labeled standard library or mass-matched to chemical structures in human metabolome databases. We envisage the routine applications of this method for high-coverage quantitative cellular metabolomics using a starting material of 10000 cells. Even for analyzing 100 or 1000 cells, although the metabolomic coverage is reduced from the maximal coverage, this method can still detect thousands of metabolites, allowing the analysis of a large fraction of the metabolome and focused analysis of the detectable metabolites.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

NASA Astrophysics Data System (ADS)

Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

2016-12-01

Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

PubMed

Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

2017-12-01

Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

PubMed

Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

2016-07-01

Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas Chromatography-Mass spectrometry.

Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

PubMed

Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

2016-05-01

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research.

PubMed

Nassar, Ala F; Wu, Terence; Nassar, Samuel F; Wisnewski, Adam V

2017-02-01

Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

PubMed

García-Cañaveras, Juan Carlos; López, Silvia; Castell, José Vicente; Donato, M Teresa; Lahoz, Agustín

2016-02-01

MS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (-) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids.

EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data

PubMed Central

2012-01-01

Background Downstream applications in metabolomics, as well as mathematical modelling, require data in a quantitative format, which may also necessitate the automated and simultaneous quantification of numerous metabolites. Although numerous applications have been previously developed for metabolomics data handling, automated calibration and calculation of the concentrations in terms of μmol have not been carried out. Moreover, most of the metabolomics applications are designed for GC-MS, and would not be suitable for LC-MS, since in LC, the deviation in the retention time is not linear, which is not taken into account in these applications. Moreover, only a few are web-based applications, which could improve stand-alone software in terms of compatibility, sharing capabilities and hardware requirements, even though a strong bandwidth is required. Furthermore, none of these incorporate asynchronous communication to allow real-time interaction with pre-processed results. Findings Here, we present EasyLCMS (http://www.easylcms.es/), a new application for automated quantification which was validated using more than 1000 concentration comparisons in real samples with manual operation. The results showed that only 1% of the quantifications presented a relative error higher than 15%. Using clustering analysis, the metabolites with the highest relative error distributions were identified and studied to solve recurrent mistakes. Conclusions EasyLCMS is a new web application designed to quantify numerous metabolites, simultaneously integrating LC distortions and asynchronous web technology to present a visual interface with dynamic interaction which allows checking and correction of LC-MS raw data pre-processing results. Moreover, quantified data obtained with EasyLCMS are fully compatible with numerous downstream applications, as well as for mathematical modelling in the systems biology field. PMID:22884039

Annotation: a computational solution for streamlining metabolomics analysis

PubMed Central

Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Benton, H. Paul; Siuzdak, Gary

2017-01-01

Metabolite identification is still considered an imposing bottleneck in liquid chromatography mass spectrometry (LC/MS) untargeted metabolomics. The identification workflow usually begins with detecting relevant LC/MS peaks via peak-picking algorithms and retrieving putative identities based on accurate mass searching. However, accurate mass search alone provides poor evidence for metabolite identification. For this reason, computational annotation is used to reveal the underlying metabolites monoisotopic masses, improving putative identification in addition to confirmation with tandem mass spectrometry. This review examines LC/MS data from a computational and analytical perspective, focusing on the occurrence of neutral losses and in-source fragments, to understand the challenges in computational annotation methodologies. Herein, we examine the state-of-the-art strategies for computational annotation including: (i) peak grouping or full scan (MS1) pseudo-spectra extraction, i.e., clustering all mass spectral signals stemming from each metabolite; (ii) annotation using ion adduction and mass distance among ion peaks; (iii) incorporation of biological knowledge such as biotransformations or pathways; (iv) tandem MS data; and (v) metabolite retention time calibration, usually achieved by prediction from molecular descriptors. Advantages and pitfalls of each of these strategies are discussed, as well as expected future trends in computational annotation. PMID:29039932

Automated LC-HRMS(/MS) Approach for the Annotation of Fragment Ions Derived from Stable Isotope Labeling-Assisted Untargeted Metabolomics

PubMed Central

2014-01-01

Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native 12C- and uniformly 13C (U-13C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-13C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research. PMID:24965664

Enzyme-driven metabolomic screening: a proof-of-principle method for discovery of plant defence compounds targeted by pathogens.

PubMed

Carere, Jason; Colgrave, Michelle L; Stiller, Jiri; Liu, Chunji; Manners, John M; Kazan, Kemal; Gardiner, Donald M

2016-11-01

Plants produce a variety of secondary metabolites to defend themselves from pathogen attack, while pathogens have evolved to overcome plant defences by producing enzymes that degrade or modify these defence compounds. However, many compounds targeted by pathogen enzymes currently remain enigmatic. Identifying host compounds targeted by pathogen enzymes would enable us to understand the potential importance of such compounds in plant defence and modify them to make them insensitive to pathogen enzymes. Here, a proof of concept metabolomics-based method was developed to discover plant defence compounds modified by pathogens using two pathogen enzymes with known targets in wheat and tomato. Plant extracts treated with purified pathogen enzymes were subjected to LC-MS, and the relative abundance of metabolites before and after treatment were comparatively analysed. Using two enzymes from different pathogens the in planta targets could be found by combining relatively simple enzymology with the power of untargeted metabolomics. Key to the method is dataset simplification based on natural isotope occurrence and statistical filtering, which can be scripted. The method presented here will aid in our understanding of plant-pathogen interactions and may lead to the development of new plant protection strategies. © 2016 CSIRO. New Phytologist © 2016 New Phytologist Trust.

Time-saving design of experiment protocol for optimization of LC-MS data processing in metabolomic approaches.

PubMed

Zheng, Hong; Clausen, Morten Rahr; Dalsgaard, Trine Kastrup; Mortensen, Grith; Bertram, Hanne Christine

2013-08-06

We describe a time-saving protocol for the processing of LC-MS-based metabolomics data by optimizing parameter settings in XCMS and threshold settings for removing noisy and low-intensity peaks using design of experiment (DoE) approaches including Plackett-Burman design (PBD) for screening and central composite design (CCD) for optimization. A reliability index, which is based on evaluation of the linear response to a dilution series, was used as a parameter for the assessment of data quality. After identifying the significant parameters in the XCMS software by PBD, CCD was applied to determine their values by maximizing the reliability and group indexes. Optimal settings by DoE resulted in improvements of 19.4% and 54.7% in the reliability index for a standard mixture and human urine, respectively, as compared with the default setting, and a total of 38 h was required to complete the optimization. Moreover, threshold settings were optimized by using CCD for further improvement. The approach combining optimal parameter setting and the threshold method improved the reliability index about 9.5 times for a standards mixture and 14.5 times for human urine data, which required a total of 41 h. Validation results also showed improvements in the reliability index of about 5-7 times even for urine samples from different subjects. It is concluded that the proposed methodology can be used as a time-saving approach for improving the processing of LC-MS-based metabolomics data.

Determination of total concentration of chemically labeled metabolites as a means of metabolome sample normalization and sample loading optimization in mass spectrometry-based metabolomics.

PubMed

Wu, Yiman; Li, Liang

2012-12-18

For mass spectrometry (MS)-based metabolomics, it is important to use the same amount of starting materials from each sample to compare the metabolome changes in two or more comparative samples. Unfortunately, for biological samples, the total amount or concentration of metabolites is difficult to determine. In this work, we report a general approach of determining the total concentration of metabolites based on the use of chemical labeling to attach a UV absorbent to the metabolites to be analyzed, followed by rapid step-gradient liquid chromatography (LC) UV detection of the labeled metabolites. It is shown that quantification of the total labeled analytes in a biological sample facilitates the preparation of an appropriate amount of starting materials for MS analysis as well as the optimization of the sample loading amount to a mass spectrometer for achieving optimal detectability. As an example, dansylation chemistry was used to label the amine- and phenol-containing metabolites in human urine samples. LC-UV quantification of the labeled metabolites could be optimally performed at the detection wavelength of 338 nm. A calibration curve established from the analysis of a mixture of 17 labeled amino acid standards was found to have the same slope as that from the analysis of the labeled urinary metabolites, suggesting that the labeled amino acid standard calibration curve could be used to determine the total concentration of the labeled urinary metabolites. A workflow incorporating this LC-UV metabolite quantification strategy was then developed in which all individual urine samples were first labeled with (12)C-dansylation and the concentration of each sample was determined by LC-UV. The volumes of urine samples taken for producing the pooled urine standard were adjusted to ensure an equal amount of labeled urine metabolites from each sample was used for the pooling. The pooled urine standard was then labeled with (13)C-dansylation. Equal amounts of the (12)C-labeled individual sample and the (13)C-labeled pooled urine standard were mixed for LC-MS analysis. This way of concentration normalization among different samples with varying concentrations of total metabolites was found to be critical for generating reliable metabolome profiles for comparison.

Metabolic Disturbances in Adult-Onset Still's Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis.

PubMed

Chen, Der-Yuan; Chen, Yi-Ming; Chien, Han-Ju; Lin, Chi-Chen; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting; Lai, Chien-Chen

2016-01-01

Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still's disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis.

Looking into aqueous humor through metabolomics spectacles - exploring its metabolic characteristics in relation to myopia.

PubMed

Barbas-Bernardos, Cecilia; Armitage, Emily G; García, Antonia; Mérida, Salvador; Navea, Amparo; Bosch-Morell, Francisco; Barbas, Coral

2016-08-05

Aqueous humor is the transparent fluid found in the anterior chamber of the eye that provides the metabolic requirements to the avascular tissues surrounding it. Despite the fact that metabolomics could be a powerful tool in the characterization of this biofluid and in revealing metabolic signatures of common ocular diseases such as myopia, it has never to our knowledge previously been applied in humans. In this research a novel method for the analysis of aqueous humor is presented to show its application in the characterization of this biofluid using CE-MS. The method was extended to a dual platform method (CE-MS and LC-MS) in order to compare samples from patients with different severities of myopia in order to explore the disease from the metabolic phenotype point of view. With this method, a profound knowledge of the metabolites present in human aqueous humor has been obtained: over 40 metabolites were reproducibly and simultaneously identified from a low volume of sample by CE-MS, including among others, a vast number of amino acids and derivatives. When this method was extended to study groups of patients with high or low myopia in both CE-MS and LC-MS, it has been possible to identify over 20 significantly different metabolite and lipid signatures that distinguish patients based on the severity of myopia. Among these, the most notable higher abundant metabolites in high myopia were aminooctanoic acid, arginine, citrulline and sphinganine while features of low myopia were aminoundecanoic acid, dihydro-retinoic acid and cysteinylglycine disulfide. This dual platform approach offered complementarity such that different metabolites were detected in each technique. Together the experiments presented provide a whelm of valuable information about human aqueous humor and myopia, proving the utility of non-targeted metabolomics for the first time in analyzing this type of sample and the metabolic phenotype of this disease. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomics-Based Elucidation of Active Metabolic Pathways in Erythrocytes and HSC-Derived Reticulocytes.

PubMed

Srivastava, Anubhav; Evans, Krystal J; Sexton, Anna E; Schofield, Louis; Creek, Darren J

2017-04-07

A detailed analysis of the metabolic state of human-stem-cell-derived erythrocytes allowed us to characterize the existence of active metabolic pathways in younger reticulocytes and compare them to mature erythrocytes. Using high-resolution LC-MS-based untargeted metabolomics, we found that reticulocytes had a comparatively much richer repertoire of metabolites, which spanned a range of metabolite classes. An untargeted metabolomics analysis using stable-isotope-labeled glucose showed that only glycolysis and the pentose phosphate pathway actively contributed to the biosynthesis of metabolites in erythrocytes, and these pathways were upregulated in reticulocytes. Most metabolite species found to be enriched in reticulocytes were residual pools of metabolites produced by earlier erythropoietic processes, and their systematic depletion in mature erythrocytes aligns with the simplification process, which is also seen at the cellular and the structural level. Our work shows that high-resolution LC-MS-based untargeted metabolomics provides a global coverage of the biochemical species that are present in erythrocytes. However, the incorporation of stable isotope labeling provides a more accurate description of the active metabolic processes that occur in each developmental stage. To our knowledge, this is the first detailed characterization of the active metabolic pathways of the erythroid lineage, and it provides a rich database for understanding the physiology of the maturation of reticulocytes into mature erythrocytes.

Non-targeted metabolomic approach reveals urinary metabolites linked to steroid biosynthesis pathway after ingestion of citrus juice.

PubMed

Medina, S; Ferreres, F; García-Viguera, C; Horcajada, M N; Orduna, J; Savirón, M; Zurek, G; Martínez-Sanz, J M; Gil, J I; Gil-Izquierdo, A

2013-01-15

Citrus juice intake has been highlighted because of its health-promoting effects. LC-MS based metabolomics approaches are applied to obtain a better knowledge on changes in the concentration of metabolites due to its dietary intake and allow a better understanding of involved metabolic pathways. Eight volunteers daily consumed 400 mL of juice for four consecutive days and urine samples were collected before intake and 24h after each citrus juice intake. Urine samples were analysed by nanoHPLC-q-TOF, followed by principal component analysis (PCA) and Student's t-test (p<0.05). PCA showed a separation between two groups (before and after citrus juice consumption). This approach allowed the identification of four endocrine compounds (tetrahydroaldosterone-3-glucuronide, cortolone-3-glucuronide, testosterone-glucuronide and 17-hydroxyprogesterone), which belonged to the steroid biosynthesis pathway as significant metabolites upregulated by citrus juice intake. Additionally, these results confirmed the importance of using the non-targeted metabolomics technique to identify new endogenous metabolites, up- or down-regulated as a consequence of food intake. Copyright © 2012 Elsevier Ltd. All rights reserved.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.

2004-11-01

A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

Development of isotope labeling LC-MS for human salivary metabolomics and application to profiling metabolome changes associated with mild cognitive impairment.

PubMed

Zheng, Jiamin; Dixon, Roger A; Li, Liang

2012-12-18

Saliva is a readily available biofluid that may contain metabolites of interest for diagnosis and prognosis of diseases. In this work, a differential (13)C/(12)C isotope dansylation labeling method, combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS), is described for quantitative profiling of the human salivary metabolome. New strategies are presented to optimize the sample preparation and LC-MS detection processes. The strategies allow the use of as little of 5 μL of saliva sample as a starting material to determine the concentration changes of an average of 1058 ion pairs or putative metabolites in comparative saliva samples. The overall workflow consists of several steps including acetone-induced protein precipitation, (12)C-dansylation labeling of the metabolites, and LC-UV measurement of the total concentration of the labeled metabolites in individual saliva samples. A pooled sample was prepared from all the individual samples and labeled with (13)C-dansylation to serve as a reference. Using this metabolome profiling method, it was found that compatible metabolome results could be obtained after saliva samples were stored in tubes normally used for genetic material collection at room temperature, -20 °C freezer, and -80 °C freezer over a period of 1 month, suggesting that many saliva samples already collected in genomic studies could become a valuable resource for metabolomics studies, although the effect of much longer term of storage remains to be determined. Finally, the developed method was applied for analyzing the metabolome changes of two different groups: normal healthy older adults and comparable older adults with mild cognitive impairment (MCI). Top-ranked 18 metabolites successfully distinguished the two groups, among which seven metabolites were putatively identified while one metabolite, taurine, was definitively identified.

Effects of sample injection amount and time-of-flight mass spectrometric detection dynamic range on metabolome analysis by high-performance chemical isotope labeling LC-MS.

PubMed

Zhou, Ruokun; Li, Liang

2015-04-06

The effect of sample injection amount on metabolome analysis in a chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) platform was investigated. The performance of time-of-flight (TOF) mass spectrometers with and without a high-dynamic-range (HD) detection system was compared in the analysis of (12)C2/(13)C2-dansyl labeled human urine samples. An average of 1635 ± 21 (n = 3) peak pairs or putative metabolites was detected using the HD-TOF-MS, compared to 1429 ± 37 peak pairs from a conventional or non-HD TOF-MS. In both instruments, signal saturation was observed. However, in the HD-TOF-MS, signal saturation was mainly caused by the ionization process, while in the non-HD TOF-MS, it was caused by the detection process. To extend the MS detection range in the non-HD TOF-MS, an automated switching from using (12)C to (13)C-natural abundance peaks for peak ratio calculation when the (12)C peaks are saturated has been implemented in IsoMS, a software tool for processing CIL LC-MS data. This work illustrates that injecting an optimal sample amount is important to maximize the metabolome coverage while avoiding the sample carryover problem often associated with over-injection. A TOF mass spectrometer with an enhanced detection dynamic range can also significantly increase the number of peak pairs detected. In chemical isotope labeling (CIL) LC-MS, relative metabolite quantification is done by measuring the peak ratio of a (13)C2-/(12)C2-labeled peak pair for a given metabolite present in two comparative samples. The dynamic range of peak ratio measurement does not need to be very large, as only subtle changes of metabolite concentrations are encountered in most metabolomic studies where relative metabolome quantification of different groups of samples is performed. However, the absolute concentrations of different metabolites can be very different, requiring a technique to provide a wide detection dynamic range to allow the detection of as many peak pairs as possible. In this work, we demonstrated that controlling the sample injection amount into LC-MS was critical to achieve the optimal detectability while avoiding sample carry-over problem. In addition, the use of a high-dynamic-range TOF system increased the number of peak pairs detected, compared to a conventional TOF system. We also investigated the ionization and detection saturation factors limiting the dynamic range of detection. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras. Copyright © 2014 Elsevier B.V. All rights reserved.

Metabolomic analysis-Addressing NMR and LC-MS related problems in human feces sample preparation.

PubMed

Moosmang, Simon; Pitscheider, Maria; Sturm, Sonja; Seger, Christoph; Tilg, Herbert; Halabalaki, Maria; Stuppner, Hermann

2017-10-31

Metabolomics is a well-established field in fundamental clinical research with applications in different human body fluids. However, metabolomic investigations in feces are currently an emerging field. Fecal sample preparation is a demanding task due to high complexity and heterogeneity of the matrix. To gain access to the information enclosed in human feces it is necessary to extract the metabolites and make them accessible to analytical platforms like NMR or LC-MS. In this study different pre-analytical parameters and factors were investigated i.e. water content, different extraction solvents, influence of freeze-drying and homogenization, ratios of sample weight to extraction solvent, and their respective impact on metabolite profiles acquired by NMR and LC-MS. The results indicate that profiles are strongly biased by selection of extraction solvent or drying of samples, which causes different metabolites to be lost, under- or overstated. Additionally signal intensity and reproducibility of the measurement were found to be strongly dependent on sample pre-treatment steps: freeze-drying and homogenization lead to improved release of metabolites and thus increased signals, but at the same time induced variations and thus deteriorated reproducibility. We established the first protocol for extraction of human fecal samples and subsequent measurement with both complementary techniques NMR and LC-MS. Copyright © 2017 Elsevier B.V. All rights reserved.

RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli.

PubMed

McCloskey, Douglas; Xu, Julia; Schrübbers, Lars; Christensen, Hanne B; Herrgård, Markus J

2018-04-25

Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing. Copyright © 2018. Published by Elsevier Inc.

Supporting metabolomics with adaptable software: design architectures for the end-user.

PubMed

Sarpe, Vladimir; Schriemer, David C

2017-02-01

Large and disparate sets of LC-MS data are generated by modern metabolomics profiling initiatives, and while useful software tools are available to annotate and quantify compounds, the field requires continued software development in order to sustain methodological innovation. Advances in software development practices allow for a new paradigm in tool development for metabolomics, where increasingly the end-user can develop or redeploy utilities ranging from simple algorithms to complex workflows. Resources that provide an organized framework for development are described and illustrated with LC-MS processing packages that have leveraged their design tools. Full access to these resources depends in part on coding experience, but the emergence of workflow builders and pluggable frameworks strongly reduces the skill level required. Developers in the metabolomics community are encouraged to use these resources and design content for uptake and reuse. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of subacute effects of two types of pyrethroid insecticides using metabolomics methods.

PubMed

Miao, Jiyan; Wang, Dezhen; Yan, Jin; Wang, Yao; Teng, Miaomiao; Zhou, Zhiqiang; Zhu, Wentao

2017-11-01

In this study, 1 H NMR based metabolomics analysis, LC-MS/MS based serum metabolomics and histopathology techniques were used to investigate the toxic effects of subacute exposure to two types of pyrethroid insecticides bifenthrin and lambda-cyhalothrin in mice. Metabolomic analysis of tissues extracts and serum showed that these two types of pyrethroid insecticides resulted in alterations of metabolites in the liver, kidney and serum of mice. Based on the altered metabolites, several significant pathways were identified, which are associated with gut microbial metabolism, lipid metabolism, nucleotide catabolism, tyrosine metabolism and energy metabolism. The results showed that bifenthrin and lambda-cyhalothrin have similarities in disruption of metabolic pathways in kidney, indicating that the toxicological mechanisms of these two types of insecticides have some likeness to each other. This study may provide novel insight into revealing differences of toxicological mechanisms between these two types of pyrethroid insecticides. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolomics: A Primer.

PubMed

Liu, Xiaojing; Locasale, Jason W

2017-04-01

Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future. Copyright © 2017 Elsevier Ltd. All rights reserved.

MassCascade: Visual Programming for LC-MS Data Processing in Metabolomics.

PubMed

Beisken, Stephan; Earll, Mark; Portwood, David; Seymour, Mark; Steinbeck, Christoph

2014-04-01

Liquid chromatography coupled to mass spectrometry (LC-MS) is commonly applied to investigate the small molecule complement of organisms. Several software tools are typically joined in custom pipelines to semi-automatically process and analyse the resulting data. General workflow environments like the Konstanz Information Miner (KNIME) offer the potential of an all-in-one solution to process LC-MS data by allowing easy integration of different tools and scripts. We describe MassCascade and its workflow plug-in for processing LC-MS data. The Java library integrates frequently used algorithms in a modular fashion, thus enabling it to serve as back-end for graphical front-ends. The functions available in MassCascade have been encapsulated in a plug-in for the workflow environment KNIME, allowing combined use with e.g. statistical workflow nodes from other providers and making the tool intuitive to use without knowledge of programming. The design of the software guarantees a high level of modularity where processing functions can be quickly replaced or concatenated. MassCascade is an open-source library for LC-MS data processing in metabolomics. It embraces the concept of visual programming through its KNIME plug-in, simplifying the process of building complex workflows. The library was validated using open data.

Metabolomic Strategies Involving Mass Spectrometry Combined with Liquid and Gas Chromatography.

PubMed

Lopes, Aline Soriano; Cruz, Elisa Castañeda Santa; Sussulini, Alessandra; Klassen, Aline

2017-01-01

Amongst all omics sciences, there is no doubt that metabolomics is undergoing the most important growth in the last decade. The advances in analytical techniques and data analysis tools are the main factors that make possible the development and establishment of metabolomics as a significant research field in systems biology. As metabolomic analysis demands high sensitivity for detecting metabolites present in low concentrations in biological samples, high-resolution power for identifying the metabolites and wide dynamic range to detect metabolites with variable concentrations in complex matrices, mass spectrometry is being the most extensively used analytical technique for fulfilling these requirements. Mass spectrometry alone can be used in a metabolomic analysis; however, some issues such as ion suppression may difficultate the quantification/identification of metabolites with lower concentrations or some metabolite classes that do not ionise as well as others. The best choice is coupling separation techniques, such as gas or liquid chromatography, to mass spectrometry, in order to improve the sensitivity and resolution power of the analysis, besides obtaining extra information (retention time) that facilitates the identification of the metabolites, especially when considering untargeted metabolomic strategies. In this chapter, the main aspects of mass spectrometry (MS), liquid chromatography (LC) and gas chromatography (GC) are discussed, and recent clinical applications of LC-MS and GC-MS are also presented.

Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

PubMed

Cuykx, Matthias; Negreira, Noelia; Beirnaert, Charlie; Van den Eede, Nele; Rodrigues, Robim; Vanhaecke, Tamara; Laukens, Kris; Covaci, Adrian

2017-03-03

Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of human plasma metabolites across different liquid chromatography/mass spectrometry platforms: Cross-platform transferable chemical signatures.

PubMed

Telu, Kelly H; Yan, Xinjian; Wallace, William E; Stein, Stephen E; Simón-Manso, Yamil

2016-03-15

The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different liquid chromatography/mass spectrometry (LC/MS) platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC/MS platforms using reversed-phase chromatography and different chromatographic scales (conventional HPLC, UHPLC and nanoLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (relative standard deviation (RSD) <2%); however, substantial differences were found in the LC/MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data.

PubMed

Creek, Darren J; Jankevics, Andris; Burgess, Karl E V; Breitling, Rainer; Barrett, Michael P

2012-04-01

The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists. IDEOM is provided free of charge at http://mzmatch.sourceforge.net/ideom.html, as a macro-enabled spreadsheet (.xlsb). Implementation requires Microsoft Excel (2007 or later). R is also required for full functionality. michael.barrett@glasgow.ac.uk Supplementary data are available at Bioinformatics online.

Analysis of Human Plasma Metabolites across Different Liquid Chromatography - Mass Spectrometry Platforms: Cross-platform Transferable Chemical Signatures

PubMed Central

Telu, Kelly H.; Yan, Xinjian; Wallace, William E.; Stein, Stephen E.; Simón-Manso, Yamil

2016-01-01

RATIONALE The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different LC-MS platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. METHODS Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC-MS platforms using reversed phase chromatography and different chromatographic scales (nano, conventional and UHPLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). RESULTS Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (RSD < 2%); however, substantial differences were found in the LC-MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. CONLUSIONS Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable. PMID:26842580

In vivo microsampling to capture the elusive exposome

NASA Astrophysics Data System (ADS)

Bessonneau, Vincent; Ings, Jennifer; McMaster, Mark; Smith, Richard; Bragg, Leslie; Servos, Mark; Pawliszyn, Janusz

2017-03-01

Loss and/or degradation of small molecules during sampling, sample transportation and storage can adversely impact biological interpretation of metabolomics data. In this study, we performed in vivo sampling using solid-phase microextraction (SPME) in combination with non-targeted liquid chromatography and high-resolution tandem mass spectrometry (LC-MS/MS) to capture the fish tissue exposome using molecular networking analysis, and the results were contrasted with molecular differences obtained with ex vivo SPME sampling. Based on 494 MS/MS spectra comparisons, we demonstrated that in vivo SPME sampling provided better extraction and stabilization of highly reactive molecules, such as 1-oleoyl-sn-glycero-3-phosphocholine and 1-palmitoleoyl-glycero-3-phosphocholine, from fish tissue samples. This sampling approach, that minimizes sample handling and preparation, offers the opportunity to perform longitudinal monitoring of the exposome in biological systems and improve the reliability of exposure-measurement in exposome-wide association studies.

In vivo microsampling to capture the elusive exposome

PubMed Central

Bessonneau, Vincent; Ings, Jennifer; McMaster, Mark; Smith, Richard; Bragg, Leslie; Servos, Mark; Pawliszyn, Janusz

2017-01-01

Loss and/or degradation of small molecules during sampling, sample transportation and storage can adversely impact biological interpretation of metabolomics data. In this study, we performed in vivo sampling using solid-phase microextraction (SPME) in combination with non-targeted liquid chromatography and high-resolution tandem mass spectrometry (LC-MS/MS) to capture the fish tissue exposome using molecular networking analysis, and the results were contrasted with molecular differences obtained with ex vivo SPME sampling. Based on 494 MS/MS spectra comparisons, we demonstrated that in vivo SPME sampling provided better extraction and stabilization of highly reactive molecules, such as 1-oleoyl-sn-glycero-3-phosphocholine and 1-palmitoleoyl-glycero-3-phosphocholine, from fish tissue samples. This sampling approach, that minimizes sample handling and preparation, offers the opportunity to perform longitudinal monitoring of the exposome in biological systems and improve the reliability of exposure-measurement in exposome-wide association studies. PMID:28266605

Porous Graphitic Carbon Liquid Chromatography-Mass Spectrometry Analysis of Drought Stress-Responsive Raffinose Family Oligosaccharides in Plant Tissues.

PubMed

Jorge, Tiago F; Florêncio, Maria H; António, Carla

2017-01-01

Drought is a major limiting factor in agriculture and responsible for dramatic crop yield losses worldwide. The adjustment of the metabolic status via accumulation of drought stress-responsive osmolytes is one of the many strategies that some plants have developed to cope with water deficit conditions. Osmolytes are highly polar compounds, analysis of whcih is difficult with typical reversed-phase chromatography. Porous graphitic carbon (PGC) has shown to be a suitable alternative to reversed-phase stationary phases for the analysis of highly polar compounds typically found in the plant metabolome. In this chapter, we describe the development and validation of a PGC-based liquid chromatography tandem mass spectrometry (LC-MS n ) method suitable for the target analysis of water-soluble carbohydrates, such as raffinose family oligosaccharides (RFOs). We present detailed information regarding PGC column equilibration, LC-MS n system operation, data analysis, and important notes to be considered during the steps of method development and validation.

Global metabolomics reveals potential urinary biomarkers of esophageal squamous cell carcinoma for diagnosis and staging

NASA Astrophysics Data System (ADS)

Xu, Jing; Chen, Yanhua; Zhang, Ruiping; He, Jiuming; Song, Yongmei; Wang, Jingbo; Wang, Huiqing; Wang, Luhua; Zhan, Qimin; Abliz, Zeper

2016-10-01

We performed a metabolomics study using liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis (MVDA) to discriminate global urine profiles in urine samples from esophageal squamous cell carcinoma (ESCC) patients and healthy controls (NC). Our work evaluated the feasibility of employing urine metabolomics for the diagnosis and staging of ESCC. The satisfactory classification between the healthy controls and ESCC patients was obtained using the MVDA model, and obvious classification of early-stage and advanced-stage patients was also observed. The results suggest that the combination of LC-MS analysis and MVDA may have potential applications for ESCC diagnosis and staging. We then conducted LC-MS/MS experiments to identify the potential biomarkers with large contributions to the discrimination. A total of 83 potential diagnostic biomarkers for ESCC were screened out, and 19 potential biomarkers were identified; the variations between the differences in staging using these potential biomarkers were further analyzed. These biomarkers may not be unique to ESCCs, but instead result from any malignant disease. To further elucidate the pathophysiology of ESCC, we studied related metabolic pathways and found that ESCC is associated with perturbations of fatty acid β-oxidation and the metabolism of amino acids, purines, and pyrimidines.

Bioprospecting Chemical Diversity and Bioactivity in a Marine Derived Aspergillus terreus.

PubMed

Adpressa, Donovon A; Loesgen, Sandra

2016-02-01

A comparative metabolomic study of a marine derived fungus (Aspergillus terreus) grown under various culture conditions is presented. The fungus was grown in eleven different culture conditions using solid agar, broth cultures, or grain based media (OSMAC). Multivariate analysis of LC/MS data from the organic extracts revealed drastic differences in the metabolic profiles and guided our subsequent isolation efforts. The compound 7-desmethylcitreoviridin was isolated and identified, and is fully described for the first time. In addition, 16 known fungal metabolites were also isolated and identified. All compounds were elucidated by detailed spectroscopic analysis and tested for antibacterial activities against five human pathogens and tested for cytotoxicity. This study demonstrates that LC/MS based multivariate analysis provides a simple yet powerful tool to analyze the metabolome of a single fungal strain grown under various conditions. This approach allows environmentally-induced changes in metabolite expression to be rapidly visualized, and uses these differences to guide the discovery of new bioactive molecules. Copyright © 2016 Verlag Helvetica Chimica Acta AG, Zürich.

Target-decoy Based False Discovery Rate Estimation for Large-scale Metabolite Identification.

PubMed

Wang, Xusheng; Jones, Drew R; Shaw, Timothy I; Cho, Ji-Hoon; Wang, Yuanyuan; Tan, Haiyan; Xie, Boer; Zhou, Suiping; Li, Yuxin; Peng, Junmin

2018-05-23

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. In this study, we report a novel method for estimating false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis, and was also evaluated with two other metabolomics tools, mzMatch and mzMine 2. The reliability of FDR calculation was examined by false datasets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled with the target-decoy strategy to process unlabeled and stable-isotope labeled metabolomic datasets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Discrimination of Four Marine Biofilm-Forming Bacteria by LC-MS Metabolomics and Influence of Culture Parameters.

PubMed

Favre, Laurie; Ortalo-Magné, Annick; Greff, Stéphane; Pérez, Thierry; Thomas, Olivier P; Martin, Jean-Charles; Culioli, Gérald

2017-05-05

Most marine bacteria can form biofilms, and they are the main components of biofilms observed on marine surfaces. Biofilms constitute a widespread life strategy, as growing in such structures offers many important biological benefits. The molecular compounds expressed in biofilms and, more generally, the metabolomes of marine bacteria remain poorly studied. In this context, a nontargeted LC-MS metabolomics approach of marine biofilm-forming bacterial strains was developed. Four marine bacteria, Persicivirga (Nonlabens) mediterranea TC4 and TC7, Pseudoalteromonas lipolytica TC8, and Shewanella sp. TC11, were used as model organisms. The main objective was to search for some strain-specific bacterial metabolites and to determine how culture parameters (culture medium, growth phase, and mode of culture) may affect the cellular metabolism of each strain and thus the global interstrain metabolic discrimination. LC-MS profiling and statistical partial least-squares discriminant analyses showed that the four strains could be differentiated at the species level whatever the medium, the growth phase, or the mode of culture (planktonic vs biofilm). A MS/MS molecular network was subsequently built and allowed the identification of putative bacterial biomarkers. TC8 was discriminated by a series of ornithine lipids, while the P. mediterranea strains produced hydroxylated ornithine and glycine lipids. Among the P. mediterranea strains, TC7 extracts were distinguished by the occurrence of diamine derivatives, such as putrescine amides.

MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets.

PubMed

Edmands, William M B; Barupal, Dinesh K; Scalbert, Augustin

2015-03-01

MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R). All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC-MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository. © The Author 2014. Published by Oxford University Press.

An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry.

PubMed

Wang, Yang; Liu, Fang; Li, Peng; He, Chengwei; Wang, Ruibing; Su, Huanxing; Wan, Jian-Bo

2016-07-13

Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

PubMed

Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

2014-07-01

Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and discovering potential metabolite biomarkers for diagnosis of bladder cancer.

Sensitivity improvement in hydrophilic interaction chromatography negative mode electrospray ionization mass spectrometry using 2-(2-methoxyethoxy)ethanol as a post-column modifier for non-targeted metabolomics.

PubMed

Koch, Wendelin; Forcisi, Sara; Lehmann, Rainer; Schmitt-Kopplin, Philippe

2014-09-26

The application of ammonia acetate buffered liquid chromatography (LC) eluents is known to concomitantly lead to ion suppression when electrospray ionization mass spectrometry (ESI-MS) detection is used. In negative ESI mode, post column infusion of 2-(2-methoxyethoxy)ethanol (2-MEE) was shown in the literature to help to compensate this adverse effect occurring in reversed phase liquid chromatography mass spectrometry (RP-LC-MS) analyses. Here a setup of direct infusion and hydrophilic interaction chromatography (HILIC) post-column infusion experiments was established in order to investigate systematically the beneficial effects of 2-MEE. We demonstrate that, 2-MEE can help to improve ESI-MS sensitivity in HILIC too and reveal analyte structure specific behaviors. Our study indicates that 2-MEE especially improves ESI response for small and polar molecules. The ESI response of stable isotope labeled amino acids spiked into biological matrices increases up to 50-fold (i.e. D5-l-glutamic acid) when post column infusion of 2-MEE is applied. A non-targeted analysis of a pooled urine sample via HILIC-ESI-QTOF-MS supports this hypothesis. In direct infusion, the combined application of an ammonia acetate buffered solution together with 2-MEE results in an improved ESI response compared to a non-buffered solution. We observed up to 60-fold increased ESI response of l-lysine. We propose this effect is putatively caused by the formation of smaller ESI droplets and stripping of positive charge from ESI droplets due to evaporation of acetic acid anions. In summary, post-column infusion of 2-MEE especially enhances ESI response of small and polar molecules. Therefore it can be regarded as a valuable add-on in targeted or non-targeted metabolomic HILIC-MS studies since this method sets a focus on this molecule category. Copyright © 2014 Elsevier B.V. All rights reserved.

MetExtract: a new software tool for the automated comprehensive extraction of metabolite-derived LC/MS signals in metabolomics research.

PubMed

Bueschl, Christoph; Kluger, Bernhard; Berthiller, Franz; Lirk, Gerald; Winkler, Stephan; Krska, Rudolf; Schuhmacher, Rainer

2012-03-01

Liquid chromatography-mass spectrometry (LC/MS) is a key technique in metabolomics. Since the efficient assignment of MS signals to true biological metabolites becomes feasible in combination with in vivo stable isotopic labelling, our aim was to provide a new software tool for this purpose. An algorithm and a program (MetExtract) have been developed to search for metabolites in in vivo labelled biological samples. The algorithm makes use of the chromatographic characteristics of the LC/MS data and detects MS peaks fulfilling the criteria of stable isotopic labelling. As a result of all calculations, the algorithm specifies a list of m/z values, the corresponding number of atoms of the labelling element (e.g. carbon) together with retention time and extracted adduct-, fragment- and polymer ions. Its function was evaluated using native (12)C- and uniformly (13)C-labelled standard substances. MetExtract is available free of charge and warranty at http://code.google.com/p/metextract/. Precompiled executables are available for Windows operating systems. Supplementary data are available at Bioinformatics online.

Conventional and Advanced Separations in Mass Spectrometry-Based Metabolomics: Methodologies and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heyman, Heino M.; Zhang, Xing; Tang, Keqi

2016-02-16

Metabolomics is the quantitative analysis of all metabolites in a given sample. Due to the chemical complexity of the metabolome, optimal separations are required for comprehensive identification and quantification of sample constituents. This chapter provides an overview of both conventional and advanced separations methods in practice for reducing the complexity of metabolite extracts delivered to the mass spectrometer detector, and covers gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), supercritical fluid chromatography (SFC) and ion mobility spectrometry (IMS) separation techniques coupled with mass spectrometry (MS) as both uni-dimensional and as multi-dimensional approaches.

Metabolomic spectral libraries for data-independent SWATH liquid chromatography mass spectrometry acquisition.

PubMed

Bruderer, Tobias; Varesio, Emmanuel; Hidasi, Anita O; Duchoslav, Eva; Burton, Lyle; Bonner, Ron; Hopfgartner, Gérard

2018-03-01

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100 eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70 eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70 eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H] + and 483 in negative mode [M-H] - . MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia

PubMed Central

Erogbogbo, Folarin; May, Jasmine; Swihart, Mark; Prasad, Paras N.; Smart, Katie; Jack, Seif El; Korcyk, Dariusz; Webster, Mark; Stewart, Ralph; Zeng, Irene; Jullig, Mia; Bakeev, Katherine; Jamieson, Michelle; Kasabov, Nikolas; Gopalan, Banu; Liang, Linda; Hu, Raphael; Schliebs, Stefan; Villas-Boas, Silas; Gladding, Patrick

2013-01-01

Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment. PMID:24019856

Applying quantitative metabolomics based on chemical isotope labeling LC-MS for detecting potential milk adulterant in human milk.

PubMed

Mung, Dorothea; Li, Liang

2018-02-25

There is an increasing demand for donor human milk to feed infants for various reasons including that a mother may be unable to provide sufficient amounts of milk for their child or the milk is considered unsafe for the baby. Selling and buying human milk via the Internet has gained popularity. However, there is a risk of human milk sold containing other adulterants such as animal or plant milk. Analytical tools for rapid detection of adulterants in human milk are needed. We report a quantitative metabolomics method for detecting potential milk adulterants (soy, almond, cow, goat and infant formula milk) in human milk. It is based on the use of a high-performance chemical isotope labeling (CIL) LC-MS platform to profile the metabolome of an unknown milk sample, followed by multivariate or univariate comparison of the resultant metabolomic profile with that of human milk to determine the differences. Using dansylation LC-MS to profile the amine/phenol submetabolome, we could detect an average of 4129 ± 297 (n = 9) soy metabolites, 3080 ± 470 (n = 9) almond metabolites, 4256 ± 136 (n = 18) cow metabolites, 4318 ± 198 (n = 9) goat metabolites, 4444 ± 563 (n = 9) infant formula metabolites, and 4020 ± 375 (n = 30) human metabolites. This high level of coverage allowed us to readily differentiate the six different types of samples. From the analysis of binary mixtures of human milk containing 5, 10, 25, 50 and 75% other type of milk, we demonstrated that this method could be used to detect the presence of as low as 5% adulterant in human milk. We envisage that this method could be applied to detect contaminant or adulterant in other types of food or drinks. Copyright © 2017 Elsevier B.V. All rights reserved.

Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

PubMed

Reisetter, Anna C; Muehlbauer, Michael J; Bain, James R; Nodzenski, Michael; Stevens, Robert D; Ilkayeva, Olga; Metzger, Boyd E; Newgard, Christopher B; Lowe, William L; Scholtens, Denise M

2017-02-02

Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

Metabolic Analysis

NASA Astrophysics Data System (ADS)

Tolstikov, Vladimir V.

Analysis of the metabolome with coverage of all of the possibly detectable components in the sample, rather than analysis of each individual metabolite at a given time, can be accomplished by metabolic analysis. Targeted and/or nontargeted approaches are applied as needed for particular experiments. Monitoring hundreds or more metabolites at a given time requires high-throughput and high-end techniques that enable screening for relative changes in, rather than absolute concentrations of, compounds within a wide dynamic range. Most of the analytical techniques useful for these purposes use GC or HPLC/UPLC separation modules coupled to a fast and accurate mass spectrometer. GC separations require chemical modification (derivatization) before analysis, and work efficiently for the small molecules. HPLC separations are better suited for the analysis of labile and nonvolatile polar and nonpolar compounds in their native form. Direct infusion and NMR-based techniques are mostly used for fingerprinting and snap phenotyping, where applicable. Discovery and validation of metabolic biomarkers are exciting and promising opportunities offered by metabolic analysis applied to biological and biomedical experiments. We have demonstrated that GC-TOF-MS, HPLC/UPLC-RP-MS and HILIC-LC-MS techniques used for metabolic analysis offer sufficient metabolome mapping providing researchers with confident data for subsequent multivariate analysis and data mining.

Development of a Postcolumn Infused-Internal Standard Liquid Chromatography Mass Spectrometry Method for Quantitative Metabolomics Studies.

PubMed

Liao, Hsiao-Wei; Chen, Guan-Yuan; Wu, Ming-Shiang; Liao, Wei-Chih; Lin, Ching-Hung; Kuo, Ching-Hua

2017-02-03

Quantitative metabolomics has become much more important in clinical research in recent years. Individual differences in matrix effects (MEs) and the injection order effect are two major factors that reduce the quantification accuracy in liquid chromatography-electrospray ionization-mass spectrometry-based (LC-ESI-MS) metabolomics studies. This study proposed a postcolumn infused-internal standard (PCI-IS) combined with a matrix normalization factor (MNF) strategy to improve the analytical accuracy of quantitative metabolomics. The PCI-IS combined with the MNF method was applied for a targeted metabolomics study of amino acids (AAs). D8-Phenylalanine was used as the PCI-IS, and it was postcolumn-infused into the ESI interface for calibration purposes. The MNF was used to bridge the AA response in a standard solution with the plasma samples. The MEs caused signal changes that were corrected by dividing the AA signal intensities by the PCI-IS intensities after adjustment with the MNF. After the method validation, we evaluated the method applicability for breast cancer research using 100 plasma samples. The quantification results revealed that the 11 tested AAs exhibit an accuracy between 88.2 and 110.7%. The principal component analysis score plot revealed that the injection order effect can be successfully removed, and most of the within-group variation of the tested AAs decreased after the PCI-IS correction. Finally, targeted metabolomics studies on the AAs showed that tryptophan was expressed more in malignant patients than in the benign group. We anticipate that a similar approach can be applied to other endogenous metabolites to facilitate quantitative metabolomics studies.

The Human Urine Metabolome

PubMed Central

Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

2013-01-01

Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca. PMID:24023812

Liquid chromatography-mass spectrometry in metabolomics research: mass analyzers in ultra high pressure liquid chromatography coupling.

PubMed

Forcisi, Sara; Moritz, Franco; Kanawati, Basem; Tziotis, Dimitrios; Lehmann, Rainer; Schmitt-Kopplin, Philippe

2013-05-31

The present review gives an introduction into the concept of metabolomics and provides an overview of the analytical tools applied in non-targeted metabolomics with a focus on liquid chromatography (LC). LC is a powerful analytical tool in the study of complex sample matrices. A further development and configuration employing Ultra-High Pressure Liquid Chromatography (UHPLC) is optimized to provide the largest known liquid chromatographic resolution and peak capacity. Reasonably UHPLC plays an important role in separation and consequent metabolite identification of complex molecular mixtures such as bio-fluids. The most sensitive detectors for these purposes are mass spectrometers. Almost any mass analyzer can be optimized to identify and quantify small pre-defined sets of targets; however, the number of analytes in metabolomics is far greater. Optimized protocols for quantification of large sets of targets may be rendered inapplicable. Results on small target set analyses on different sample matrices are easily comparable with each other. In non-targeted metabolomics there is almost no analytical method which is applicable to all different matrices due to limitations pertaining to mass analyzers and chromatographic tools. The specifications of the most important interfaces and mass analyzers are discussed. We additionally provide an exemplary application in order to demonstrate the level of complexity which remains intractable up to date. The potential of coupling a high field Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ICR-FT/MS), the mass analyzer with the largest known mass resolving power, to UHPLC is given with an example of one human pre-treated plasma sample. This experimental example illustrates one way of overcoming the necessity of faster scanning rates in the coupling with UHPLC. The experiment enabled the extraction of thousands of features (analytical signals). A small subset of this compositional space could be mapped into a mass difference network whose topology shows specificity toward putative metabolite classes and retention time. Copyright © 2013 Elsevier B.V. All rights reserved.

REVIEW ARTICLE: Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes

NASA Astrophysics Data System (ADS)

Dunn, Warwick B.

2008-03-01

The functional levels of biological cells or organisms can be separated into the genome, transcriptome, proteome and metabolome. Of these the metabolome offers specific advantages to the investigation of the phenotype of biological systems. The investigation of the metabolome (metabolomics) has only recently appeared as a mainstream scientific discipline and is currently developing rapidly for the study of microbial, plant and mammalian metabolomes. The metabolome pipeline or workflow encompasses the processes of sample collection and preparation, collection of analytical data, raw data pre-processing, data analysis and data storage. Of these processes the collection of analytical data will be discussed in this review with specific interest shown in the application of mass spectrometry in the metabolomics pipeline. The current developments in mass spectrometry platforms (GC-MS, LC-MS, DIMS and imaging MS) and applications of specific interest will be highlighted. The current limitations of these platforms and applications will be discussed with areas requiring further development also highlighted. These include the detectable coverage of the metabolome, the identification of metabolites and the process of converting raw data to biological knowledge.

Liquid chromatography/mass spectrometry for the detection of ash tree metabolites following Emerald Ash Borer infestation.

PubMed

Stock, Naomi L; Doran, Michael C; Bonners, Ron F; March, Raymond E

2018-03-15

The Emerald Ash Borer (EAB), Agrilus planipennis, an invasive insect detected in the USA and Canada in 2002, is a threat to ash trees with both ecological and economic implications. Early detection of EAB-infestation is difficult due to lack of visible signs and symptoms in the early stages of attack, but is essential to prevent ash mortality. An efficient and reliable tool for the early detection of EAB-infestation would be advantageous. A mass spectrometry based metabolomics approach, using liquid chromatography/mass spectrometry (LC/MS), has been used to investigate the leaf metabolites of both healthy and EAB-infested trees. Leaves from 40 healthy and 40 EAB-infested trees were extracted and analyzed using LC/MS. Resulting data were examined to differentiate between foliage from healthy and EAB-infested trees. Possible biomarkers of EAB attack have been detected. Twenty-one metabolites with increased average ion intensity in EAB-infested ash tree samples and nine metabolites with increased average ion intensity in healthy ash tree samples were identified. Results of this study indicate that metabolomic screening of leaf samples using LC/MS can be useful as a potential tool for the early detection of EAB-infestation. Copyright © 2018 John Wiley & Sons, Ltd.

Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

PubMed

Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

2016-01-01

Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

Decreased glycolytic and tricarboxylic acid cycle intermediates coincide with peripheral nervous system oxidative stress in a murine model of type 2 diabetes.

PubMed

Hinder, Lucy M; Vivekanandan-Giri, Anuradha; McLean, Lisa L; Pennathur, Subramaniam; Feldman, Eva L

2013-01-01

Diabetic neuropathy (DN) is the most common complication of diabetes and is characterized by distal-to-proximal loss of peripheral nerve axons. The idea of tissue-specific pathological alterations in energy metabolism in diabetic complications-prone tissues is emerging. Altered nerve metabolism in type 1 diabetes models is observed; however, therapeutic strategies based on these models offer limited efficacy to type 2 diabetic patients with DN. Therefore, understanding how peripheral nerves metabolically adapt to the unique type 2 diabetic environment is critical to develop disease-modifying treatments. In the current study, we utilized targeted liquid chromatography-tandem mass spectrometry (LC/MS/MS) to characterize the glycolytic and tricarboxylic acid (TCA) cycle metabolomes in sural nerve, sciatic nerve, and dorsal root ganglia (DRG) from male type 2 diabetic mice (BKS.Cg-m+/+Lepr(db); db/db) and controls (db/+). We report depletion of glycolytic intermediates in diabetic sural nerve and sciatic nerve (glucose-6-phosphate, fructose-6-phosphate, fructose-1,6-bisphosphate (sural nerve only), 3-phosphoglycerate, 2-phosphoglycerate, phosphoenolpyruvate, and lactate), with no significant changes in DRG. Citrate and isocitrate TCA cycle intermediates were decreased in sural nerve, sciatic nerve, and DRG from diabetic mice. Utilizing LC/electrospray ionization/MS/MS and HPLC methods, we also observed increased protein and lipid oxidation (nitrotyrosine; hydroxyoctadecadienoic acids) in db/db tissue, with a proximal-to-distal increase in oxidative stress, with associated decreased aconitase enzyme activity. We propose a preliminary model, whereby the greater change in metabolomic profile, increase in oxidative stress, and decrease in TCA cycle enzyme activity may cause distal peripheral nerves to rely on truncated TCA cycle metabolism in the type 2 diabetes environment.

Comparative metabolomics in vanilla pod and vanilla bean revealing the biosynthesis of vanillin during the curing process of vanilla.

PubMed

Gu, Fenglin; Chen, Yonggan; Hong, Yinghua; Fang, Yiming; Tan, Lehe

2017-12-01

High-performance liquid chromatography-mass spectrometry (LC-MS) was used for comprehensive metabolomic fingerprinting of vanilla fruits prepared from the curing process. In this study, the metabolic changes of vanilla pods and vanilla beans were characterized using MS-based metabolomics to elucidate the biosynthesis of vanillin. The vanilla pods were significantly different from vanilla beans. Seven pathways of vanillin biosynthesis were constructed, namely, glucovanillin, glucose, cresol, capsaicin, vanillyl alcohol, tyrosine, and phenylalanine pathways. Investigations demonstrated that glucose, cresol, capsaicin, and vanillyl alcohol pathway were detected in a wide range of distribution in microbial metabolism. Thus, microorganisms might have participated in vanillin biosynthesis during vanilla curing. Furthermore, the ion strength of glucovanillin was stable, which indicated that glucovanillin only participated in the vanillin biosynthesis during the curing of vanilla.

Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma

PubMed Central

Wang, Hanghang; Muehlbauer, Michael J.; O’Neal, Sara K.; Newgard, Christopher B.; Hauser, Elizabeth R.; Shah, Svati H.

2017-01-01

The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma. PMID:28841195

Rumen fluid metabolomics analysis associated with feed efficiency on crossbred steers

USDA-ARS?s Scientific Manuscript database

The rumen has a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in feed efficiency, rumen fluid metabolomic analysis by LC-MS and multivariate/univariate statistical analysis were used to identify differences in r...

Galaxy-M: a Galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data.

PubMed

Davidson, Robert L; Weber, Ralf J M; Liu, Haoyu; Sharma-Oates, Archana; Viant, Mark R

2016-01-01

Metabolomics is increasingly recognized as an invaluable tool in the biological, medical and environmental sciences yet lags behind the methodological maturity of other omics fields. To achieve its full potential, including the integration of multiple omics modalities, the accessibility, standardization and reproducibility of computational metabolomics tools must be improved significantly. Here we present our end-to-end mass spectrometry metabolomics workflow in the widely used platform, Galaxy. Named Galaxy-M, our workflow has been developed for both direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LC-MS) metabolomics. The range of tools presented spans from processing of raw data, e.g. peak picking and alignment, through data cleansing, e.g. missing value imputation, to preparation for statistical analysis, e.g. normalization and scaling, and principal components analysis (PCA) with associated statistical evaluation. We demonstrate the ease of using these Galaxy workflows via the analysis of DIMS and LC-MS datasets, and provide PCA scores and associated statistics to help other users to ensure that they can accurately repeat the processing and analysis of these two datasets. Galaxy and data are all provided pre-installed in a virtual machine (VM) that can be downloaded from the GigaDB repository. Additionally, source code, executables and installation instructions are available from GitHub. The Galaxy platform has enabled us to produce an easily accessible and reproducible computational metabolomics workflow. More tools could be added by the community to expand its functionality. We recommend that Galaxy-M workflow files are included within the supplementary information of publications, enabling metabolomics studies to achieve greater reproducibility.

Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

PubMed

Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

2016-05-15

To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase.

PubMed

Lv, Haitao; Palacios, Gustavo; Hartil, Kirsten; Kurland, Irwin J

2011-04-01

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.

Metabolomic Responses of Arabidopsis Suspension Cells to Bicarbonate under Light and Dark Conditions

PubMed Central

Misra, Biswapriya B.; Yin, Zepeng; Geng, Sisi; de Armas, Evaldo; Chen, Sixue

2016-01-01

Global CO2 level presently recorded at 400 ppm is expected to reach 550 ppm in 2050, an increment likely to impact plant growth and productivity. Using targeted LC-MS and GC-MS platforms we quantified 229 and 29 metabolites, respectively in a time-course study to reveal short-term responses to different concentrations (1, 3, and 10 mM) of bicarbonate (HCO3−) under light and dark conditions. Results indicate that HCO3− treatment responsive metabolomic changes depend on the HCO3− concentration, time of treatment, and light/dark. Interestingly, 3 mM HCO3− concentration treatment induced more significantly changed metabolites than either lower or higher concentrations used. Flavonoid biosynthesis and glutathione metabolism were common to both light and dark-mediated responses in addition to showing concentration-dependent changes. Our metabolomics results provide insights into short-term plant cellular responses to elevated HCO3− concentrations as a result of ambient increases in CO2 under light and dark. PMID:27762345

Processing methods for differential analysis of LC/MS profile data

PubMed Central

Katajamaa, Mikko; Orešič, Matej

2005-01-01

Background Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. Results We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. Conclusion The software is freely available under the GNU General Public License and it can be obtained from the project web page at: . PMID:16026613

Processing methods for differential analysis of LC/MS profile data.

PubMed

Katajamaa, Mikko; Oresic, Matej

2005-07-18

Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. The software is freely available under the GNU General Public License and it can be obtained from the project web page at: http://mzmine.sourceforge.net/.

Discriminant biomarkers of acute respiratory distress syndrome associated to H1N1 influenza identified by metabolomics HPLC-QTOF-MS/MS platform.

PubMed

Ferrarini, Alessia; Righetti, Laura; Martínez, Ma Paz; Fernández-López, Mariano; Mastrangelo, Annalaura; Horcajada, Juan P; Betbesé, Antoni; Esteban, Andrés; Ordóñez, Jordi; Gea, Joaquín; Cabello, Jesús Ruiz; Pellati, Federica; Lorente, José A; Nin, Nicolás; Rupérez, Francisco J

2017-09-01

Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC-MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC-MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty-three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

PubMed

Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

2016-06-01

Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

PubMed Central

Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure.

PubMed

García-Sevillano, M A; García-Barrera, T; Navarro, F; Montero-Lobato, Z; Gómez-Ariza, J L

2015-04-01

Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies.

Metabolite profiling of fish skin mucus: a novel approach for minimally-invasive environmental exposure monitoring and surveillance.

PubMed

Ekman, D R; Skelton, D M; Davis, J M; Villeneuve, D L; Cavallin, J E; Schroeder, A; Jensen, K M; Ankley, G T; Collette, T W

2015-03-03

The application of 'omics tools to biologically based monitoring and surveillance of aquatic environments shows considerable promise for complementing chemical monitoring in ecological risk assessments. However, few of the current approaches offer the ability to sample ecologically relevant species (e.g., fish) in a way that produces minimal impact on the health of the organism(s) under study. In the current study we employ liquid chromatography tandem mass spectrometry (LC-MS/MS) to assess the potential for skin mucus-based metabolomics for minimally invasive sampling of the fathead minnow (FHM; Pimephales promelas). Using this approach we were able to detect 204 distinct metabolites in the FHM skin mucus metabolome representing a large number of metabolite classes. An analysis of the sex specificity of the skin mucus metabolome showed it to be highly sexually dimorphic with 72 of the detected metabolites showing a statistically significant bias with regard to sex. Finally, in a proof-of-concept fashion we report on the use of skin mucus-based metabolomics to assess exposures in male and female fathead minnows to an environmentally relevant concentration of bisphenol A, a nearly ubiquitous environmental contaminant and an established endocrine active chemical.

Methods for the analysis of organophosphorus flame retardants-Comparison of GC-EI-MS, GC-NCI-MS, LC-ESI-MS/MS, and LC-APCI-MS/MS.

PubMed

Tokumura, Masahiro; Miyake, Yuichi; Wang, Qi; Nakayama, Hayato; Amagai, Takashi; Ogo, Sayaka; Kume, Kazunari; Kobayashi, Takeshi; Takasu, Shinji; Ogawa, Kumiko

2018-04-16

Organophosphorus flame retardants (PFRs) are extensively used as alternatives to banned polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCD). In this study, we analyzed 14 PFRs by means of four mass-spectrometry-based methods: gas chromatography combined with electron-impact mass spectrometry (GC-EI-MS) or negative-chemical-ionization mass spectrometry (GC-NCI-MS) and liquid chromatography combined with tandem mass spectrometry using electrospray ionization (LC-ESI-MS/MS) or atmospheric pressure chemical ionization (LC-APCI-MS/MS). The limits of quantification (LOQs) for LC-ESI-MS/MS and LC-APCI-MS/MS (0.81-970 pg) were 1-2 orders of magnitude lower than the LOQs for GC-EI-MS and GC-NCI-MS (2.3-3900 pg). LC-APCI-MS/MS showed the lowest LOQs (mean = 41 pg; median = 3.4 pg) for all but two of the PFRs targeted in this study. For LC-APCI-MS/MS, the lowest LOQ was observed for tributyl phosphate (TBP) (0.81 pg), and the highest was observed for tris(butoxyethyl) phosphate (TBOEP) (36 pg). The results of this study indicate that LC-APCI-MS/MS is the optimum analytical method for the target PFRs, at least in terms of LOQ.

Metabolic changes in different developmental stages of Vanilla planifolia pods.

PubMed

Palama, Tony Lionel; Khatib, Alfi; Choi, Young Hae; Payet, Bertrand; Fock, Isabelle; Verpoorte, Robert; Kodja, Hippolyte

2009-09-09

The metabolomic analysis of developing Vanilla planifolia green pods (between 3 and 8 months after pollination) was carried out by nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis. Multivariate data analysis of the (1)H NMR spectra, such as principal component analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA), showed a trend of separation of those samples based on the metabolites present in the methanol/water (1:1) extract. Older pods had a higher content of glucovanillin, vanillin, p-hydroxybenzaldehyde glucoside, p-hydroxybenzaldehyde, and sucrose, while younger pods had more bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A), bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-(2-butyl)tartrate (glucoside B), glucose, malic acid, and homocitric acid. A liquid chromatography-mass spectrometry (LC-MS) analysis targeted at phenolic compound content was also performed on the developing pods and confirmed the NMR results. Ratios of aglycones/glucosides were estimated and thus allowed for detection of more minor metabolites in the green vanilla pods. Quantification of compounds based on both LC-MS and NMR analyses showed that free vanillin can reach 24% of the total vanillin content after 8 months of development in the vanilla green pods.

An overview of methods using (13)C for improved compound identification in metabolomics and natural products.

PubMed

Clendinen, Chaevien S; Stupp, Gregory S; Ajredini, Ramadan; Lee-McMullen, Brittany; Beecher, Chris; Edison, Arthur S

2015-01-01

Compound identification is a major bottleneck in metabolomics studies. In nuclear magnetic resonance (NMR) investigations, resonance overlap often hinders unambiguous database matching or de novo compound identification. In liquid chromatography-mass spectrometry (LC-MS), discriminating between biological signals and background artifacts and reliable determination of molecular formulae are not always straightforward. We have designed and implemented several NMR and LC-MS approaches that utilize (13)C, either enriched or at natural abundance, in metabolomics applications. For LC-MS applications, we describe a technique called isotopic ratio outlier analysis (IROA), which utilizes samples that are isotopically labeled with 5% (test) and 95% (control) (13)C. This labeling strategy leads to characteristic isotopic patterns that allow the differentiation of biological signals from artifacts and yield the exact number of carbons, significantly reducing possible molecular formulae. The relative abundance between the test and control samples for every IROA feature can be determined simply by integrating the peaks that arise from the 5 and 95% channels. For NMR applications, we describe two (13)C-based approaches. For samples at natural abundance, we have developed a workflow to obtain (13)C-(13)C and (13)C-(1)H statistical correlations using 1D (13)C and (1)H NMR spectra. For samples that can be isotopically labeled, we describe another NMR approach to obtain direct (13)C-(13)C spectroscopic correlations. These methods both provide extensive information about the carbon framework of compounds in the mixture for either database matching or de novo compound identification. We also discuss strategies in which (13)C NMR can be used to identify unknown compounds from IROA experiments. By combining technologies with the same samples, we can identify important biomarkers and corresponding metabolites of interest.

Forecasting Chronic Diseases Using Data Fusion.

PubMed

Acar, Evrim; Gürdeniz, Gözde; Savorani, Francesco; Hansen, Louise; Olsen, Anja; Tjønneland, Anne; Dragsted, Lars Ove; Bro, Rasmus

2017-07-07

Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC-MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC-MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer.

Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

NASA Astrophysics Data System (ADS)

Huan, Tao; Troyer, Dean A.; Li, Liang

2016-08-01

We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.

Application of an untargeted metabolomics approach for the identification of compounds that may be responsible for observed differential effects in chickens fed an organic and a conventional diet.

PubMed

Ruiz-Aracama, A; Lommen, A; Huber, M; van de Vijver, L; Hoogenboom, R

2012-01-01

The aim of this study was to apply an untargeted NMR and LC-MS-based metabolomics approach to detect potential differences between an organically and a conventionally produced feed, which caused statistically significant differences in growth, in the response to an immunological challenge and in the gene expression profiles in the small intestine of laying hens. A fractionation procedure was set up to create multiple fractions of the feed, which were subsequently analysed by NMR and UPLC-TOF/MS operating in positive mode. Comparison of the profiles revealed that the most apparent differences came from the isoflavones in the soy as well as a compound with a molecular mass of 441.202 (M + 1)⁺, which was identified as N,N'-diferuloylputrescine (DFP) and came from the corn. Whether the observed differences in effects are due to the higher levels of isoflavones and DFP is unclear, as is the fact whether the observed differences are typical for organic or conventional produced corn and soy. However, this study shows that this metabolomics approach is suitable for detecting potential differences between products, even in levels of compounds that would have been overlooked with a more targeted approach. As such, the method is suitable for a more systematic study on differences between conventionally and organically produced food.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sumner, Lloyd W.; Lei, Zhentian; Nikolau, Basil J.

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This study highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR formore » metabolite identifications, and x-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.« less

Untargeted mass spectrometry-based metabolomic profiling of pleural effusions: fatty acids as novel cancer biomarkers for malignant pleural effusions.

PubMed

Lam, Ching-Wan; Law, Chun-Yiu

2014-09-05

Untargeted mass spectrometry-based metabolomic profiling is a powerful analytical method used for broad-spectrum identification and quantification of metabolites in biofluids in human health and disease states. In this study, we exploit metabolomic profiling for cancer biomarker discovery for diagnosis of malignant pleural effusions. We envisage the result will be clinically useful since currently there are no cancer biomarkers that are accurate enough for the diagnosis of malignant pleural effusions. Metabolomes of 32 malignant pleural effusions from lung cancer patients and 18 benign effusions from patients with pulmonary tuberculosis were analyzed using reversed-phase liquid chromatography tandem mass spectrometry (LC-MS/MS) using AB SCIEX TripleTOF 5600. MS spectra were analyzed using XCMS, PeakView, and LipidView. Metabolome-Wide Association Study (MWAS) was performed by Receiver Operating Characteristic Curve Explorer and Tester (ROCCET). Insignificant markers were filtered out using a metabolome-wide significance level (MWSL) with p-value < 2 × 10(-5) for t test. Only compounds in Human Metabolome Database (HMDB) will be used as cancer biomarkers. ROCCET analysis of ESI positive and negative MS spectra revealed free fatty acid (FFA) 18:1 (oleic acid) had the largest area-under-ROC of 0.96 (95% CI = 0.87-1.00) in malignant pleural effusions. Using a ratio of FFA 18:1-to-ceramide (d18:1/16:0), the area-under-ROC was further increased to 0.99 (95% CI = 0.91-1.00) with sensitivity 93.8% and specificity 100.0%. Using untargeted metabolomic profiling, the diagnostic cancer biomarker with the largest area-under-ROC can be determined objectively. This lipogenic phenotype could be explained by overexpression of fatty acid synthase (FASN) in cancer cells. The diagnostic performance of FFA 18:1-to-ceramide (d18:1/16:0) ratio supports its use for diagnosis of malignant pleural effusions.

Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach.

PubMed

Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

2010-02-19

In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg(-1) day(-1) or 250 mg kg(-1) day(-1) for a period of 7 days (n=4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers. Copyright 2009 Elsevier B.V. All rights reserved.

MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

PubMed Central

Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

2014-01-01

Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow. PMID:24266674

Evaluation of peak picking quality in LC-MS metabolomics data.

PubMed

Brodsky, Leonid; Moussaieff, Arieh; Shahaf, Nir; Aharoni, Asaph; Rogachev, Ilana

2010-11-15

The output of LC-MS metabolomics experiments consists of mass-peak intensities identified through a peak-picking/alignment procedure. Besides imperfections in biological samples and instrumentation, data accuracy is highly dependent on the applied algorithms and their parameters. Consequently, quality control (QC) is essential for further data analysis. Here, we present a QC approach that is based on discrepancies between replicate samples. First, the quantile normalization of per-sample log-signal distributions is applied to each group of biologically homogeneous samples. Next, the overall quality of each replicate group is characterized by the Z-transformed correlation coefficients between samples. This general QC allows a tuning of the procedure's parameters which minimizes the inter-replicate discrepancies in the generated output. Subsequently, an in-depth QC measure detects local neighborhoods on a template of aligned chromatograms that are enriched by divergences between intensity profiles of replicate samples. These neighborhoods are determined through a segmentation algorithm. The retention time (RT)-m/z positions of the neighborhoods with local divergences are indicative of either: incorrect alignment of chromatographic features, technical problems in the chromatograms, or to a true biological discrepancy between replicates for particular metabolites. We expect this method to aid in the accurate analysis of metabolomics data and in the development of new peak-picking/alignment procedures.

Data Treatment for LC-MS Untargeted Analysis.

PubMed

Riccadonna, Samantha; Franceschi, Pietro

2018-01-01

Liquid chromatography-mass spectrometry (LC-MS) untargeted experiments require complex chemometrics strategies to extract information from the experimental data. Here we discuss "data preprocessing", the set of procedures performed on the raw data to produce a data matrix which will be the starting point for the subsequent statistical analysis. Data preprocessing is a crucial step on the path to knowledge extraction, which should be carefully controlled and optimized in order to maximize the output of any untargeted metabolomics investigation.

Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach.

PubMed

Yu, Tianwei; Jones, Dean P

2014-10-15

Peak detection is a key step in the preprocessing of untargeted metabolomics data generated from high-resolution liquid chromatography-mass spectrometry (LC/MS). The common practice is to use filters with predetermined parameters to select peaks in the LC/MS profile. This rigid approach can cause suboptimal performance when the choice of peak model and parameters do not suit the data characteristics. Here we present a method that learns directly from various data features of the extracted ion chromatograms (EICs) to differentiate between true peak regions from noise regions in the LC/MS profile. It utilizes the knowledge of known metabolites, as well as robust machine learning approaches. Unlike currently available methods, this new approach does not assume a parametric peak shape model and allows maximum flexibility. We demonstrate the superiority of the new approach using real data. Because matching to known metabolites entails uncertainties and cannot be considered a gold standard, we also developed a probabilistic receiver-operating characteristic (pROC) approach that can incorporate uncertainties. The new peak detection approach is implemented as part of the apLCMS package available at http://web1.sph.emory.edu/apLCMS/ CONTACT: tyu8@emory.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Modern plant metabolomics: Advanced natural product gene discoveries, improved technologies, and future prospects

DOE PAGES

Sumner, Lloyd W.; Lei, Zhentian; Nikolau, Basil J.; ...

2014-10-24

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This study highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR formore » metabolite identifications, and x-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.« less

Variations in gut microbiota and fecal metabolic phenotype associated with depression by 16S rRNA gene sequencing and LC/MS-based metabolomics.

PubMed

Yu, Meng; Jia, Hongmei; Zhou, Chao; Yang, Yong; Zhao, Yang; Yang, Maohua; Zou, Zhongmei

2017-05-10

As a prevalent, life-threatening and highly recurrent psychiatric illness, depression is characterized by a wide range of pathological changes; however, its etiology remains incompletely understood. Accumulating evidence supports that gut microbiota affects not only gastrointestinal physiology but also central nervous system (CNS) function and behavior through the microbiota-gut-brain axis. To assess the impact of gut microbiota on fecal metabolic phenotype in depressive conditions, an integrated approach of 16S rRNA gene sequencing combined with ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS) based metabolomics was performed in chronic variable stress (CVS)-induced depression rat model. Interestingly, depression led to significant gut microbiota changes, at the phylum and genus levels in rats treated with CVS compared to controls. The relative abundances of the bacterial genera Marvinbryantia, Corynebacterium, Psychrobacter, Christensenella, Lactobacillus, Peptostreptococcaceae incertae sedis, Anaerovorax, Clostridiales incertae sedis and Coprococcus were significantly decreased, whereas Candidatus Arthromitus and Oscillibacter were markedly increased in model rats compared with normal controls. Meanwhile, distinct changes in fecal metabolic phenotype of depressive rats were also found, including lower levels of amino acids, and fatty acids, and higher amounts of bile acids, hypoxanthine and stercobilins. Moreover, there were substantial associations of perturbed gut microbiota genera with the altered fecal metabolites, especially compounds involved in the metabolism of tryptophan and bile acids. These results showed that the gut microbiota was altered in association with fecal metabolism in depressive conditions. These findings suggest that the 16S rRNA gene sequencing and LC-MS based metabolomics approach can be further applied to assess pathogenesis of depression. Copyright © 2017 Elsevier B.V. All rights reserved.

Data preprocessing method for liquid chromatography-mass spectrometry based metabolomics.

PubMed

Wei, Xiaoli; Shi, Xue; Kim, Seongho; Zhang, Li; Patrick, Jeffrey S; Binkley, Joe; McClain, Craig; Zhang, Xiang

2012-09-18

A set of data preprocessing algorithms for peak detection and peak list alignment are reported for analysis of liquid chromatography-mass spectrometry (LC-MS)-based metabolomics data. For spectrum deconvolution, peak picking is achieved at the selected ion chromatogram (XIC) level. To estimate and remove the noise in XICs, each XIC is first segmented into several peak groups based on the continuity of scan number, and the noise level is estimated by all the XIC signals, except the regions potentially with presence of metabolite ion peaks. After removing noise, the peaks of molecular ions are detected using both the first and the second derivatives, followed by an efficient exponentially modified Gaussian-based peak deconvolution method for peak fitting. A two-stage alignment algorithm is also developed, where the retention times of all peaks are first transferred into the z-score domain and the peaks are aligned based on the measure of their mixture scores after retention time correction using a partial linear regression. Analysis of a set of spike-in LC-MS data from three groups of samples containing 16 metabolite standards mixed with metabolite extract from mouse livers demonstrates that the developed data preprocessing method performs better than two of the existing popular data analysis packages, MZmine2.6 and XCMS(2), for peak picking, peak list alignment, and quantification.

A Data Pre-processing Method for Liquid Chromatography Mass Spectrometry-based Metabolomics

PubMed Central

Wei, Xiaoli; Shi, Xue; Kim, Seongho; Zhang, Li; Patrick, Jeffrey S.; Binkley, Joe; McClain, Craig; Zhang, Xiang

2012-01-01

A set of data pre-processing algorithms for peak detection and peak list alignment are reported for analysis of LC-MS based metabolomics data. For spectrum deconvolution, peak picking is achieved at selected ion chromatogram (XIC) level. To estimate and remove the noise in XICs, each XIC is first segmented into several peak groups based on the continuity of scan number, and the noise level is estimated by all the XIC signals, except the regions potentially with presence of metabolite ion peaks. After removing noise, the peaks of molecular ions are detected using both the first and the second derivatives, followed by an efficient exponentially modified Gaussian-based peak deconvolution method for peak fitting. A two-stage alignment algorithm is also developed, where the retention times of all peaks are first transferred into z-score domain and the peaks are aligned based on the measure of their mixture scores after retention time correction using a partial linear regression. Analysis of a set of spike-in LC-MS data from three groups of samples containing 16 metabolite standards mixed with metabolite extract from mouse livers, demonstrates that the developed data pre-processing methods performs better than two of the existing popular data analysis packages, MZmine2.6 and XCMS2, for peak picking, peak list alignment and quantification. PMID:22931487

Highly sensitive quantification for human plasma-targeted metabolomics using an amine derivatization reagent.

PubMed

Arashida, Naoko; Nishimoto, Rumi; Harada, Masashi; Shimbo, Kazutaka; Yamada, Naoyuki

2017-02-15

Amino acids and their related metabolites play important roles in various physiological processes and have consequently become biomarkers for diseases. However, accurate quantification methods have only been established for major compounds, such as amino acids and a limited number of target metabolites. We previously reported a highly sensitive high-throughput method for the simultaneous quantification of amines using 3-aminopyridyl-N-succinimidyl carbamate as a derivatization reagent combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Herein, we report the successful development of a practical and accurate LC-MS/MS method to analyze low concentrations of 40 physiological amines in 19 min. Thirty-five of these amines showed good linearity, limits of quantification, accuracy, precision, and recovery characteristics in plasma, with scheduled selected reaction monitoring acquisitions. Plasma samples from 10 healthy volunteers were evaluated using our newly developed method. The results revealed that 27 amines were detected in one of the samples, and that 24 of these compounds could be quantified. Notably, this new method successfully quantified metabolites with high accuracy across three orders of magnitude, with lowest and highest averaged concentrations of 31.7 nM (for spermine) and 18.3 μM (for α-aminobutyric acid), respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Isolating the metabolic pathways involved in the hepatoprotective effect of Muntingia calabura against CCl4-induced liver injury using LC/MS Q-TOF.

PubMed

Rofiee, M S; Yusof, M I M; Abdul Hisam, E E; Bannur, Z; Zakaria, Z A; Somchit, M N; Teh, L K; Salleh, M Z

2015-05-26

Muntingia calabura L. has been used in Southeast Asia and tropical America as antipyretic, antiseptic, analgesic, antispasmodic and liver tonic. This study aims to determine the acute toxicity and the metabolic pathways involved in the hepatoprotective mechanism of M. calabura. CCl4-induced hepatotoxic rat model was developed and a dose dependent effect of M. calabura was conducted. Body weight, food and water consumption were measured every day and rats were sacrificed to collect the serum samples at the end of the 10-days treatment. Liquid chromatography-mass spectrometry quadrapole time of flight (LC/MS-QTOF) combined with principal component analysis (PCA) were used to determine differentially expressed metabolites due to treatment with CCl4 and M. calabura extracts. Metabolomics Pathway Analysis (MetPA) was used for analysis and visualization of pathways involved. Body weight, food and water consumption were significantly decreased and histopathological study revealed steatosis in CCl4-induced rats. PCA score plots show distinct separation in the metabolite profiles of the normal group, CCl4-treated group and extract of M. calabura (MCME) pre-treated groups. Biomarkers network reconstruction using MetPA had identified 2 major pathways which were involved in the protective mechanism of MCME. These include the (i) biosynthesis of the primary bile acid, (ii) metabolism of arachidonic acid. This study has successfully isolated 2 major pathways involved in the hepatoprotecive effect of MCME against CCl4-induced liver injury using the LC/MS Q-TOF metabolomics approach. The involvement of archidonic acid and purine metabolism in hepatoprotection has not been reported previously and may provide new therapeutic targets and/or options for the treatment of liver injury. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics.

PubMed

Domingo-Almenara, Xavier; Brezmes, Jesus; Vinaixa, Maria; Samino, Sara; Ramirez, Noelia; Ramon-Krauel, Marta; Lerin, Carles; Díaz, Marta; Ibáñez, Lourdes; Correig, Xavier; Perera-Lluna, Alexandre; Yanes, Oscar

2016-10-04

Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC/MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-time-of-flight (TOF) MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign, and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-triple quadrupole (QqQ) MS, LC-QqQ, and NMR. eRah is freely available at http://CRAN.R-project.org/package=erah .

A QC approach to the determination of day-to-day reproducibility and robustness of LC-MS methods for global metabolite profiling in metabonomics/metabolomics.

PubMed

Gika, Helen G; Theodoridis, Georgios A; Earll, Mark; Wilson, Ian D

2012-09-01

An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.

Targeted Metabolomic Pathway Analysis and Validation Revealed Glutamatergic Disorder in the Prefrontal Cortex among the Chronic Social Defeat Stress Mice Model of Depression.

PubMed

Wang, Wei; Guo, Hua; Zhang, Shu-Xiao; Li, Juan; Cheng, Ke; Bai, Shun-Jie; Yang, De-Yu; Wang, Hai-Yang; Liang, Zi-Hong; Liao, Li; Sun, Lin; Xie, Peng

2016-10-07

Major depressive disorder (MDD) is a severe psychiatric disease that has critically affected life quality for millions of people. Chronic stress is gradually recognized as a primary pathogenesis risk factor of MDD. Despite the remarkable progress in mechanism research, the pathogenesis mechanism of MDD is still not well understood. Therefore, we conducted a liquid chromatography-tandem mass spectrometry (LC-MS/MS) detection of 25 major metabolites of tryptophanic, GABAergic, and catecholaminergic pathways in the prefontal cortex (PFC) of mice in chronic social defeat stress (CSDS). The depressed mice exhibit significant reduction of glutamate in the GABAergic pathway and an increase of L-DOPA and vanillylmandelic acid in catecholaminergic pathways. The data of real-time-quantitative polymerase chain reaction (RT-qPCR) and Western blotting analysis revealed an altered level of glutamatergic circuitry. The metabolomic and molecular data reveal that the glutamatergic disorder in mice shed lights to reveal a mechanism on depression-like and stress resilient phenotype.

QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

PubMed

Simader, Alexandra Maria; Kluger, Bernhard; Neumann, Nora Katharina Nicole; Bueschl, Christoph; Lemmens, Marc; Lirk, Gerald; Krska, Rudolf; Schuhmacher, Rainer

2015-10-24

Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple quality control sample types as well as experimental samples in one or more measurement sequences.

Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS.

PubMed

Zhang, Yan-Xin; Yang, Xin; Zou, Pan; Du, Peng-Fei; Wang, Jing; Jin, Fen; Jin, Mao-Jun; She, Yong-Xin

2016-05-14

Nonylphenol (NP) was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS) in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS) to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend), and tryptophan (showing a downward trend), were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM)-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG) levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP.

Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

PubMed Central

Zhang, Yan-Xin; Yang, Xin; Zou, Pan; Du, Peng-Fei; Wang, Jing; Jin, Fen; Jin, Mao-Jun; She, Yong-Xin

2016-01-01

Nonylphenol (NP) was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS) in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS) to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend), and tryptophan (showing a downward trend), were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM)-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG) levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP. PMID:27187439

Top-down approach for the direct characterization of low molecular weight heparins using LC-FT-MS.

PubMed

Li, Lingyun; Zhang, Fuming; Zaia, Joseph; Linhardt, Robert J

2012-10-16

Low molecular heparins (LMWHs) are structurally complex, heterogeneous, polydisperse, and highly negatively charged mixtures of polysaccharides. The direct characterization of LMWH is a major challenge for currently available analytical technologies. Electrospray ionization (ESI) liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for the characterization complex biological samples in the fields of proteomics, metabolomics, and glycomics. LC-MS has been applied to the analysis of heparin oligosaccharides, separated by size exclusion, reversed phase ion-pairing chromatography, and chip-based amide hydrophilic interaction chromatography (HILIC). However, there have been limited applications of ESI-LC-MS for the direct characterization of intact LMWHs (top-down analysis) due to their structural complexity, low ionization efficiency, and sulfate loss. Here we present a simple and reliable HILIC-Fourier transform (FT)-ESI-MS platform to characterize and compare two currently marketed LMWH products using the top-down approach requiring no special sample preparation steps. This HILIC system relies on cross-linked diol rather than amide chemistry, affording highly resolved chromatographic separations using a relatively high percentage of acetonitrile in the mobile phase, resulting in stable and high efficiency ionization. Bioinformatics software (GlycReSoft 1.0) was used to automatically assign structures within 5-ppm mass accuracy.

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification.

PubMed

Beirnaert, Charlie; Meysman, Pieter; Vu, Trung Nghia; Hermans, Nina; Apers, Sandra; Pieters, Luc; Covaci, Adrian; Laukens, Kris

2018-03-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

PubMed Central

Pieters, Luc; Covaci, Adrian

2018-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID:29494588

Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

PubMed

Mahieu, Nathaniel G; Patti, Gary J

2017-10-03

When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

Alterations of the Lipid Metabolome in Dairy Cows Experiencing Excessive Lipolysis Early Postpartum

PubMed Central

Humer, Elke; Khol-Parisini, Annabella; Metzler-Zebeli, Barbara U.; Gruber, Leonhard; Zebeli, Qendrim

2016-01-01

A decrease in insulin sensitivity enhances adipose tissue lipolysis helping early lactation cows counteracting their energy deficit. However, excessive lipolysis poses serious health risks for cows, and its underlying mechanisms are not clearly understood. The present study used targeted ESI-LC-MS/MS-based metabolomics and indirect insulin sensitivity measurements to evaluate metabolic alterations in the serum of dairy cows of various parities experiencing variable lipolysis early postpartum. Thirty (12 primiparous and 18 multiparous) cows of Holstein Friesian and Simmental breeds, fed the same diet and kept under the same management conditions, were sampled at d 21 postpartum and classified as low (n = 10), medium (n = 8), and high (n = 12) lipolysis groups, based on serum concentration of nonesterified fatty acids. Overall, excessive lipolysis in the high group came along with impaired estimated insulin sensitivity and characteristic shifts in acylcarnitine, sphingomyelin, phosphatidylcholine and lysophospholipid metabolome profiles compared to the low group. From the detected phosphatidylcholines mainly those with diacyl-residues showed differences among lipolysis groups. Furthermore, more than half of the detected sphingomyelins were increased in cows experiencing high lipomobilization. Additionally, strong differences in serum acylcarnitines were noticed among lipolysis groups. The study suggests an altered serum phospholipidome in dairy cows associated with an increase in certain long-chain sphingomyelins and the progression of disturbed insulin function. In conclusion, the present study revealed 37 key metabolites as part of alterations in the synthesis or breakdown of sphingolipids and phospholipids associated with lowered estimated insulin sensitivity and excessive lipolysis in early-lactating cows. PMID:27383746

Alterations of the Lipid Metabolome in Dairy Cows Experiencing Excessive Lipolysis Early Postpartum.

PubMed

Humer, Elke; Khol-Parisini, Annabella; Metzler-Zebeli, Barbara U; Gruber, Leonhard; Zebeli, Qendrim

2016-01-01

A decrease in insulin sensitivity enhances adipose tissue lipolysis helping early lactation cows counteracting their energy deficit. However, excessive lipolysis poses serious health risks for cows, and its underlying mechanisms are not clearly understood. The present study used targeted ESI-LC-MS/MS-based metabolomics and indirect insulin sensitivity measurements to evaluate metabolic alterations in the serum of dairy cows of various parities experiencing variable lipolysis early postpartum. Thirty (12 primiparous and 18 multiparous) cows of Holstein Friesian and Simmental breeds, fed the same diet and kept under the same management conditions, were sampled at d 21 postpartum and classified as low (n = 10), medium (n = 8), and high (n = 12) lipolysis groups, based on serum concentration of nonesterified fatty acids. Overall, excessive lipolysis in the high group came along with impaired estimated insulin sensitivity and characteristic shifts in acylcarnitine, sphingomyelin, phosphatidylcholine and lysophospholipid metabolome profiles compared to the low group. From the detected phosphatidylcholines mainly those with diacyl-residues showed differences among lipolysis groups. Furthermore, more than half of the detected sphingomyelins were increased in cows experiencing high lipomobilization. Additionally, strong differences in serum acylcarnitines were noticed among lipolysis groups. The study suggests an altered serum phospholipidome in dairy cows associated with an increase in certain long-chain sphingomyelins and the progression of disturbed insulin function. In conclusion, the present study revealed 37 key metabolites as part of alterations in the synthesis or breakdown of sphingolipids and phospholipids associated with lowered estimated insulin sensitivity and excessive lipolysis in early-lactating cows.

Metabolomic Insight into Lipid and Protein Profile in Diabetes Using Mass Spectrometry.

PubMed

Bukowiecka-Matusiak, Malgorzata; Chmielewska-Kassassir, Malgorzata; Szczesna, Dorota; Wozniak, Lucyna A

2016-01-01

In recent years, metabolomics has become a necessary tool for understanding the impact of external and pathological factors on the operation of biological systems. The first reports of metabolomics date back to the 1970s, however, the area only began to develop dynamically at the beginning of this century and has proved effective only during the present decade. The five primary tools used in this form of analysis are NMR spectrometry, HPLC, TLC-UV, GC-MS and LC-MS/MS, with MS as the most universal approach, particularly when used together with chromatographic separation and NMR. Diabetes mellitus type 2 (T2DM) is a rapidly growing problem with global consequences. The metabolomic approach has been extensively applied to examining T2DM, insulin resistance and obesity, not only to assess the development of the disease, but also to discover its potential biomarkers. The presented review summarizes current studies on lipidomic and proteomic profiles in the context of different types of diabetes mellitus disease (T1DM, T2DM and GDM), as determined by chromatography-coupled mass spectrometry.

Metabolomic Fingerprinting in the Comprehensive Study of Liver Changes Associated with Onion Supplementation in Hypercholesterolemic Wistar Rats

PubMed Central

González-Peña, Diana; Dudzik, Danuta; García, Antonia; de Ancos, Begoña; Barbas, Coral; Sánchez-Moreno, Concepción

2017-01-01

The consumption of functional ingredients has been suggested to be a complementary tool for the prevention and management of liver disease. In this light, processed onion can be considered as a source of multiple bioactive compounds with hepatoprotective properties. The liver fingerprint of male Wistar rats (n = 24) fed with three experimental diets (control (C), high-cholesterol (HC), and high-cholesterol enriched with onion (HCO) diets) was obtained through a non-targeted, multiplatform metabolomics approach to produce broad metabolite coverage. LC-MS, CE-MS and GC-MS results were subjected to univariate and multivariate analyses, providing a list of significant metabolites. All data were merged in order to figure out the most relevant metabolites that were modified by the onion ingredient. Several relevant metabolic changes and related metabolic pathways were found to be impacted by both HC and HCO diet. The model highlighted several metabolites (such as hydroxybutyryl carnitine and palmitoyl carnitine) modified by the HCO diet. These findings could suggest potential impairments in the energy−lipid metabolism, perturbations in the tricarboxylic acid cycle (TCA) cycle and β-oxidation modulated by the onion supplementation in the core of hepatic dysfunction. Metabolomics shows to be a valuable tool to evaluate the effects of complementary dietetic approaches directed to hepatic damage amelioration or non-alcoholic fatty liver disease (NAFLD) prevention. PMID:28134852

The Metabolomic Profile of Umbilical Cord Blood in Neonatal Hypoxic Ischaemic Encephalopathy

PubMed Central

Walsh, Brian H.; Broadhurst, David I.; Mandal, Rupasri; Wishart, David S.; Boylan, Geraldine B.; Kenny, Louise C.; Murray, Deirdre M.

2012-01-01

Background Hypoxic ischaemic encephalopathy (HIE) in newborns can cause significant long-term neurological disability. The insult is a complex injury characterised by energy failure and disruption of cellular homeostasis, leading to mitochondrial damage. The importance of individual metabolic pathways, and their interaction in the disease process is not fully understood. The aim of this study was to describe and quantify the metabolomic profile of umbilical cord blood samples in a carefully defined population of full-term infants with HIE. Methods and Findings The injury severity was defined using both the modified Sarnat score and continuous multichannel electroencephalogram. Using these classification systems, our population was divided into those with confirmed HIE (n = 31), asphyxiated infants without encephalopathy (n = 40) and matched controls (n = 71). All had umbilical cord blood drawn and biobanked at −80°C within 3 hours of delivery. A combined direct injection and LC-MS/MS assay (AbsolutIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria) was used for the metabolomic analyses of the samples. Targeted metabolomic analysis showed a significant alteration between study groups in 29 metabolites from 3 distinct classes (Amino Acids, Acylcarnitines, and Glycerophospholipids). 9 of these metabolites were only significantly altered between neonates with Hypoxic ischaemic encephalopathy and matched controls, while 14 were significantly altered in both study groups. Multivariate Discriminant Analysis models developed showed clear multifactorial metabolite associations with both asphyxia and HIE. A logistic regression model using 5 metabolites clearly delineates severity of asphyxia and classifies HIE infants with AUC = 0.92. These data describe wide-spread disruption to not only energy pathways, but also nitrogen and lipid metabolism in both asphyxia and HIE. Conclusion This study shows that a multi-platform targeted approach to metabolomic analyses using accurately phenotyped and meticulously biobanked samples provides insight into the pathogenesis of perinatal asphyxia. It highlights the potential for metabolomic technology to develop a diagnostic test for HIE. PMID:23227182

A Metabolomic Approach Applied to a Liquid Chromatography Coupled to High-Resolution Tandem Mass Spectrometry Method (HPLC-ESI-HRMS/MS): Towards the Comprehensive Evaluation of the Chemical Composition of Cannabis Medicinal Extracts.

PubMed

Citti, Cinzia; Battisti, Umberto Maria; Braghiroli, Daniela; Ciccarella, Giuseppe; Schmid, Martin; Vandelli, Maria Angela; Cannazza, Giuseppe

2018-03-01

Cannabis sativa L. is a powerful medicinal plant and its use has recently increased for the treatment of several pathologies. Nonetheless, side effects, like dizziness and hallucinations, and long-term effects concerning memory and cognition, can occur. Most alarming is the lack of a standardised procedure to extract medicinal cannabis. Indeed, each galenical preparation has an unknown chemical composition in terms of cannabinoids and other active principles that depends on the extraction procedure. This study aims to highlight the main differences in the chemical composition of Bediol® extracts when the extraction is carried out with either ethyl alcohol or olive oil for various times (0, 60, 120 and 180 min for ethyl alcohol, and 0, 60, 90 and 120 min for olive oil). Cannabis medicinal extracts (CMEs) were analysed by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) using an untargeted metabolomics approach. The data sets were processed by unsupervised multivariate analysis. Our results suggested that the main difference lies in the ratio of acid to decarboxylated cannabinoids, which dramatically influences the pharmacological activity of CMEs. Minor cannabinoids, alkaloids, and amino acids contributing to this difference are also discussed. The main cannabinoids were quantified in each extract applying a recently validated LC-MS and LC-UV method. Notwithstanding the use of a standardised starting plant material, great changes are caused by different extraction procedures. The metabolomics approach is a useful tool for the evaluation of the chemical composition of cannabis extracts. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Told through the wine: A liquid chromatography-mass spectrometry interplatform comparison reveals the influence of the global approach on the final annotated metabolites in non-targeted metabolomics.

PubMed

Díaz, Ramon; Gallart-Ayala, Hector; Sancho, Juan V; Nuñez, Oscar; Zamora, Tatiana; Martins, Claudia P B; Hernández, Félix; Hernández-Cassou, Santiago; Saurina, Javier; Checa, Antonio

2016-02-12

This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomic Analysis of the Secretome of Human Embryonic Stem Cells Following Methyl Parathion and Methyl Paraoxon Exposure. Phase 3. LC-MS-MS Structural Confirmation

DTIC Science & Technology

2014-01-01

attention deficit - hyperactivity disorder ( ADHD ) in their offspring. The...17 ACRONYMS AND ABBREVIATIONS ADHD attention deficit - hyperactivity disorder ADMA asymmetric dimethylarginine APG Aberdeen Proving...Wright, R.O.; Weisskopf, M.G. Attention - Deficit / Hyperactivity Disorder and Urinary Metabololites or Organophosphate Pesticides. Pediatrics

Navigating freely-available software tools for metabolomics analysis.

PubMed

Spicer, Rachel; Salek, Reza M; Moreno, Pablo; Cañueto, Daniel; Steinbeck, Christoph

2017-01-01

The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools. To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics. The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for. A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary. This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.

Secondary metabolite profiling of Curcuma species grown at different locations using GC/TOF and UPLC/Q-TOF MS.

PubMed

Lee, Jueun; Jung, Youngae; Shin, Jeoung-Hwa; Kim, Ho Kyoung; Moon, Byeong Cheol; Ryu, Do Hyun; Hwang, Geum-Sook

2014-07-04

Curcuma, a genus of rhizomatous herbaceous species, has been used as a spice, traditional medicine, and natural dye. In this study, the metabolite profile of Curcuma extracts was determined using gas chromatography-time of flight mass spectrometry (GC/TOF MS) and ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) to characterize differences between Curcuma aromatica and Curcuma longa grown on the Jeju-do or Jin-do islands, South Korea. Previous studies have performed primary metabolite profiling of Curcuma species grown in different regions using NMR-based metabolomics. This study focused on profiling of secondary metabolites from the hexane extract of Curcuma species. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) plots showed significant differences between the C. aromatica and C. longa metabolite profiles, whereas geographical location had little effect. A t-test was performed to identify statistically significant metabolites, such as terpenoids. Additionally, targeted profiling using UPLC/Q-TOF MS showed that the concentration of curcuminoids differed depending on the plant origin. Based on these results, a combination of GC- and LC-MS allowed us to analyze curcuminoids and terpenoids, the typical bioactive compounds of Curcuma, which can be used to discriminate Curcuma samples according to species or geographical origin.

Proteomic and Metabolomic Analyses Reveal Contrasting Anti-Inflammatory Effects of an Extract of Mucor Racemosus Secondary Metabolites Compared to Dexamethasone.

PubMed

Meier, Samuel M; Muqaku, Besnik; Ullmann, Ronald; Bileck, Andrea; Kreutz, Dominique; Mader, Johanna C; Knasmüller, Siegfried; Gerner, Christopher

2015-01-01

Classical drug assays are often confined to single molecules and targeting single pathways. However, it is also desirable to investigate the effects of complex mixtures on complex systems such as living cells including the natural multitude of signalling pathways. Evidence based on herbal medicine has motivated us to investigate potential beneficial health effects of Mucor racemosus (M rac) extracts. Secondary metabolites of M rac were collected using a good-manufacturing process (GMP) approved production line and a validated manufacturing process, in order to obtain a stable product termed SyCircue (National Drug Code USA: 10424-102). Toxicological studies confirmed that this product does not contain mycotoxins and is non-genotoxic. Potential effects on inflammatory processes were investigated by treating stimulated cells with M rac extracts and the effects were compared to the standard anti-inflammatory drug dexamethasone on the levels of the proteome and metabolome. Using 2D-PAGE, slight anti-inflammatory effects were observed in primary white blood mononuclear cells, which were more pronounced in primary human umbilical vein endothelial cells (HUVECs). Proteome profiling based on nLC-MS/MS analysis of tryptic digests revealed inhibitory effects of M rac extracts on pro-inflammatory cytoplasmic mediators and secreted cytokines and chemokines in these endothelial cells. This finding was confirmed using targeted proteomics, here treatment of stimulated cells with M rac extracts down-regulated the secretion of IL-6, IL-8, CXCL5 and GROA significantly. Finally, the modulating effects of M rac on HUVECs were also confirmed on the level of the metabolome. Several metabolites displayed significant concentration changes upon treatment of inflammatory activated HUVECs with the M rac extract, including spermine and lysophosphatidylcholine acyl C18:0 and sphingomyelin C26:1, while the bulk of measured metabolites remained unaffected. Interestingly, the effects of M rac treatment on lipids were orthogonal to the effect of dexamethasone underlining differences in the overall mode of action.

Metabolomic and proteomic analysis of D-lactate-producing Lactobacillus delbrueckii under various fermentation conditions.

PubMed

Liang, Shaoxiong; Gao, Dacheng; Liu, Huanhuan; Wang, Cheng; Wen, Jianping

2018-05-28

As an important feedstock monomer for the production of biodegradable stereo-complex poly-lactic acid polymer, D-lactate has attracted much attention. To improve D-lactate production by microorganisms such as Lactobacillus delbrueckii, various fermentation conditions were performed, such as the employment of anaerobic fermentation, the utilization of more suitable neutralizing agents, and exploitation of alternative nitrogen sources. The highest D-lactate titer could reach 133 g/L under the optimally combined fermentation condition, increased by 70.5% compared with the control. To decipher the potential mechanisms of D-lactate overproduction, the time-series response of intracellular metabolism to different fermentation conditions was investigated by GC-MS and LC-MS/MS-based metabolomic analysis. Then the metabolomic datasets were subjected to weighted correlation network analysis (WGCNA), and nine distinct metabolic modules and eight hub metabolites were identified to be specifically associated with D-lactate production. Moreover, a quantitative iTRAQ-LC-MS/MS proteomic approach was employed to further analyze the change of intracellular metabolism under the combined fermentation condition, identifying 97 up-regulated and 42 down-regulated proteins compared with the control. The in-depth analysis elucidated how the key factors exerted influence on D-lactate biosynthesis. The results revealed that glycolysis and pentose phosphate pathways, transport of glucose, amino acids and peptides, amino acid metabolism, peptide hydrolysis, synthesis of nucleotides and proteins, and cell division were all strengthened, while ATP consumption for exporting proton, cell damage, metabolic burden caused by stress response, and bypass of pyruvate were decreased under the combined condition. These might be the main reasons for significantly improved D-lactate production. These findings provide the first omics view of cell growth and D-lactate overproduction in L. delbrueckii, which can be a theoretical basis for further improving the production of D-lactate.

Analysis of phytochemical variations in dioecious Tinospora cordifolia stems using HPLC/QTOF MS/MS and UPLC/QqQLIT -MS/MS.

PubMed

Bajpai, Vikas; Singh, Awantika; Chandra, Preeti; Negi, M P S; Kumar, Nikhil; Kumar, Brijesh

2016-01-01

The stem of dioecious Tinospora cordifolia (Menispermaceae) is a commonly used traditional Ayurvedic medicine in India having several therapeutic properties. To develop and validate LC-MS methods for the identification and simultaneous quantitation of various secondary metabolites and to study metabolomic variations in the stem of male and female plants. Ethanolic extract of stems were analysed by HPLC/ESI-QTOF-MS/MS for rapid screening of bioactive phytochemicals. High resolution MS and MS/MS in positive ESI mode were used for structural investigation of secondary metabolites. An UPLC/ESI-QqQ(LIT) -MS/MS method in MRM mode was developed and validated for the simultaneous quantitation of five bioactive alkaloids. Identification and characterisation of 36 metabolites including alkaloids, sesquiterpenes and phytoecdysteroids were performed using LC-MS and MS/MS techniques. The bioactive alkaloids such as jatrorrhizine, magnoflorine, isocorydine, palmatine and tetrahydropalmatine were successfully quantified in male and female plants. The mean abundances of magnoflorine jatrorrhizine, and oblongine were significantly (P < 0.05) higher in male plants while mean abundances of tetrahydropalmatine, norcoclaurine, and reticuline were significantly (P < 0.05) higher in female plants. Phytochemicals in the stem of male and female Tinospora cordifolia showed significant qualitative and quantitative variations. LC-MS and MS/MS methods can be used to differentiate between male and female plants based on their chemical profiles and quantities of the marker bioactive alkaloids. This chemical composition difference was also evident during vegetative stage when there were no male and female flowers. Copyright © 2015 John Wiley & Sons, Ltd.

Discovery of A-type procyanidin dimers in yellow raspberries by untargeted metabolomics and correlation based data analysis.

PubMed

Carvalho, Elisabete; Franceschi, Pietro; Feller, Antje; Herrera, Lorena; Palmieri, Luisa; Arapitsas, Panagiotis; Riccadonna, Samantha; Martens, Stefan

2016-01-01

Raspberries are becoming increasingly popular due to their reported health beneficial properties. Despite the presence of only trace amounts of anthocyanins, yellow varieties seems to show similar or better effects in comparison to conventional raspberries. The aim of this work is to characterize the metabolic differences between red and yellow berries, focussing on the compounds showing a higher concentration in yellow varieties. The metabolomic profile of 13 red and 12 yellow raspberries (of different varieties, locations and collection dates) was determined by UPLC-TOF-MS. A novel approach based on Pearson correlation on the extracted ion chromatograms was implemented to extract the pseudospectra of the most relevant biomarkers from high energy LC-MS runs. The raw data will be made publicly available on MetaboLights (MTBLS333). Among the metabolites showing higher concentration in yellow raspberries it was possible to identify a series of compounds showing a pseudospectrum similar to that of A-type procyanidin polymers. The annotation of this group of compounds was confirmed by specific MS/MS experiments and performing standard injections. In berries lacking anthocyanins the polyphenol metabolism might be shifted to the formation of a novel class of A-type procyanidin polymers.

Metabolomic Profiling in Individuals with a Failing Kidney Allograft.

PubMed

Bassi, Roberto; Niewczas, Monika A; Biancone, Luigi; Bussolino, Stefania; Merugumala, Sai; Tezza, Sara; D'Addio, Francesca; Ben Nasr, Moufida; Valderrama-Vasquez, Alessandro; Usuelli, Vera; De Zan, Valentina; El Essawy, Basset; Venturini, Massimo; Secchi, Antonio; De Cobelli, Francesco; Lin, Alexander; Chandraker, Anil; Fiorina, Paolo

2017-01-01

Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease. To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine) and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft) 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3). Ten healthy non-allograft individuals were chosen as controls. LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA) and short-chain acylcarnitines (C4 and C12), (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively). The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively). In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05) in individuals with lower GFR levels. We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function.

The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

PubMed

Carroll, Adam J; Badger, Murray R; Harvey Millar, A

2010-07-14

Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.

Simultaneous testing of multiclass organic contaminants in food and environment by liquid chromatography/dielectric barrier discharge ionization-mass spectrometry.

PubMed

Gilbert-López, Bienvenida; García-Reyes, Juan F; Meyer, Cordula; Michels, Antje; Franzke, Joachim; Molina-Díaz, Antonio; Hayen, Heiko

2012-11-21

A Dielectric Barrier Discharge Ionization (DBDI) LC/MS interface is based on the use of a low-temperature helium plasma, which features the possibility of simultaneous ionization of species with a wide variety of physicochemical properties. In this work, the performance of LC/DBDI-MS for trace analysis of highly relevant species in food and environment has been examined. Over 75 relevant species including multiclass priority organic contaminants and residues such as pesticides, polycyclic aromatic hydrocarbons, organochlorine species, pharmaceuticals, personal care products, and drugs of abuse were tested. LC/DBDI-MS performance for this application was assessed and compared with standard LC/MS sources (electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI)). The used benchtop Orbitrap mass spectrometer features a 10 Hz polarity switching mode, so that both positive and negative ion mode acquisitions are possible with acquisition cycles matching the requirements of fast liquid chromatography. Both polar and nonpolar species (including those typically analyzed by GC/electron ionization-MS) can be tested in a single run using polarity switching mode. The methodology was found to be effective in detecting a wide array of organic compounds at concentration levels in the low ng L(-1) to μg kg(-1) range in wastewater and food matrices, respectively. The linearity was evaluated in an olive oil extract, obtaining good correlation coefficients in the studied range. Additionally, minor matrix effects (≤15% of signal suppression or enhancement) were observed for most of the studied analytes in this complex fatty matrix. The results obtained were compared with data from both ESI and APCI sources, obtaining a merged coverage between ESI and APCI in terms of analyte ionization and higher overall sensitivity for the proposed ion source based on the DBD principle. The use of this approach further extends the coverage of current LC/MS methods towards an even larger variety of chemical species including both polar and nonpolar (non-ESI amenable) species and may find several applications in fields such as food and environment testing or metabolomics where GC/MS and LC/MS are combined to cover as many different species as possible.

Time Course Exo-Metabolomic Profiling in the Green Marine Macroalga Ulva (Chlorophyta) for Identification of Growth Phase-Dependent Biomarkers

PubMed Central

Alsufyani, Taghreed; Weiss, Anne; Wichard, Thomas

2017-01-01

The marine green macroalga Ulva (Chlorophyta) lives in a mutualistic symbiosis with bacteria that influence growth, development, and morphogenesis. We surveyed changes in Ulva’s chemosphere, which was defined as a space where organisms interact with each other via compounds, such as infochemicals, nutrients, morphogens, and defense compounds. Thereby, Ulva mutabilis cooperates with bacteria, in particular, Roseovarius sp. strain MS2 and Maribacter sp. strain MS6 (formerly identified as Roseobacter sp. strain MS2 and Cytophaga sp. strain MS6). Without this accompanying microbial flora, U. mutabilis forms only callus-like colonies. However, upon addition of the two bacteria species, in effect forming a tripartite community, morphogenesis can be completely restored. Under this strictly standardized condition, bioactive and eco-physiologically-relevant marine natural products can be discovered. Solid phase extracted waterborne metabolites were analyzed using a metabolomics platform, facilitating gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) analysis, combined with the necessary acquisition of biological metadata. Multivariate statistics of the GC-MS and LC-MS data revealed strong differences between Ulva’s growth phases, as well as between the axenic Ulva cultures and the tripartite community. Waterborne biomarkers, including glycerol, were identified as potential indicators for algal carbon source and bacterial-algal interactions. Furthermore, it was demonstrated that U. mutabilis releases glycerol that can be utilized for growth by Roseovarius sp. MS2. PMID:28075408

High-speed homogenization coupled with microwave-assisted extraction followed by liquid chromatography-tandem mass spectrometry for the direct determination of alkaloids and flavonoids in fresh Isatis tinctoria L. hairy root cultures.

PubMed

Jiao, Jiao; Gai, Qing-Yan; Zhang, Lin; Wang, Wei; Luo, Meng; Zu, Yuan-Gang; Fu, Yu-Jie

2015-06-01

A new, simple and efficient analysis method for fresh plant in vitro cultures-namely, high-speed homogenization coupled with microwave-assisted extraction (HSH-MAE) followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-was developed for simultaneous determination of six alkaloids and eight flavonoids in Isatis tinctoria hairy root cultures (ITHRCs). Compared with traditional methods, the proposed HSH-MAE offers the advantages of easy manipulation, higher efficiency, energy saving, and reduced waste. Cytohistological studies were conducted to clarify the mechanism of HSH-MAE at cellular/tissue levels. Moreover, the established LC-MS/MS method showed excellent linearity, precision, repeatability, and reproducibility. The HSH-MAE-LC-MS/MS method was also successfully applied for screening high-productivity ITHRCs. Overall, this study opened up a new avenue for the direct determination of secondary metabolic profiles from fresh plant in vitro cultures, which is valuable for improving quality control of plant cell/organ cultures and sheds light on the metabolomic analysis of biological samples. Graphical Abstract HSH-MAE-LC-MS/MS opened up a new avenue for the direct determination of alkaloids and flavonoids in fresh Isatis tinctoria hairy root cultures.

Chemical Assignment of Structural Isomers of Sulfur-Containing Metabolites in Garlic by Liquid Chromatography-Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry.

PubMed

Nakabayashi, Ryo; Sawada, Yuji; Aoyagi, Morihiro; Yamada, Yutaka; Hirai, Masami Yokota; Sakurai, Tetsuya; Kamoi, Takahiro; Rowan, Daryl D; Saito, Kazuki

2016-02-01

The chemical assignment of metabolites is crucial to understanding the relation between food composition and biological activity. This study was designed to detect and chemically assign sulfur-containing metabolites by using LC-Fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) in Allium plants. Ultrahigh resolution (>250,000 full width at half-maximum) and mass accuracy (<1 mDa) by FTICR-MS allowed us to distinguish ions containing sulfur isotopes ((32)S and (34)S). Putative 69 S-containing monoisotopic ions (S-ions) were extracted from the metabolome data of onion (Allium cepa), green onion (Allium fistulosum), and garlic (Allium sativum) on the basis of theoretical mass differences between (32)S-ions and their (34)S-substituted counterparts and on the natural abundance of (34)S. Eight S-ions were chemically assigned by using the reference data according to the guidelines of the Metabolomics Standards Initiative. Three ions detected in garlic were assigned as derived from the isomers γ-glutamyl-S-1-propenylcysteine and γ-glutamyl-S-2-propenylcysteine and as S-2-propenylmercaptoglutathione on the basis of differences in key product ions identified in reference tandem MS spectra. The ability to discriminate between such geometric isomers will be extremely useful for the chemical assignment of unknown metabolites in MS-based metabolomics. © 2016 American Society for Nutrition.

SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

PubMed

Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

2018-03-20

The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

An emerging strategy for evaluating the grades of Keemun black tea by combinatory liquid chromatography-Orbitrap mass spectrometry-based untargeted metabolomics and inhibition effects on α-glucosidase and α-amylase.

PubMed

Guo, Xuemei; Long, Piaopiao; Meng, Qilu; Ho, Chi-Tang; Zhang, Liang

2018-04-25

Quantitative analysis and untargeted liquid chromatography mass spectrum (LC-MS) based metabolomics of different grades of Keemun black tea (KBT) were conducted. Quantitative analysis did not show tight correlation between tea grades and contents of polyphenols, but untargeted metabolomics analysis revealed that high-grades KBT were distinguished from the low-grades. S-plot and Variable Importance (VIP) analysis gave 28 marker compounds responsible for the discrimination of different grades of KBT. The inhibitory effects of KBT on α-amylase and α-glucosidase were positively correlated to tea grades, and the correlation coefficient between each marker compound and inhibitory rate were calculated. Thirteen compounds were positively related to the anti-glycemic activity, and theasinensin A, afzelechin gallate and kaempferol-glucoside were confirmed as grade-related bioactive marker compounds by chemical and bioassay in effective fractions. This study suggested that combinatory metabolomics and bioactivities assay provided a new strategy for the classification of tea grades. Copyright © 2017 Elsevier Ltd. All rights reserved.

A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma.

PubMed

Jones, Drew R; Wu, Zhiping; Chauhan, Dharminder; Anderson, Kenneth C; Peng, Junmin

2014-04-01

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.

PubMed

Gil de la Fuente, Alberto; Grace Armitage, Emily; Otero, Abraham; Barbas, Coral; Godzien, Joanna

2017-09-01

Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Liver metabolomics study reveals protective function of Phyllanthus urinaria against CCl4-induced liver injury.

PubMed

Guo, Qing; Zhang, Qian-Qian; Chen, Jia-Qing; Zhang, Wei; Qiu, Hong-Cong; Zhang, Zun-Jian; Liu, Bu-Ming; Xu, Feng-Guo

2017-07-01

Phyllanthus Urinaria L. (PUL) is a traditional Chinese medicine used to treat hepatic and renal disorders. However, the mechanism of its hepatoprotective action is not fully understood. In the present study, blood biochemical indexes and liver histopathological changes were used to estimate the extent of hepatic injury. GC/MS and LC/MS-based untargeted metabolomics were used in combination to characterize the potential biomarkers associated with the protective activity of PUL against CCl 4 -induced liver injury in rats. PUL treatment could reverse the increase in ALT, AST and ALP induced by CCl 4 and attenuate the pathological changes in rat liver. Significant changes in liver metabolic profiling were observed in PUL-treated group compared with liver injury model group. Seventeen biomarkers related to the hepatoprotective effects of PUL against CCl 4 -induced liver injury were screened out using nonparametric test and Pearson's correlation analysis (OPLS-DA). The results suggested that the potential hepatoprotective effects of PUL in attenuating CCl 4 -induced hepatotoxicity could be partially attributed to regulating L-carnitine, taurocholic acid, and amino acids metabolism, which may become promising targets for treatment of liver toxicity. In conclusion, this study provides new insights into the mechanism of the hepatoprotection of Phyllanthus Urinaria. Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kyle, Jennifer E.; Crowell, Kevin L.; Casey, Cameron P.

2017-01-31

We introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species.

Metabolomic Profiling in Individuals with a Failing Kidney Allograft

PubMed Central

Biancone, Luigi; Bussolino, Stefania; Merugumala, Sai; Tezza, Sara; D’Addio, Francesca; Ben Nasr, Moufida; Valderrama-Vasquez, Alessandro; Usuelli, Vera; De Zan, Valentina; El Essawy, Basset; Venturini, Massimo; Secchi, Antonio; De Cobelli, Francesco; Lin, Alexander; Chandraker, Anil; Fiorina, Paolo

2017-01-01

Background Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease. Methods To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine) and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft) 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3). Ten healthy non-allograft individuals were chosen as controls. Results LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA) and short-chain acylcarnitines (C4 and C12), (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively). The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively). In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05) in individuals with lower GFR levels. Conclusions We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function. PMID:28052095

Reduced levels of hydroxylated, polyunsaturated ultra long-chain fatty acids in the serum of colorectal cancer patients: implications for early screening and detection

PubMed Central

2010-01-01

Background There are currently no accurate serum markers for detecting early risk of colorectal cancer (CRC). We therefore developed a non-targeted metabolomics technology to analyse the serum of pre-treatment CRC patients in order to discover putative metabolic markers associated with CRC. Using tandem-mass spectrometry (MS/MS) high throughput MS technology we evaluated the utility of selected markers and this technology for discriminating between CRC and healthy subjects. Methods Biomarker discovery was performed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). Comprehensive metabolic profiles of CRC patients and controls from three independent populations from different continents (USA and Japan; total n = 222) were obtained and the best inter-study biomarkers determined. The structural characterization of these and related markers was performed using liquid chromatography (LC) MS/MS and nuclear magnetic resonance technologies. Clinical utility evaluations were performed using a targeted high-throughput triple-quadrupole multiple reaction monitoring (TQ-MRM) method for three biomarkers in two further independent populations from the USA and Japan (total n = 220). Results Comprehensive metabolomic analyses revealed significantly reduced levels of 28-36 carbon-containing hydroxylated polyunsaturated ultra long-chain fatty-acids in all three independent cohorts of CRC patient samples relative to controls. Structure elucidation studies on the C28 molecules revealed two families harbouring specifically two or three hydroxyl substitutions and varying degrees of unsaturation. The TQ-MRM method successfully validated the FTICR-MS results in two further independent studies. In total, biomarkers in five independent populations across two continental regions were evaluated (three populations by FTICR-MS and two by TQ-MRM). The resultant receiver-operator characteristic curve AUCs ranged from 0.85 to 0.98 (average = 0.91 ± 0.04). Conclusions A novel comprehensive metabolomics technology was used to identify a systemic metabolic dysregulation comprising previously unknown hydroxylated polyunsaturated ultra-long chain fatty acid metabolites in CRC patients. These metabolites are easily measurable in serum and a decrease in their concentration appears to be highly sensitive and specific for the presence of CRC, regardless of ethnic or geographic background. The measurement of these metabolites may represent an additional tool for the early detection and screening of CRC. PMID:20156336

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

PubMed

Hoffman, Melissa A; Fang, Bin; Haura, Eric B; Rix, Uwe; Koomen, John M

2018-01-05

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

Profiling intact steroid sulfates and unconjugated steroids in biological fluids by liquid chromatography-tandem mass spectrometry (LC-MS-MS).

PubMed

Galuska, Christina E; Hartmann, Michaela F; Sánchez-Guijo, Alberto; Bakhaus, Katharina; Geyer, Joachim; Schuler, Gerhard; Zimmer, Klaus-Peter; Wudy, Stefan A

2013-07-07

Within the combined DFG research project "Sulfated Steroids in Reproduction" an analytical method was needed for determining sulfated and unconjugated steroids with highest specificity out of different biological matrices such as aqueous solution, cell lysate and serum. With regard to this analytical challenge, LC-MS-MS presents the technique of choice because it permits (1) analysis of the intact steroid conjugate, (2) allows for simultaneous determination of multiple analytes (profiling, targeted metabolomics approach) and (3) is independent of phenomena such as cross-reactivity. Sample work up consisted of incubation of sample with internal standards (deuterium labeled steroids) followed by solid phase extraction. Only serum samples required a protein precipitation step prior to solid phase extraction. The extract was divided in two parts: six steroid sulfates (E1S, E2S, AS, 16-OH-DHEAS, PREGS, DHEAS) were analyzed by C18aQ-ESI-MS-MS in negative ion mode and eleven unconjugated steroids (E3, 16-OH-DHEA, E1, E2, (4)A, DHEA, T, 17-OH-PREG, Prog, An, PREG) were analyzed by C18-APCI-MS-MS in positive ion mode. For steroid sulfates, we found high sensitivities with LoQ values ranging from 0.08 to 1 ng mL(-1). Unconjugated steroids showed LoQ values between 0.5 and 10 ng mL(-1). Calibration plots showed excellent linearity. Mean intra- and inter-assay CVs were 2.4% for steroid sulfates and 6.4% for unconjugated steroids. Accuracy - determined in a two-level spike experiment - showed mean relative errors of 5.9% for steroid sulfates and 6.1% for unconjugated steroids. In summary, we describe a novel LC-MS-MS procedure capable of profiling six steroid sulfates and eleven unconjugated steroids from various biological matrices.

Validation approach for a fast and simple targeted screening method for 75 antibiotics in meat and aquaculture products using LC-MS/MS.

PubMed

Dubreil, Estelle; Gautier, Sophie; Fourmond, Marie-Pierre; Bessiral, Mélaine; Gaugain, Murielle; Verdon, Eric; Pessel, Dominique

2017-04-01

An approach is described to validate a fast and simple targeted screening method for antibiotic analysis in meat and aquaculture products by LC-MS/MS. The strategy of validation was applied for a panel of 75 antibiotics belonging to different families, i.e., penicillins, cephalosporins, sulfonamides, macrolides, quinolones and phenicols. The samples were extracted once with acetonitrile, concentrated by evaporation and injected into the LC-MS/MS system. The approach chosen for the validation was based on the Community Reference Laboratory (CRL) guidelines for the validation of screening qualitative methods. The aim of the validation was to prove sufficient sensitivity of the method to detect all the targeted antibiotics at the level of interest, generally the maximum residue limit (MRL). A robustness study was also performed to test the influence of different factors. The validation showed that the method is valid to detect and identify 73 antibiotics of the 75 antibiotics studied in meat and aquaculture products at the validation levels.

Serum metabolomics study of Traditional Chinese medicine formula intervention to polycystic ovary syndrome.

PubMed

Lu, Caixia; Zhao, Xinjie; Li, Yan; Li, Yanjie; Yuan, Chengkun; Xu, Fang; Meng, Xiaoyu; Hou, Lihui; Xu, Guowang

2016-02-20

Polycystic ovary syndrome (PCOS) is a most common, heterogeneous, complex endocrinopathy disease. Traditional Chinese medicine (TCM) has been used in the treatment of PCOS for many years. However, the mechanism underlying TCM remains obscure and challenging. In this study, 30 PCOS subjects were separated into normoinsulinemic group (NI=13) and hyperinsulinemic group (HI=17), and treated for three menstrual cycles with TCM Formula, Bushen Huatan Formula (BHF). A metabolomics approach based on ultra-high-performance liquid chromatography (UPLC) coupled with linear ion trap Orbi-trap mass spectrometer (LTQ Orbi-trap MS) is used to investigate serum metabolic changes of TCM intervention to PCOS. After BHF intervention for three menstrual cycles, the serum levels of glycerophosphorylethanolamine (GPEA), creatine, creatinine decreased in both NI and HI groups. Furthermore, in NI group, the main manifestation was the changes of phospholipid metabolism. While in HI group, lysine, phenol sulfate, phe-phe etc. decreased, and ornithine, proline, betaine, acetylcholine etc. increased. Combined with clinical biochemical data, BHF was proved effective to PCOS by reducing the inflammatory reaction and oxidative stress. This study also illustrates that the LC-MS based metabolomic approach is a helpful tool to evaluate curative effect and to understand the mechanisms of TCM. Copyright © 2015 Elsevier B.V. All rights reserved.

Attribution of the discrepancy between ELISA and LC-MS/MS assay results of a PEGylated scaffold protein in post-dose monkey plasma samples due to the presence of anti-drug antibodies.

PubMed

Wang, Shujie J; Wu, Steven T; Gokemeijer, Jochem; Fura, Aberra; Krishna, Murli; Morin, Paul; Chen, Guodong; Price, Karen; Wang-Iverson, David; Olah, Timothy; Weiner, Russell; Tymiak, Adrienne; Jemal, Mohammed

2012-01-01

High-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) and enzyme-linked immunosorbent assay (ELISA) methods were developed for the quantification of a PEGylated scaffold protein drug in monkey plasma samples. The LC-MS/MS method was based on the extraction of the therapeutic protein with a water-miscible organic solvent and the subsequent trypsin digestion of the extract followed by the detection of a surrogate peptide. The assay was linear over a range of 10-3,000 ng/mL. The ELISA method utilized a therapeutic target-binding format in which the recombinant target antigen was used to capture the drug in the sample, followed by detection with an anti-PEG monoclonal antibody. The assay range was 30-2,000 ng/mL. A correlation study between the two methods was performed by measuring the drug concentrations in plasma samples from a single-dose pharmacokinetic (PK) study in cynomolgus monkeys following a 5-mg/kg subcutaneous administration (n = 4). In the early time points of the PK profile, the drug concentrations obtained by the LC-MS/MS method agreed very well with those obtained by the ELISA method. However, at later time points, the drug concentrations measured by the LC-MS/MS method were consistently higher than those measured by the ELISA method. The PK parameters calculated based on the concentration data showed that the two methods gave equivalent peak exposure (C(max)) at 24-48 h. However, the LC-MS/MS results exhibited about 1.53-fold higher total exposure (AUC(tot)) than the ELISA results. The discrepancy between the LC-MS/MS and ELISA results was investigated by conducting immunogenicity testing, anti-drug antibody (ADA) epitope mapping, and Western blot analysis of the drug concentrations coupled with Protein G separation. The results demonstrated the presence of ADA specific to the engineered antigen-binding region of the scaffold protein drug that interfered with the ability of the drug to bind to the target antigen used in the ELISA method. In the presence of the ADAs, the ELISA method measured only the active circulating drug (target-binding), while the LC-MS/MS method measured the total circulating drug. The work presented here indicates that the bioanalysis of protein drugs may be complicated owing to the presence of drug-binding endogenous components or ADAs in the post-dose (incurred) samples. The clear understanding of the behavior of different bioanalytical techniques vis-à-vis the potentially interfering components found in incurred samples is critical in selecting bioanalytical strategies for measuring protein drugs.

Target analyte quantification by isotope dilution LC-MS/MS directly referring to internal standard concentrations--validation for serum cortisol measurement.

PubMed

Maier, Barbara; Vogeser, Michael

2013-04-01

Isotope dilution LC-MS/MS methods used in the clinical laboratory typically involve multi-point external calibration in each analytical series. Our aim was to test the hypothesis that determination of target analyte concentrations directly derived from the relation of the target analyte peak area to the peak area of a corresponding stable isotope labelled internal standard compound [direct isotope dilution analysis (DIDA)] may be not inferior to conventional external calibration with respect to accuracy and reproducibility. Quality control samples and human serum pools were analysed in a comparative validation protocol for cortisol as an exemplary analyte by LC-MS/MS. Accuracy and reproducibility were compared between quantification either involving a six-point external calibration function, or a result calculation merely based on peak area ratios of unlabelled and labelled analyte. Both quantification approaches resulted in similar accuracy and reproducibility. For specified analytes, reliable analyte quantification directly derived from the ratio of peak areas of labelled and unlabelled analyte without the need for a time consuming multi-point calibration series is possible. This DIDA approach is of considerable practical importance for the application of LC-MS/MS in the clinical laboratory where short turnaround times often have high priority.

Metabolic changes in transgenic maize mature seeds over-expressing the Aspergillus niger phyA2.

PubMed

Rao, Jun; Yang, Litao; Guo, Jinchao; Quan, Sheng; Chen, Guihua; Zhao, Xiangxiang; Zhang, Dabing; Shi, Jianxin

2016-02-01

Non-targeted metabolomics analysis revealed only intended metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2. Genetically modified (GM) crops account for a large proportion of modern agriculture worldwide, raising increasingly the public concerns of safety. Generally, according to substantial equivalence principle, if a GM crop is demonstrated to be equivalently safe to its conventional species, it is supposed to be safe. In this study, taking the advantage of an established non-target metabolomic profiling platform based on the combination of UPLC-MS/MS with GC-MS, we compared the mature seed metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2 with its non-transgenic counterpart and other 14 conventional maize lines. In total, levels of nine out of identified 210 metabolites were significantly changed in transgenic maize as compared with its non-transgenic counterpart, and the number of significantly altered metabolites was reduced to only four when the natural variations were taken into consideration. Notably, those four metabolites were all associated with targeted engineering pathway. Our results indicated that although both intended and non-intended metabolic changes occurred in the mature seeds of this GM maize event, only intended metabolic pathway was found to be out of the range of the natural metabolic variation in the metabolome of the transgenic maize. Therefore, only when natural metabolic variation was taken into account, could non-targeted metabolomics provide reliable objective compositional substantial equivalence analysis on GM crops.

Novel approach in LC-MS/MS using MRM to generate a full profile of acyl-CoAs: discovery of acyl-dephospho-CoAs.

PubMed

Li, Qingling; Zhang, Shenghui; Berthiaume, Jessica M; Simons, Brigitte; Zhang, Guo-Fang

2014-03-01

A metabolomic approach to selectively profile all acyl-CoAs was developed using a programmed multiple reaction monitoring (MRM) method in LC-MS/MS and was employed in the analysis of various rat organs. The programmed MRM method possessed 300 mass ion transitions with the mass difference of 507 between precursor ion (Q1) and product ion (Q3), and the precursor ion started from m/z 768 and progressively increased one mass unit at each step. Acyl-dephospho-CoAs resulting from the dephosphorylation of acyl-CoAs were identified by accurate MS and fragmentation. Acyl-dephospho-CoAs were also quantitatively scanned by the MRM method with the mass difference of 427 between Q1 and Q3 mass ions. Acyl-CoAs and dephospho-CoAs were assayed with limits of detection ranging from 2 to 133 nM. The accuracy of the method was demonstrated by assaying a range of concentrations of spiked acyl-CoAs with the results of 80-114%. The distribution of acyl-CoAs reflects the metabolic status of each organ. The physiological role of dephosphorylation of acyl-CoAs remains to be further characterized. The methodology described herein provides a novel strategy in metabolomic studies to quantitatively and qualitatively profile all potential acyl-CoAs and acyl-dephospho-CoAs.

Hepatic Metabolomics Investigation in Acute and Chronic Murine Toxoplasmosis.

PubMed

Chen, Xiao-Qing; Elsheikha, Hany M; Hu, Rui-Si; Hu, Gui-Xue; Guo, Shu-Ling; Zhou, Chun-Xue; Zhu, Xing-Quan

2018-01-01

Toxoplasma gondii poses a great threat to human health, with no approved vaccine available for the treatment of T. gondii infection. T. gondii infections are not limited to the brain, and may also affect other organs especially the liver. Identification of host liver molecules or pathways involved in T. gondii replication process may lead to the discovery of novel anti- T. gondii targets. Here, we analyzed the metabolic profile of the liver of mice on 11 and 30 days postinfection (dpi) with type II T. gondii Pru strain. Global metabolomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 389 significant metabolites from acutely infected mice; and 368 from chronically infected mice, when compared with control mice. Multivariate statistical analysis revealed distinct metabolic signatures from acutely infected, chronically infected and control mice. Infection influenced several metabolic processes, in particular those for lipids and amino acids. Metabolic pathways, such as steroid hormone biosynthesis, primary bile acid biosynthesis, bile secretion, and biosynthesis of unsaturated fatty acids were perturbed during the whole infection process, particularly during the acute stage of infection. The present results provide insight into hepatic metabolic changes that occur in BALB/c mice during acute and chronic T. gondii infection.

Cold acclimation wholly reorganizes the Drosophila melanogaster transcriptome and metabolome

PubMed Central

MacMillan, Heath A.; Knee, Jose M.; Dennis, Alice B.; Udaka, Hiroko; Marshall, Katie E.; Merritt, Thomas J. S.; Sinclair, Brent J.

2016-01-01

Cold tolerance is a key determinant of insect distribution and abundance, and thermal acclimation can strongly influence organismal stress tolerance phenotypes, particularly in small ectotherms like Drosophila. However, there is limited understanding of the molecular and biochemical mechanisms that confer such impressive plasticity. Here, we use high-throughput mRNA sequencing (RNA-seq) and liquid chromatography – mass spectrometry (LC-MS) to compare the transcriptomes and metabolomes of D. melanogaster acclimated as adults to warm (rearing) (21.5 °C) or cold conditions (6 °C). Cold acclimation improved cold tolerance and led to extensive biological reorganization: almost one third of the transcriptome and nearly half of the metabolome were differentially regulated. There was overlap in the metabolic pathways identified via transcriptomics and metabolomics, with proline and glutathione metabolism being the most strongly-supported metabolic pathways associated with increased cold tolerance. We discuss several new targets in the study of insect cold tolerance (e.g. dopamine signaling and Na+-driven transport), but many previously identified candidate genes and pathways (e.g. heat shock proteins, Ca2+ signaling, and ROS detoxification) were also identified in the present study, and our results are thus consistent with and extend the current understanding of the mechanisms of insect chilling tolerance. PMID:27357258

Metabolomic profile of systemic sclerosis patients.

PubMed

Murgia, Federica; Svegliati, Silvia; Poddighe, Simone; Lussu, Milena; Manzin, Aldo; Spadoni, Tatiana; Fischetti, Colomba; Gabrielli, Armando; Atzori, Luigi

2018-05-16

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726-0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7-0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

Metabolic Profile of the Cellulolytic Industrial Actinomycete Thermobifida fusca

PubMed Central

Vanee, Niti

2017-01-01

Actinomycetes have a long history of being the source of numerous valuable natural products and medicinals. To expedite product discovery and optimization of biochemical production, high-throughput technologies can now be used to screen the library of compounds present (or produced) at a given time in an organism. This not only facilitates chemical product screening, but also provides a comprehensive methodology to the study cellular metabolic networks to inform cellular engineering. Here, we present some of the first metabolomic data of the industrial cellulolytic actinomycete Thermobifida fusca generated using LC-MS/MS. The underlying objective of conducting global metabolite profiling was to gain better insight on the innate capabilities of T. fusca, with a long-term goal of facilitating T. fusca-based bioprocesses. The T. fusca metabolome was characterized for growth on two cellulose-relevant carbon sources, cellobiose and Avicel. Furthermore, the comprehensive list of measured metabolites was computationally integrated into a metabolic model of T. fusca, to study metabolic shifts in the network flux associated with carbohydrate and amino acid metabolism. PMID:29137138

Targeted isolation and identification of bioactive compounds lowering cholesterol in the crude extracts of crabapples using UPLC-DAD-MS-SPE/NMR based on pharmacology-guided PLS-DA.

PubMed

Wen, Chao; Wang, Dongshan; Li, Xing; Huang, Tao; Huang, Cheng; Hu, Kaifeng

2018-02-20

The anti-hyperlipidemic effects of crude crabapple extracts derived from Malus 'Red jade', Malus hupehensis (Pamp.) Rehd. and Malus prunifolia (Willd.) Borkh. were evaluated on high-fat diet induced obese (HF DIO) mice. The results revealed that some of these extracts could lower serum cholesterol levels in HF DIO mice. The same extracts were also parallelly analyzed by LC-MS in both positive and negative ionization modes. Based on the pharmacological results, 22 LC-MS variables were identified to be correlated with the anti-hyperlipidemic effects using partial least square discriminant analysis (PLS-DA) and independent samples t-test. Further, under the guidance of the bioactivity-correlated LC-MS signals, 10 compounds were targetedly isolated and enriched using UPLC-DAD-MS-SPE and identified/elucidated by NMR together with MS/MS as citric acid(1), p-coumaric acid(2), hyperoside(3), myricetin(4), naringenin(5), quercetin(6), kaempferol(7), gentiopicroside(8), ursolic acid(9) and 8-epiloganic acid(10). Among these 10 compounds, 6 compounds, hyperoside(3), myricetin(4), naringenin(5), quercetin(6), kaempferol(7) and ursolic acid(9), were individually studied and reported to indeed have effects on lowering the serum lipid levels. These results demonstrated the efficiency of this strategy for drug discovery. In contrast to traditional routes to discover bioactive compounds in the plant extracts, targeted isolation and identification of bioactive compounds in the crude plant extracts using UPLC-DAD-MS-SPE/NMR based on pharmacology-guided PLS-DA of LC-MS data brings forward a new efficient dereplicated approach to natural products research for drug discovery. Copyright © 2017 Elsevier B.V. All rights reserved.

The enhanced value of combining conventional and 'omics' analyses in early assessment of drug-induced hepatobiliary injury

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellinger-Ziegelbauer, Heidrun, E-mail: heidrun.ellinger-ziegelbauer@bayerhealthcare.com; Adler, Melanie; Amberg, Alexander

2011-04-15

The InnoMed PredTox consortium was formed to evaluate whether conventional preclinical safety assessment can be significantly enhanced by incorporation of molecular profiling ('omics') technologies. In short-term toxicological studies in rats, transcriptomics, proteomics and metabolomics data were collected and analyzed in relation to routine clinical chemistry and histopathology. Four of the sixteen hepato- and/or nephrotoxicants given to rats for 1, 3, or 14 days at two dose levels induced similar histopathological effects. These were characterized by bile duct necrosis and hyperplasia and/or increased bilirubin and cholestasis, in addition to hepatocyte necrosis and regeneration, hepatocyte hypertrophy, and hepatic inflammation. Combined analysis ofmore » liver transcriptomics data from these studies revealed common gene expression changes which allowed the development of a potential sequence of events on a mechanistic level in accordance with classical endpoint observations. This included genes implicated in early stress responses, regenerative processes, inflammation with inflammatory cell immigration, fibrotic processes, and cholestasis encompassing deregulation of certain membrane transporters. Furthermore, a preliminary classification analysis using transcriptomics data suggested that prediction of cholestasis may be possible based on gene expression changes seen at earlier time-points. Targeted bile acid analysis, based on LC-MS metabonomics data demonstrating increased levels of conjugated or unconjugated bile acids in response to individual compounds, did not provide earlier detection of toxicity as compared to conventional parameters, but may allow distinction of different types of hepatobiliary toxicity. Overall, liver transcriptomics data delivered mechanistic and molecular details in addition to the classical endpoint observations which were further enhanced by targeted bile acid analysis using LC/MS metabonomics.« less

Development of an ESI-LC-MS-based assay for kinetic evaluation of Mycobacterium tuberculosis shikimate kinase activity and inhibition.

PubMed

Simithy, Johayra; Gill, Gobind; Wang, Yu; Goodwin, Douglas C; Calderón, Angela I

2015-02-17

A simple and reliable liquid chromatography-mass spectrometry (LC-MS) assay has been developed and validated for the kinetic characterization and evaluation of inhibitors of shikimate kinase from Mycobacterium tuberculosis (MtSK), a potential target for the development of novel antitubercular drugs. This assay is based on the direct determination of the reaction product shikimate-3-phosphate (S3P) using electrospray ionization (ESI) and a quadrupole time-of-flight (Q-TOF) detector. A comparative analysis of the kinetic parameters of MtSK obtained by the LC-MS assay with those obtained by a conventional UV-assay was performed. Kinetic parameters determined by LC-MS were in excellent agreement with those obtained from the UV assay, demonstrating the accuracy, and reliability of this method. The validated assay was successfully applied to the kinetic characterization of a known inhibitor of shikimate kinase; inhibition constants and mode of inhibition were accurately delineated with LC-MS.

Metabolomics evaluation of the impact of smokeless tobacco exposure on the oral bacterium Capnocytophaga sputigena

PubMed Central

Sun, Jinchun; Jin, Jinshan; Beger, Richard D.; Cerniglia, Carl E.; Yang, Maocheng; Chen, Huizhong

2017-01-01

The association between exposure to smokeless tobacco products (STP) and oral diseases is partially due to the physiological and pathological changes in the composition of the oral microbiome and its metabolic profile. However, it is not clear how STPs affect the physiology and ecology of oral microbiota. A UPLC/QTof-MS-based metabolomics study was employed to analyze metabolic alterations in oral bacterium, Capnocytophaga sputigena as a result of smokeless tobacco exposure and to assess the capability of the bacterium to metabolize nicotine. Pathway analysis of the metabolome profiles indicated that smokeless tobacco extracts caused oxidative stress in the bacterium. The metabolomics data also showed that the argininenitric oxide pathway was perturbed by the smokeless tobacco treatment. Results also showed that LC/MS was useful in identifying STP constituents and additives, including caffeine and many flavoring compounds. No significant changes in levels of nicotine and its major metabolites were found when C. sputigena was cultured in a nutrient rich medium, although hydroxylnicotine and cotinine N-oxide were detected in the bacterial metabolites suggesting that nicotine metabolism might be present as a minor degradation pathway in the bacterium. Study results provide new insights regarding the physiological and toxicological effects of smokeless tobacco on oral bacterium C. sputigena and associated oral health as well as measuring the ability of the oral bacterium to metabolize nicotine. PMID:27480511

Metabolomics evaluation of the impact of smokeless tobacco exposure on the oral bacterium Capnocytophaga sputigena.

PubMed

Sun, Jinchun; Jin, Jinshan; Beger, Richard D; Cerniglia, Carl E; Yang, Maocheng; Chen, Huizhong

2016-10-01

The association between exposure to smokeless tobacco products (STP) and oral diseases is partially due to the physiological and pathological changes in the composition of the oral microbiome and its metabolic profile. However, it is not clear how STPs affect the physiology and ecology of oral microbiota. A UPLC/QTof-MS-based metabolomics study was employed to analyze metabolic alterations in oral bacterium, Capnocytophaga sputigena as a result of smokeless tobacco exposure and to assess the capability of the bacterium to metabolize nicotine. Pathway analysis of the metabolome profiles indicated that smokeless tobacco extracts caused oxidative stress in the bacterium. The metabolomics data also showed that the arginine-nitric oxide pathway was perturbed by the smokeless tobacco treatment. Results also showed that LC/MS was useful in identifying STP constituents and additives, including caffeine and many flavoring compounds. No significant changes in levels of nicotine and its major metabolites were found when C. sputigena was cultured in a nutrient rich medium, although hydroxylnicotine and cotinine N-oxide were detected in the bacterial metabolites suggesting that nicotine metabolism might be present as a minor degradation pathway in the bacterium. Study results provide new insights regarding the physiological and toxicological effects of smokeless tobacco on oral bacterium C. sputigena and associated oral health as well as measuring the ability of the oral bacterium to metabolize nicotine. Published by Elsevier Ltd.

Macranthoidin B Modulates Key Metabolic Pathways to Enhance ROS Generation and Induce Cytotoxicity and Apoptosis in Colorectal Cancer.

PubMed

Fan, Xing; Rao, Jun; Zhang, Ziwei; Li, Dengfeng; Cui, Wenhao; Zhang, Jun; Wang, Hua; Tou, Fangfang; Zheng, Zhi; Shen, Qiang

2018-01-01

Induction of oxidative stress and reactive oxygen species (ROS) mediated-apoptosis have been utilized as effective strategies in anticancer therapy. Macranthoidin B (MB) is a potent inducer of ROS-mediated apoptosis in cancer, but its mechanism of action is poorly understood. Superoxide production with MB exposure in colorectal cancer (CRC) cells was measured using lucigenin chemiluminescence and real-time PCR. MB's inhibitory effect on proliferation and viability of CRC cells was determined by proliferation assays. MB's effect on apoptosis of CRC cells was determined by Western blotting and annexin V-FITC/PI staining. MB's effect on the growth of CRC xenografts in mice was assessed. An established metabolomics profiling platform combining ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS) with gas chromatography-mass spectrometry (GC-MS) was performed to determine MB's effect on total metabolite variation in CRC cells. We found that MB increases ROS generation via modulating key metabolic pathways. Using metabolomics profiling platform combining LC-MS with GC-MS, a total of 236 metabolites were identified in HCT-116 cells in which 31 metabolites were determined to be significantly regulated (p ≤ 0.05) after MB exposure. A number of key metabolites revealed by metabolomics analysis include glucose, fructose, citrate, arginine, phenylalanine, and S-adenosylhomocysteine (SAH), suggesting specific modulation of metabolism on carbohydrates, amino acids and peptides, lipids, nucleotide, cofactors and vitamins in HCT-116 CRC cells with MB treatment highly associated with apoptosis triggered by enhanced ROS and activated caspase-3. Our results demonstrate that MB represses CRC cell proliferation by inducing ROS-mediated apoptosis. © 2018 The Author(s). Published by S. Karger AG, Basel.

Development of an Integrated Metabolomic Profiling Approach for Infectious Diseases Research

PubMed Central

Lv, Haitao; Hung, Chia S.; Chaturvedi, Kaveri S.; Hooton, Thomas M.; Henderson, Jeffrey P.

2013-01-01

Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ∼2300 molecular features. Principal components analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts. PMID:21922104

Development of a Magnetic Microbead Affinity Selection Screen (MagMASS) Using Mass Spectrometry for Ligands to the Retinoid X Receptor-α

NASA Astrophysics Data System (ADS)

Rush, Michael D.; Walker, Elisabeth M.; Prehna, Gerd; Burton, Tristesse; van Breemen, Richard B.

2017-03-01

To overcome limiting factors in mass spectrometry-based screening methods such as automation while still facilitating the screening of complex mixtures such as botanical extracts, magnetic microbead affinity selection screening (MagMASS) was developed. The screening process involves immobilization of a target protein on a magnetic microbead using a variety of possible chemistries, incubation with mixtures of molecules containing possible ligands, a washing step that removes non-bound compounds while a magnetic field retains the beads in the microtiter well, and an organic solvent release step followed by LC-MS analysis. Using retinoid X receptor-α (RXRα) as an example, which is a nuclear receptor and target for anti-inflammation therapy as well as cancer treatment and prevention, a MagMASS assay was developed and compared with an existing screening assay, pulsed ultrafiltration (PUF)-MS. Optimization of MagMASS involved evaluation of multiple protein constructs and several magnetic bead immobilization chemistries. The full-length RXRα construct immobilized with amylose beads provided optimum results. Additional enhancements of MagMASS were the application of 96-well plates to enable automation, use of UHPLC instead of HPLC for faster MS analyses, and application of metabolomics software for faster, automated data analysis. Performance of MagMASS was demonstrated using mixtures of synthetic compounds and known ligands spiked into botanical extracts.

iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation

PubMed Central

2014-01-01

Background Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work. Results We developed a software toolkit, iPhos, to facilitate and streamline the work-flow of AP-assisted phosphoproteome characterization. The iPhos tookit includes one assister and three modules. The iPhos Peak Extraction Assister automates the batch mode peak extraction for multiple liquid chromatography mass spectrometry (LC-MS) runs. iPhos Module-1 can process the peak lists extracted from the LC-MS analyses derived from the original and dephosphorylated samples to mine out potential phosphorylated peptide signals based on mass shift caused by the loss of some multiples of phosphate groups. And iPhos Module-2 provides customized inclusion lists with peak retention time windows for subsequent targeted LC-MS/MS experiments. Finally, iPhos Module-3 facilitates to link the peptide identifications from protein search engines to the quantification results from pattern-based label-free quantification tools. We further demonstrated the utility of the iPhos toolkit on the data of human metastatic lung cancer cells (CL1-5). Conclusions In the comparison study of the control group of CL1-5 cell lysates and the treatment group of dasatinib-treated CL1-5 cell lysates, we demonstrated the applicability of the iPhos toolkit and reported the experimental results based on the iPhos-facilitated phosphoproteome investigation. And further, we also compared the strategy with pure DDA-based LC-MS/MS phosphoproteome investigation. The results of iPhos-facilitated targeted LC-MS/MS analysis convey more thorough and confident phosphopeptide identification than the results of pure DDA-based analysis. PMID:25521246

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

LipidMiner: A Software for Automated Identification and Quantification of Lipids from Multiple Liquid Chromatography-Mass Spectrometry Data Files

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Da; Zhang, Qibin; Gao, Xiaoli

2014-04-30

We have developed a tool for automated, high-throughput analysis of LC-MS/MS data files, which greatly simplifies LC-MS based lipidomics analysis. Our results showed that LipidMiner is accurate and comprehensive in identification and quantification of lipid molecular species. In addition, the workflow implemented in LipidMiner is not limited to identification and quantification of lipids. If a suitable metabolite library is implemented in the library matching module, LipidMiner could be reconfigured as a tool for general metabolomics data analysis. It is of note that LipidMiner currently is limited to singly charged ions, although it is adequate for the purpose of lipidomics sincemore » lipids are rarely multiply charged,[14] even for the polyphosphoinositides. LipidMiner also only processes file formats generated from mass spectrometers from Thermo, i.e. the .RAW format. In the future, we are planning to accommodate file formats generated by mass spectrometers from other predominant instrument vendors to make this tool more universal.« less

Ion trace detection algorithm to extract pure ion chromatograms to improve untargeted peak detection quality for liquid chromatography/time-of-flight mass spectrometry-based metabolomics data.

PubMed

Wang, San-Yuan; Kuo, Ching-Hua; Tseng, Yufeng J

2015-03-03

Able to detect known and unknown metabolites, untargeted metabolomics has shown great potential in identifying novel biomarkers. However, elucidating all possible liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS) ion signals in a complex biological sample remains challenging since many ions are not the products of metabolites. Methods of reducing ions not related to metabolites or simply directly detecting metabolite related (pure) ions are important. In this work, we describe PITracer, a novel algorithm that accurately detects the pure ions of a LC/TOF-MS profile to extract pure ion chromatograms and detect chromatographic peaks. PITracer estimates the relative mass difference tolerance of ions and calibrates the mass over charge (m/z) values for peak detection algorithms with an additional option to further mass correction with respect to a user-specified metabolite. PITracer was evaluated using two data sets containing 373 human metabolite standards, including 5 saturated standards considered to be split peaks resultant from huge m/z fluctuation, and 12 urine samples spiked with 50 forensic drugs of varying concentrations. Analysis of these data sets show that PITracer correctly outperformed existing state-of-art algorithm and extracted the pure ion chromatograms of the 5 saturated standards without generating split peaks and detected the forensic drugs with high recall, precision, and F-score and small mass error.

Chiral PCB 91 and 149 Toxicity Testing in Embryo and Larvae (Danio rerio): Application of Targeted Metabolomics via UPLC-MS/MS

NASA Astrophysics Data System (ADS)

Chai, Tingting; Cui, Feng; Yin, Zhiqiang; Yang, Yang; Qiu, Jing; Wang, Chengju

2016-09-01

In this study, we aimed to investigate the dysfunction of zebrafish embryos and larvae induced by rac-/(+)-/(-)- PCB91 and rac-/(-)-/(+)- PCB149. UPLC-MS/MS (Ultra-performance liquid chromatography coupled with mass spectrometry) was employed to perform targeted metabolomics analysis, including the quantification of 22 amino acids and the semi-quantitation of 22 other metabolites. Stereoselective changes in target metabolites were observed in embryos and larvae after exposure to chiral PCB91 and PCB149, respectively. In addition, statistical analyses, including PCA and PLS-DA, combined with targeted metabolomics were conducted to identify the characteristic metabolites and the affected pathways. Most of the unique metabolites in embryos and larvae after PCB91/149 exposure were amino acids, and the affected pathways for zebrafish in the developmental stage were metabolic pathways. The stereoselective effects of PCB91/149 on the metabolic pathways of zebrafish embryos and larvae suggest that chiral PCB91/149 exposure has stereoselective toxicity on the developmental stages of zebrafish.

Cultivar Diversity of Grape Skin Polyphenol Composition and Changes in Response to Drought Investigated by LC-MS Based Metabolomics

PubMed Central

Pinasseau, Lucie; Vallverdú-Queralt, Anna; Verbaere, Arnaud; Roques, Maryline; Meudec, Emmanuelle; Le Cunff, Loïc; Péros, Jean-Pierre; Ageorges, Agnès; Sommerer, Nicolas; Boulet, Jean-Claude; Terrier, Nancy; Cheynier, Véronique

2017-01-01

Phenolic compounds represent a large family of plant secondary metabolites, essential for the quality of grape and wine and playing a major role in plant defense against biotic and abiotic stresses. Phenolic composition is genetically driven and greatly affected by environmental factors, including water stress. A major challenge for breeding of grapevine cultivars adapted to climate change and with high potential for wine-making is to dissect the complex plant metabolic response involved in adaptation mechanisms. A targeted metabolomics approach based on ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode has been developed for high throughput profiling of the phenolic composition of grape skins. This method enables rapid, selective, and sensitive quantification of 96 phenolic compounds (anthocyanins, phenolic acids, stilbenoids, flavonols, dihydroflavonols, flavan-3-ol monomers, and oligomers…), and of the constitutive units of proanthocyanidins (i.e., condensed tannins), giving access to detailed polyphenol composition. It was applied on the skins of mature grape berries from a core-collection of 279 Vitis vinifera cultivars grown with or without watering to assess the genetic variation for polyphenol composition and its modulation by irrigation, in two successive vintages (2014–2015). Distribution of berry weights and δ13C values showed that non irrigated vines were subjected to a marked water stress in 2014 and to a very limited one in 2015. Metabolomics analysis of the polyphenol composition and chemometrics analysis of this data demonstrated an influence of water stress on the biosynthesis of different polyphenol classes and cultivar differences in metabolic response to water deficit. Correlation networks gave insight on the relationships between the different polyphenol metabolites and related biosynthetic pathways. They also established patterns of polyphenol response to drought, with different molecular families affected either positively or negatively in the different cultivars, with potential impact on grape and wine quality. PMID:29163566

Metabolomic Analysis of Key Central Carbon Metabolism Carboxylic Acids as Their 3-Nitrophenylhydrazones by UPLC/ESI-MS

PubMed Central

Han, Jun; Gagnon, Susannah; Eckle, Tobias; Borchers, Christoph H.

2014-01-01

Multiple hydroxy-, keto-, di-, and tri-carboxylic acids are among the cellular metabolites of central carbon metabolism (CCM). Sensitive and reliable analysis of these carboxylates is important for many biological and cell engineering studies. In this work, we examined 3-nitrophenylhydrazine as a derivatizing reagent and optimized the reaction conditions for the measurement of ten CCM related carboxylic compounds, including glycolate, lactate, malate, fumarate, succinate, citrate, isocitrate, pyruvate, oxaloacetate, and α-ketoglutarate as their 3-nitrophenylhydrazones using LC/MS with electrospray ionization. With the derivatization protocol which we have developed, and using negative-ion multiple reaction monitoring on a triple-quadrupole instrument, all of the carboxylates showed good linearity within a dynamic range of ca. 200 to more than 2000. The on-column limits of detection and quantitation were from high femtomoles to low picomoles. The analytical accuracies for eight of the ten analytes were determined to be between 89.5 to 114.8% (CV≤7.4%, n=6). Using a quadrupole time-of-flight instrument, the isotopic distribution patterns of these carboxylates, extracted from a 13C-labeled mouse heart, were successfully determined by UPLC/MS with full-mass detection, indicating the possible utility of this analytical method for metabolic flux analysis. In summary, this work demonstrates an efficient chemical derivatization LC/MS method for metabolomic analysis of these key CCM intermediates in a biological matrix. PMID:23580203

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome.

PubMed

Chetwynd, Andrew J; David, Arthur; Hill, Elizabeth M; Abdul-Sada, Alaa

2014-10-01

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.

Current advances in screening for bioactive components from medicinal plants by affinity ultrafiltration mass spectrometry.

PubMed

Chen, Guilin; Huang, Bill X; Guo, Mingquan

2018-05-21

Medicinal plants have played an important role in maintaining human health for thousands of years. However, the interactions between the active components in medicinal plants and some certain biological targets during a disease are still unclear in most cases. To conduct the high-throughput screening for small active molecules that can interact with biological targets, which is of great theoretical significance and practical value. The ultrafiltration mass spectrometry (UF-LC/MS) is a powerful bio-analytical method by combining affinity ultrafiltration and liquid chromatography-mass spectrometry (LC/MS), which could rapidly screen and identify small active molecules that bind to biological targets of interest at the same time. Compared with other analytical methods, affinity UF-LC/MS has the characteristics of fast, sensitive and high throughput, and is especially suitable for the complicated extracts of medicinal plants. In this review, the basic principle, characteristics and some most recent challenges in UF-LC/MS have been demonstrated. Meanwhile, the progress and applications of affinity UF-LC/MS in the discovery of the active components from natural medicinal plants and the interactions between small molecules and biological target proteins are also briefly summarised. In addition, the future directions for UF-LC/MS are also prospected. Affinity UF-LC/MS is a powerful tool in studies on the interactions between small active molecules and biological protein targets, especially in the high-throughput screening of active components from the natural medicinal plants. Copyright © 2018 John Wiley & Sons, Ltd.

Quasi-targeted analysis of hydroxylation-related metabolites of polycyclic aromatic hydrocarbons in human urine by liquid chromatography-mass spectrometry.

PubMed

Tang, Caiming; Tan, Jianhua; Fan, Ruifang; Zhao, Bo; Tang, Caixing; Ou, Weihui; Jin, Jiabin; Peng, Xianzhi

2016-08-26

Metabolite identification is crucial for revealing metabolic pathways and comprehensive potential toxicities of polycyclic aromatic hydrocarbons (PAHs) in human body. In this work, a quasi-targeted analysis strategy was proposed for metabolite identification of monohydroxylated polycyclic aromatic hydrocarbons (OH-PAHs) in human urine using liquid chromatography triple quadruple mass spectrometry (LC-QqQ-MS/MS) combined with liquid chromatography high resolution mass spectrometry (LC-HRMS). Potential metabolites of OH-PAHs were preliminarily screened out by LC-QqQ-MS/MS in association with filtering in a self-constructed information list of possible metabolites, followed by further identification and confirmation with LC-HRMS. The developed method can provide more reliable and systematic results compared with traditional untargeted analysis using LC-HRMS. In addition, data processing for LC-HRMS analysis were greatly simplified. This quasi-targeted analysis method was successfully applied to identifying phase I and phase II metabolites of OH-PAHs in human urine. Five metabolites of hydroxynaphthalene, seven of hydroxyfluorene, four of hydroxyphenanthrene, and three of hydroxypyrene were tentatively identified. Metabolic pathways of PAHs in human body were putatively revealed based on the identified metabolites. The experimental results will be valuable for investigating the metabolic processes of PAHs in human body, and the quasi-targeted analysis strategy can be expanded to the metabolite identification and profiling of other compounds in vivo. Copyright © 2016 Elsevier B.V. All rights reserved.

A Metabolomic Approach to the Study of Wine Micro-Oxygenation

PubMed Central

Arapitsas, Panagiotis; Scholz, Matthias; Vrhovsek, Urska; Di Blasi, Stefano; Biondi Bartolini, Alessandra; Masuero, Domenico; Perenzoni, Daniele; Rigo, Adelio; Mattivi, Fulvio

2012-01-01

Wine micro-oxygenation is a globally used treatment and its effects were studied here by analysing by untargeted LC-MS the wine metabolomic fingerprint. Eight different procedural variations, marked by the addition of oxygen (four levels) and iron (two levels) were applied to Sangiovese wine, before and after malolactic fermentation. Data analysis using supervised and unsupervised multivariate methods highlighted some known candidate biomarkers, together with a number of metabolites which had never previously been considered as possible biomarkers for wine micro-oxygenation. Various pigments and tannins were identified among the known candidate biomarkers. Additional new information was obtained suggesting a correlation between oxygen doses and metal contents and changes in the concentration of primary metabolites such as arginine, proline, tryptophan and raffinose, and secondary metabolites such as succinic acid and xanthine. Based on these findings, new hypotheses regarding the formation and reactivity of wine pigment during micro-oxygenation have been proposed. This experiment highlights the feasibility of using unbiased, untargeted metabolomic fingerprinting to improve our understanding of wine chemistry. PMID:22662221

The LC-MS-based metabolomics of hydroxytyrosol administration in rats reveals amelioration of the metabolic syndrome.

PubMed

Lemonakis, Nikolaos; Poudyal, Hemant; Halabalaki, Maria; Brown, Lindsay; Tsarbopoulos, Anthony; Skaltsounis, Alexios-Leandros; Gikas, Evagelos

2017-01-15

Hydroxytyrosol (HT), an important component of olive fruit and olive oil, improves the signs of metabolic syndrome in rats following chronic treatment. At a dose of 20mg/kg/day, HT decreased adiposity and improved cardiovascular and liver structure and function in rats fed with a high-carbohydrate, high-fat diet. An untargeted metabolomics approach has been employed using both UPLC-Orbitrap and -QqTOF methods to identify the changes induced by chronic HT administration on the plasma metabolome. 31 metabolites have been found to be differentially expressed between the examined groups. HT was shown to decrease biosynthesis of unsaturated fatty acids, fatty acid biosynthesis, and the metabolism of linoleic acid, retinol, sphingolipids and arachidonic acid, whereas glycerolipid metabolism is up-regulated. These are plausible mechanisms for the attenuation by HT of cardiovascular, liver and metabolic changes in high-carbohydrate, high-fat diet fed rats. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

DOE PAGES

Yao, Yushu; Sun, Terence; Wang, Tony; ...

2015-07-20

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.« less

Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction

DOE PAGES

Broeckling, Corey D.; Ganna, Andrea; Layer, Mark; ...

2016-08-25

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, ourmore » analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.« less

Large-scale identification of target proteins of a glycosyltransferase isozyme by Lectin-IGOT-LC/MS, an LC/MS-based glycoproteomic approach

PubMed Central

Sugahara, Daisuke; Kaji, Hiroyuki; Sugihara, Kazushi; Asano, Masahide; Narimatsu, Hisashi

2012-01-01

Model organisms containing deletion or mutation in a glycosyltransferase-gene exhibit various physiological abnormalities, suggesting that specific glycan motifs on certain proteins play important roles in vivo. Identification of the target proteins of glycosyltransferase isozymes is the key to understand the roles of glycans. Here, we demonstrated the proteome-scale identification of the target proteins specific for a glycosyltransferase isozyme, β1,4-galactosyltransferase-I (β4GalT-I). Although β4GalT-I is the most characterized glycosyltransferase, its distinctive contribution to β1,4-galactosylation has been hardly described so far. We identified a large number of candidates for the target proteins specific to β4GalT-I by comparative analysis of β4GalT-I-deleted and wild-type mice using the LC/MS-based technique with the isotope-coded glycosylation site-specific tagging (IGOT) of lectin-captured N-glycopeptides. Our approach to identify the target proteins in a proteome-scale offers common features and trends in the target proteins, which facilitate understanding of the mechanism that controls assembly of a particular glycan motif on specific proteins. PMID:23002422

Acylated flavonol tri- and tetraglycosides in the flavonoid metabolome of Cladrastis kentukea (Leguminosae).

PubMed

Kite, Geoffrey C; Rowe, Emily R; Lewis, Gwilym P; Veitch, Nigel C

2011-04-01

The foliar metabolome of Cladrastis kentukea (Leguminosae) contains a complex mixture of flavonoids including acylated derivatives of the 3-O-rhamnosyl(1→2)[rhamnosyl(1→6)]-galactosides of kaempferol and quercetin and their 7-O-rhamnosides, together with an array of non-acylated kaempferol and quercetin di-, tri- and tetraglycosides. Thirteen of the acylated flavonoids, 12 of which had not been reported previously, were characterised by spectroscopic and chemical methods. Eight of these were the four isomers of kaempferol 3-O-α-l-rhamnopyranosyl(1→2)[α-l-rhamnopyranosyl(1→6)]-(3/4-O-E/Z-p-coumaroyl-β-d-galactopyranoside) and their 7-O-α-l-rhamnopyranosides, and three were isomers of quercetin 3-O-α-l-rhamnopyranosyl(1→2)[α-l-rhamnopyranosyl(1→6)]-(3/4-O-E/Z-p-coumaroyl-β-d-galactopyranoside) - the remaining 4Z isomer was identified by LC-UV-MS analysis of a crude extract. The final two acylated flavonoids characterised by NMR were the 3E and 4E isomers of kaempferol 3-O-α-l-rhamnopyranosyl(1→2)[α-l-rhamnopyranosyl(1→6)]-(3/4-O-E-feruloyl-β-d-galactopyranoside)-7-O-α-l-rhamnopyranoside while the 3Z and 4Z isomers were again detected by LC-UV-MS. Using the observed fragmentation behaviour of the isolated compounds following a variety of MS experiments, a further 18 acylated flavonoids were given tentative structures by LC-MS analysis of a crude extract. Acylated flavonoids were absent from the flowers of C. kentukea, which contained an array of non-acylated kaempferol and quercetin glycosides. Immature fruits contained kaempferol 3-O-α-rhamnopyranosyl(1→2)[α-rhamnopyranosyl(1→6)]-β-galactopyranoside and its 7-O-α-rhamnopyranoside as the major flavonoids with acylated flavonoids, different from those in the leaves, only present as minor constituents. The presence of acylated flavonoids distinguishes the foliar flavonoid metabolome of C. kentukea from that of a closely related legume, Styphnolobium japonicum, which contains a similar range of non-acylated flavonoids. Copyright © 2011 Elsevier Ltd. All rights reserved.

Proposed Confidence Scale and ID Score in the Identification of Known-Unknown Compounds Using High Resolution MS Data

NASA Astrophysics Data System (ADS)

Rochat, Bertrand

2017-04-01

High-resolution (HR) MS instruments recording HR-full scan allow analysts to go further beyond pre-acquisition choices. Untargeted acquisition can reveal unexpected compounds or concentrations and can be performed for preliminary diagnosis attempt. Then, revealed compounds will have to be identified for interpretations. Whereas the need of reference standards is mandatory to confirm identification, the diverse information collected from HRMS allows identifying unknown compounds with relatively high degree of confidence without reference standards injected in the same analytical sequence. However, there is a necessity to evaluate the degree of confidence in putative identifications, possibly before further targeted analyses. This is why a confidence scale and a score in the identification of (non-peptidic) known-unknown, defined as compounds with entries in database, is proposed for (LC-) HRMS data. The scale is based on two representative documents edited by the European Commission (2007/657/EC) and the Metabolomics Standard Initiative (MSI), in an attempt to build a bridge between the communities of metabolomics and screening labs. With this confidence scale, an identification (ID) score is determined as [a number, a letter, and a number] (e.g., 2D3), from the following three criteria: I, a General Identification Category (1, confirmed, 2, putatively identified, 3, annotated compounds/classes, and 4, unknown); II, a Chromatography Class based on the relative retention time (from the narrowest tolerance, A, to no chromatographic references, D); and III, an Identification Point Level (1, very high, 2, high, and 3, normal level) based on the number of identification points collected. Three putative identification examples of known-unknown will be presented.

Characterizing Dissolved Organic Matter and Metabolites in an Actively Serpentinizing Ophiolite Using Global Metabolomics Techniques

NASA Astrophysics Data System (ADS)

Seyler, L. M.; Rempfert, K. R.; Kraus, E. A.; Spear, J. R.; Templeton, A. S.; Schrenk, M. O.

2017-12-01

Environmental metabolomics is an emerging approach used to study ecosystem properties. Through bioinformatic comparisons to metagenomic data sets, metabolomics can be used to study microbial adaptations and responses to varying environmental conditions. Since the techniques are highly parallel to organic geochemistry approaches, metabolomics can also provide insight into biogeochemical processes. These analyses are a reflection of metabolic potential and intersection with other organisms and environmental components. Here, we used an untargeted metabolomics approach to characterize dissolved organic carbon and aqueous metabolites from groundwater obtained from an actively serpentinizing habitat. Serpentinites are known to support microbial communities that feed off of the products of serpentinization (such as methane and H2 gas), while adapted to harsh environmental conditions such as high pH and low DIC availability. However, the biochemistry of microbial populations that inhabit these environments are understudied and are complicated by overlapping biotic and abiotic processes. The aim of this study was to identify potential sources of carbon in an environment that is depleted of soluble inorganic carbon, and to characterize the flow of metabolites and describe overlapping biogenic and abiogenic processes impacting carbon cycling in serpentinizing rocks. We applied untargeted metabolomics techniques to groundwater taken from a series of wells drilled into the Semail Ophiolite in Oman.. Samples were analyzed via quadrupole time-of-flight liquid chromatography tandem mass spectrometry (QToF-LC/MS/MS). Metabolomes and metagenomic data were imported into Progenesis QI software for statistical analysis and correlation, and metabolic networks constructed using the Genome-Linked Application for Metabolic Maps (GLAMM), a web interface tool. Further multivariate statistical analyses and quality control was performed using EZinfo. Pools of dissolved organic carbon could readily be distinguished based on their source rock and the pH of the groundwater sample. Our results are promising regarding the future use of metabolomics techniques in this and other serpentinizing environments, for the identification of nutrients, biomarkers and metabolic pathways in the subsurface biosphere.

LC-MS/MS analysis of uncommon paracetamol metabolites derived through in vitro polymerization and nitration reactions in liquid nitrogen.

PubMed

Trettin, Arne; Jordan, Jens; Tsikas, Dimitrios

2014-09-01

Paracetamol (acetaminophen, APAP) is a commonly used analgesic drug. Known paracetamol metabolites include the glucuronide, sulfate and mercapturate. N-Acetyl-benzoquinonimine (NAPQI) is considered the toxic intermediate metabolite of paracetamol. In vitro and in vivo studies indicate that paracetamol is also metabolized to additional poorly characterized metabolites. For example, metabolomic studies in urine samples of APAP-treated mice revealed metabolites such as APAP-sulfate-APAP and APAP-S-S-APAP in addition to the classical phase II metabolites. Here, we report on the development and application of LC-MS and LC-MS/MS approaches to study reactions of unlabelled and (2)H-labelled APAP with unlabelled and (15)N-labelled nitrite in aqueous phosphate buffers (pH 7.4) upon their immersion into liquid nitrogen (-196°C). In mechanistic studies, these reactions were also studied in aqueous buffer prepared in (18)O-labelled water. LC-MS and LC-MS/MS analyses were performed on a reverse-phase material (C18) using gradient elution (2mM ammonium acetate/acetonitrile), in positive and negative electrospray mode. We identified a series of APAP metabolites including di-, tri- and tetra-APAP, mono- and di-nitro-APAP and nitric ester of di-APAP. Our study indicates that nitrite induces oxidation, i.e., polymerization and nitration of APAP, when buffered APAP/nitrite solutions are immersed into liquid nitrogen. These reactions are specific for nitrite with respect to nitrate and do not proceed via intermediate formation of NAPQI. Potassium ions and physiological saline but not thiols inhibit nitrite- and shock-freeze-induced reactions of paracetamol. The underlying mechanism likely involves in situ formation of NO2 radicals from nitrite secondary to profound pH reduction (down to pH 1) and disproportionation. Polymeric paracetamol species can be analyzed as pentafluorobenzyl derivatives by LC-MS but not by GC-MS. Copyright © 2013 Elsevier B.V. All rights reserved.

Serum Metabolomics to Identify the Liver Disease-Specific Biomarkers for the Progression of Hepatitis to Hepatocellular Carcinoma

NASA Astrophysics Data System (ADS)

Gao, Rong; Cheng, Jianhua; Fan, Chunlei; Shi, Xiaofeng; Cao, Yuan; Sun, Bo; Ding, Huiguo; Hu, Chengjin; Dong, Fangting; Yan, Xianzhong

2015-12-01

Hepatocellular carcinoma (HCC) is a common malignancy that has region specific etiologies. Unfortunately, 85% of cases of HCC are diagnosed at an advanced stage. Reliable biomarkers for the early diagnosis of HCC are urgently required to reduced mortality and therapeutic expenditure. We established a non-targeted gas chromatography-time of flight-mass spectrometry (GC-TOFMS) metabolomics method in conjunction with Random Forests (RF) analysis based on 201 serum samples from healthy controls (NC), hepatitis B virus (HBV), liver cirrhosis (LC) and HCC patients to explore the metabolic characteristics in the progression of hepatocellular carcinogenesis. Ultimately, 15 metabolites were identified intimately associated with the process. Phenylalanine, malic acid and 5-methoxytryptamine for HBV vs. NC, palmitic acid for LC vs. HBV, and asparagine and β-glutamate for HCC vs. LC were screened as the liver disease-specific potential biomarkers with an excellent discriminant performance. All the metabolic perturbations in these liver diseases are associated with pathways for energy metabolism, macromolecular synthesis, and maintaining the redox balance to protect tumor cells from oxidative stress.

Plant-microbe interactions driven by exometabolite preferences of rhizosphere bacteria

NASA Astrophysics Data System (ADS)

Zhalnina, K.; Louie, K. B.; Mansoori, N.; Hao, Z.; Gao, J.; Cho, H. J.; Karaoz, U.; Loqué, D.; Bowen, B.; Firestone, M.; Brodie, E.; Northen, T.

2016-12-01

It is known that rhizosphere bacteria can impact important processes during plant development. In `return' plants release substantial quantities of soluble C into the soil surrounding its roots, attracting bacteria and other soil organisms. Given the potential beneficial and detrimental consequences of stimulating high densities of organisms adjacent to newly formed root, regulating the chemical composition of exudates would represent a potential means of plant selection for beneficial microorganisms. If exudate resource composition functions to select specific microorganisms, then one would expect that substrate specialization exists within the rhizosphere microbiome. Here we provide evidence that in the rhizosphere of wild oats (Avena barbata), specific metabolites are exuded that are preferentially used by selected bacteria in rhizosphere and this substrate specialization, together with the changing composition of root exudates, drives the observed successional patterns. To investigate the relationship between exudates and rhizosphere bacteria we first analyzed exudate composition of hydroponically grown plants using LC-MS/MS based metabolomics. We then designed a medium to simulate plant exudates and using this medium we examined the substrate preferences of a diversity of rhizosphere bacterial isolates. We then assessed the ability of soil isolates to consume exudate components by LC-MS/MS based metabolomics. These substrate preferences were then related to genomic features and successional patterns of bacteria in the Avena rhizosphere. The major fraction of plant exudates was found to be composed of amino- and carboxylic acids, sugars, nucleosides, quaternary amines and plant hormones. Amino acids, sugars and nucleosides were consumed by all analyzed isolates. However, isolates that were preferentially stimulated by plant growth, revealed substrate utilization preferences towards aromatic organic acids, while those not responding to growing roots did not utilize these compounds under these conditions. This substrate partitioning among rhizosphere bacteria can be suggested as a potential mechanism for how plants influence the structure of their rhizosphere microbiome and provides a key insight into the mechanisms underlying patterns of ecological succession in soil.

Metabolomics relative quantitation with mass spectrometry using chemical derivatization and isotope labeling

DOE PAGES

O'Maille, Grace; Go, Eden P.; Hoang, Linh; ...

2008-01-01

Comprehensive detection and quantitation of metabolites from a biological source constitute the major challenges of current metabolomics research. Two chemical derivatization methodologies, butylation and amination, were applied to human serum for ionization enhancement of a broad spectrum of metabolite classes, including steroids and amino acids. LC-ESI-MS analysis of the derivatized serum samples provided a significant signal elevation across the total ion chromatogram to over a 100-fold increase in ionization efficiency. It was also demonstrated that derivatization combined with isotopically labeled reagents facilitated the relative quantitation of derivatized metabolites from individual as well as pooled samples.

Methodological aspects for metabolome visualization and characterization: a metabolomic evaluation of the 24 h evolution of human urine after cocoa powder consumption.

PubMed

Llorach-Asunción, R; Jauregui, O; Urpi-Sarda, M; Andres-Lacueva, C

2010-01-20

The LC-MS based metabolomics studies are characterized by the capacity to produce a large and complex dataset being mandatory to use the appropriate tools to recover and to interpret as maximum information as possible. In this context, a combined partial least square discriminat analysis (PLS-DA) and two-way hierarchical clustering (two-way HCA) using Bonferroni correction as filter is proposed to improve analysis in human urinary metabolome modifications in a nutritional intervention context. After overnight fasting, 10 subjects consumed cocoa powder with milk. Urine samples were collected before the ingestion product and at 0-6, 6-12, 12-24 h after test-meal consumption and analysed by LC-Q-ToF. The PLS-DA analysis showed a clear pattern related to the differences between before consumption period and the other three periods revealing relevant mass features in this separation, however, a weaker association between mass features and the three periods after cocoa consumption was observed. On the other hand, two-way HCA showed a separation of four urine time periods and point out the mass features associated with the corresponding urine times. The correlation matrix revealed complex relations between the mass features that could be used for metabolite identifications and to infer the possible metabolite origin. The reported results prove that combining visualization strategies would be an excellent way to produce new bioinformatic applications that help the scientific community to unravel the complex relations between the consumption of phytochemicals and their expected effects on health.

Development of a GC/Quadrupole-Orbitrap Mass Spectrometer, Part I: Design and Characterization

PubMed Central

2015-01-01

Identification of unknown compounds is of critical importance in GC/MS applications (metabolomics, environmental toxin identification, sports doping, petroleomics, and biofuel analysis, among many others) and remains a technological challenge. Derivation of elemental composition is the first step to determining the identity of an unknown compound by MS, for which high accuracy mass and isotopomer distribution measurements are critical. Here, we report on the development of a dedicated, applications-grade GC/MS employing an Orbitrap mass analyzer, the GC/Quadrupole-Orbitrap. Built from the basis of the benchtop Orbitrap LC/MS, the GC/Quadrupole-Orbitrap maintains the performance characteristics of the Orbitrap, enables quadrupole-based isolation for sensitive analyte detection, and includes numerous analysis modalities to facilitate structural elucidation. We detail the design and construction of the instrument, discuss its key figures-of-merit, and demonstrate its performance for the characterization of unknown compounds and environmental toxins. PMID:25208235

Discovery of Antimalarial Drugs from Streptomycetes Metabolites Using a Metabolomic Approach

PubMed Central

Baba, Mohd Shukri

2017-01-01

Natural products continue to play an important role as a source of biologically active substances for the development of new drug. Streptomyces, Gram-positive bacteria which are widely distributed in nature, are one of the most popular sources of natural antibiotics. Recently, by using a bioassay-guided fractionation, an antimalarial compound, Gancidin-W, has been discovered from these bacteria. However, this classical method in identifying potentially novel bioactive compounds from the natural products requires considerable effort and is a time-consuming process. Metabolomics is an emerging “omics” technology in systems biology study which integrated in process of discovering drug from natural products. Metabolomics approach in finding novel therapeutics agent for malaria offers dereplication step in screening phase to shorten the process. The highly sensitive instruments, such as Liquid Chromatography-Mass Spectrophotometry (LC-MS), Gas Chromatography-Mass Spectrophotometry (GC-MS), and Nuclear Magnetic Resonance (1H-NMR) spectroscopy, provide a wide range of information in the identification of potentially bioactive compounds. The current paper reviews concepts of metabolomics and its application in drug discovery of malaria treatment as well as assessing the antimalarial activity from natural products. Metabolomics approach in malaria drug discovery is still new and needs to be initiated, especially for drug research in Malaysia. PMID:29123551

Identification of RIP-II toxins by affinity enrichment, enzymatic digestion and LC-MS.

PubMed

Fredriksson, Sten-Åke; Artursson, Elisabet; Bergström, Tomas; Östin, Anders; Nilsson, Calle; Åstot, Crister

2015-01-20

Type 2 ribosome-inactivating protein toxins (RIP-II toxins) were enriched and purified prior to enzymatic digestion and LC-MS analysis. The enrichment of the RIP-II family of plant proteins, such as ricin, abrin, viscumin, and volkensin was based on their affinity for galactosyl moieties. A macroporous chromatographic material was modified with a galactose-terminated substituent and packed into miniaturized columns that were used in a chromatographic system to achieve up to 1000-fold toxin enrichment. The galactose affinity of the RIP-II proteins enabled their selective enrichment from water, beverages, and extracts of powder and wipe samples. The enriched fractions were digested with trypsin and RIP-II peptides were identified based on accurate mass LC-MS data. Their identities were unambiguously confirmed by LC-MS/MS product ion scans of peptides unique to each of the toxins. The LC-MS detection limit achieved for ricin target peptides was 10 amol and the corresponding detection limit for the full method was 10 fmol/mL (0.6 ng/mL). The affinity enrichment method was applied to samples from a forensic investigation into a case involving the illegal production of ricin and abrin toxins.

Comprehensive identification and structural characterization of target components from Gelsemium elegans by high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry based on accurate mass databases combined with MS/MS spectra.

PubMed

Liu, Yan-Chun; Xiao, Sa; Yang, Kun; Ling, Li; Sun, Zhi-Liang; Liu, Zhao-Ying

2017-06-01

This study reports an applicable analytical strategy of comprehensive identification and structure characterization of target components from Gelsemium elegans by using high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QqTOF MS) based on the use of accurate mass databases combined with MS/MS spectra. The databases created included accurate masses and elemental compositions of 204 components from Gelsemium and their structural data. The accurate MS and MS/MS spectra were acquired through data-dependent auto MS/MS mode followed by an extraction of the potential compounds from the LC-QqTOF MS raw data of the sample. The same was matched using the databases to search for targeted components in the sample. The structures for detected components were tentatively characterized by manually interpreting the accurate MS/MS spectra for the first time. A total of 57 components have been successfully detected and structurally characterized from the crude extracts of G. elegans, but has failed to differentiate some isomers. This analytical strategy is generic and efficient, avoids isolation and purification procedures, enables a comprehensive structure characterization of target components of Gelsemium and would be widely applicable for complicated mixtures that are derived from Gelsemium preparations. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Metabolic system alterations in pancreatic cancer patient serum: potential for early detection

PubMed Central

2013-01-01

Background The prognosis of pancreatic cancer (PC) is one of the poorest among all cancers, due largely to the lack of methods for screening and early detection. New biomarkers for identifying high-risk or early-stage subjects could significantly impact PC mortality. The goal of this study was to find metabolic biomarkers associated with PC by using a comprehensive metabolomics technology to compare serum profiles of PC patients to healthy control subjects. Methods A non-targeted metabolomics approach based on high-resolution, flow-injection Fourier transform ion cyclotron resonance mass spectrometry (FI-FTICR-MS) was used to generate comprehensive metabolomic profiles containing 2478 accurate mass measurements from the serum of Japanese PC patients (n=40) and disease-free subjects (n=50). Targeted flow-injection tandem mass spectrometry (FI-MS/MS) assays for specific metabolic systems were developed and used to validate the FI-FTICR-MS results. A FI-MS/MS assay for the most discriminating metabolite discovered by FI-FTICR-MS (PC-594) was further validated in two USA Caucasian populations; one comprised 14 PCs, six intraductal papillary mucinous neoplasims (IPMN) and 40 controls, and a second comprised 1000 reference subjects aged 30 to 80, which was used to create a distribution of PC-594 levels among the general population. Results FI-FTICR-MS metabolomic analysis showed significant reductions in the serum levels of metabolites belonging to five systems in PC patients compared to controls (all p<0.000025). The metabolic systems included 36-carbon ultra long-chain fatty acids, multiple choline-related systems including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins, as well as vinyl ether-containing plasmalogen ethanolamines. ROC-AUCs based on FI-MS/MS of selected markers from each system ranged between 0.93 ±0.03 and 0.97 ±0.02. No significant correlations between any of the systems and disease-stage, gender, or treatment were observed. Biomarker PC-594 (an ultra long-chain fatty acid), was further validated using an independently-collected US Caucasian population (blinded analysis, n=60, p=9.9E-14, AUC=0.97 ±0.02). PC-594 levels across 1000 reference subjects showed an inverse correlation with age, resulting in a drop in the AUC from 0.99 ±0.01 to 0.90 ±0.02 for subjects aged 30 to 80, respectively. A PC-594 test positivity rate of 5.0% in low-risk reference subjects resulted in a PC sensitivity of 87% and a significant improvement in net clinical benefit based on decision curve analysis. Conclusions The serum metabolome of PC patients is significantly altered. The utility of serum metabolite biomarkers, particularly PC-594, for identifying subjects with elevated risk of PC should be further investigated. PMID:24024929

Fingerprinting-based metabolomic approach with LC-MS to sleep apnea and hypopnea syndrome: a pilot study.

PubMed

Ferrarini, Alessia; Rupérez, Francisco J; Erazo, Marcela; Martínez, Ma Paz; Villar-Álvarez, Felipe; Peces-Barba, Germán; González-Mangado, Nicolás; Troncoso, María F; Ruiz-Cabello, Jesús; Barbas, Coral

2013-10-01

Sleep apnea and hypopnea syndrome (SAHS) is a multicomponent disorder, with associated cardiovascular and metabolic alterations, second in order of frequency among respiratory disorders. Sleep apnea is diagnosed with an overnight sleep test called a polysomnogram, which requires having the patient in hospital. In addition, a more clear classification of patients according to mild and severe presentations would be desirable. The aim of the present study was to assess the relative metabolic changes in SAHS to identify new potential biomarkers for diagnosis, able to evaluate disease severity to establish response to therapeutic interventions and outcomes. For this purpose, metabolic fingerprinting represents a valuable strategy to monitor, in a nontargeted manner, the changes that are at the base of the pathophysiological mechanism of SAHS. Plasma samples of 33 SAHS patients were collected after polysomnography and analyzed with LC coupled to MS (LC-QTOF-MS). After data treatment and statistical analysis, signals differentiating nonsevere and severe patients were detected. Putative identification of 14 statistically significant features was obtained and changes that can be related to the episodes of hypoxia/reoxygenation (inflammation) have been highlighted. Among them, the patterns of variation of platelet activating factor and lysophospholipids, together with some compounds related to differential activity of the gut microflora (bile pigments and pipecolic acid) open new lines of research that will benefit our understanding of the alterations, offering new possibilities for adequate monitoring of the stage of the disease. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impact of a transposon insertion in phzF2 on the specialized metabolite production and interkingdom interactions of Pseudomonas aeruginosa.

PubMed

Phelan, Vanessa V; Moree, Wilna J; Aguilar, Julieta; Cornett, Dale S; Koumoutsi, Alexandra; Noble, Suzanne M; Pogliano, Kit; Guerrero, Carlos A; Dorrestein, Pieter C

2014-05-01

In microbiology, gene disruption and subsequent experiments often center on phenotypic changes caused by one class of specialized metabolites (quorum sensors, virulence factors, or natural products), disregarding global downstream metabolic effects. With the recent development of mass spectrometry-based methods and technologies for microbial metabolomics investigations, it is now possible to visualize global production of diverse classes of microbial specialized metabolites simultaneously. Using imaging mass spectrometry (IMS) applied to the analysis of microbiology experiments, we can observe the effects of mutations, knockouts, insertions, and complementation on the interactive metabolome. In this study, a combination of IMS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to visualize the impact on specialized metabolite production of a transposon insertion into a Pseudomonas aeruginosa phenazine biosynthetic gene, phzF2. The disruption of phenazine biosynthesis led to broad changes in specialized metabolite production, including loss of pyoverdine production. This shift in specialized metabolite production significantly alters the metabolic outcome of an interaction with Aspergillus fumigatus by influencing triacetylfusarinine production.

Impact of a Transposon Insertion in phzF2 on the Specialized Metabolite Production and Interkingdom Interactions of Pseudomonas aeruginosa

PubMed Central

Phelan, Vanessa V.; Moree, Wilna J.; Aguilar, Julieta; Cornett, Dale S.; Koumoutsi, Alexandra; Noble, Suzanne M.; Pogliano, Kit; Guerrero, Carlos A.

2014-01-01

In microbiology, gene disruption and subsequent experiments often center on phenotypic changes caused by one class of specialized metabolites (quorum sensors, virulence factors, or natural products), disregarding global downstream metabolic effects. With the recent development of mass spectrometry-based methods and technologies for microbial metabolomics investigations, it is now possible to visualize global production of diverse classes of microbial specialized metabolites simultaneously. Using imaging mass spectrometry (IMS) applied to the analysis of microbiology experiments, we can observe the effects of mutations, knockouts, insertions, and complementation on the interactive metabolome. In this study, a combination of IMS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to visualize the impact on specialized metabolite production of a transposon insertion into a Pseudomonas aeruginosa phenazine biosynthetic gene, phzF2. The disruption of phenazine biosynthesis led to broad changes in specialized metabolite production, including loss of pyoverdine production. This shift in specialized metabolite production significantly alters the metabolic outcome of an interaction with Aspergillus fumigatus by influencing triacetylfusarinine production. PMID:24532776

LC-QTOF-MS-based targeted metabolomics of arginine-creatine metabolic pathway-related compounds in plasma: application to identify potential biomarkers in pediatric chronic kidney disease.

PubMed

Benito, Sandra; Sánchez, Alicia; Unceta, Nora; Andrade, Fernando; Aldámiz-Echevarria, Luis; Goicolea, M Aránzazu; Barrio, Ramón J

2016-01-01

Chronic kidney disease (CKD) is a major epidemiologic problem which causes several disturbances in adults and in pediatrics. Despite being a worldwide public health problem, information available for CKD in the pediatric population is scarce. For that reason, an ion-pair reversed-phase liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) method has been developed and validated in order to analyze 16 amino acids, amino acid derivatives, and analogous compounds related to the arginine-creatine metabolic pathway that are suspicious of being increased or decreased in plasma from patients with CKD. The analytical method involved the addition of dithiothreitol, a reducing agent which reduces disulfide and thus giving total aminothiol concentration, as well as a simple precipitation of plasma proteins. Moreover, despite amino acids being usually derivatized to improve their retention time and to enhance their signal, for this method, an ion-pairing reagent was used, thus avoiding the need for derivatization. Subsequently, analysis of plasma from pediatric patients suffering from CKD and control pediatrics was carried out. As a result, glycine, citrulline, creatinine, asymmetric dimethylarginine (ADMA), and symmetric dimethylarginine (SDMA) were significantly increased in patients with CKD, regardless of their creatinine level, whereas in addition to these compounds dimethylglycine was also increased when CKD patients had plasma creatinine concentrations above 12 μg mL(-1), thus all are suggested as potential biomarkers for renal impairment.

A Method for LC-MS/MS Profiling of Coumarins in Zanthoxylum zanthoxyloides (Lam.) B. Zepernich and Timler Extracts and Essential Oils.

PubMed

Tine, Yoro; Renucci, Franck; Costa, Jean; Wélé, Alassane; Paolini, Julien

2017-01-22

The metabolites from the coumarin class, present in tissues of plants belonging mainly to the Rutaceae and Apiaceae families, included compounds with high chemical diversity such as simple coumarins and furocoumarins. These health-promoting components are recognized for their valuable biological activities in herbal preparations but also for their phototoxic effects. In this work, a targeted liquid chromatography (LC) coupled with tandem mass spectrometry (MS²) was developed for the screening of 39 reference standards of coumarins and furocoumarins in essential oils and plant extracts. Chromatographic separation was accomplished on reversed phase column using water/acetonitrile as the mobile phase and detection was performed on a hybrid QqQ/linear ion trap spectrometer fitted with an atmospheric pressure chemical ionization (APCI) source operating in positive ion mode. This analytical approach was applied to investigate the coumarin compositions of fruit essential oils and methanolic extracts obtained from separated parts (fruit, leaf, stem, trunk, and root) of Zanthoxylum zanthoxyloides . Ten coumarins and six furanocoumarins were reported in this species and data analyses were used to assess the suitability of these compounds to the metabolomics-based differentiation of plant organs. The quantification criteria of the metabolites in extract samples included linearity, limit of quantification, limit of detection, and matrix effect were validated. As reported for other species of the Rutaceae family, the concentration of coumarins was drastically higher in Z. zanthoxyloides fruits than in other plant organs.

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

PubMed Central

Liu, Xiaojing; Ser, Zheng; Cluntun, Ahmad A.; Mentch, Samantha J.; Locasale, Jason W.

2014-01-01

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases. PMID:24894601

Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

PubMed

Wang, Zhengfang; Jablonski, Joseph E

2016-01-01

Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

Chicken, beams, and Campylobacter: rapid differentiation of foodborne bacteria via vibrational spectroscopy and MALDI-mass spectrometry.

PubMed

Muhamadali, Howbeer; Weaver, Danielle; Subaihi, Abdu; AlMasoud, Najla; Trivedi, Drupad K; Ellis, David I; Linton, Dennis; Goodacre, Royston

2016-01-07

Campylobacter species are one of the main causes of food poisoning worldwide. Despite the availability of established culturing and molecular techniques, due to the fastidious nature of these microorganisms, simultaneous detection and species differentiation still remains challenging. This study focused on the differentiation of eleven Campylobacter strains from six species, using Fourier transform infrared (FT-IR) and Raman spectroscopies, together with matrix-assisted laser desorption ionisation-time of flight-mass spectrometry (MALDI-TOF-MS), as physicochemical approaches for generating biochemical fingerprints. Cluster analysis of data from each of the three analytical approaches provided clear differentiation of each Campylobacter species, which was generally in agreement with a phylogenetic tree based on 16S rRNA gene sequences. Notably, although C. fetus subspecies fetus and venerealis are phylogenetically very closely related, using FT-IR and MALDI-TOF-MS data these subspecies were readily differentiated based on differences in the lipid (2920 and 2851 cm(-1)) and fingerprint regions (1500-500 cm(-1)) of the FT-IR spectra, and the 500-2000 m/z region of the MALDI-TOF-MS data. A finding that was further investigated with targeted lipidomics using liquid chromatography-mass spectrometry (LC-MS). Our results demonstrate that such metabolomics approaches combined with molecular biology techniques may provide critical information and knowledge related to the risk factors, virulence, and understanding of the distribution and transmission routes associated with different strains of foodborne Campylobacter spp.

An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

PubMed

Ruiz-Aracama, Ainhoa; Peijnenburg, Ad; Kleinjans, Jos; Jennen, Danyel; van Delft, Joost; Hellfrisch, Caroline; Lommen, Arjen

2011-05-20

In vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied in vitro but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on in vitro systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the in vitro model system and model toxicant, respectively. The study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD. Untargeted profiling of the polar and apolar metabolites of in vitro cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.

Stable isotope-resolved metabolomics and applications for drug development

PubMed Central

Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

2012-01-01

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

Chemical derivatization for enhancing sensitivity during LC/ESI-MS/MS quantification of steroids in biological samples: a review.

PubMed

Higashi, Tatsuya; Ogawa, Shoujiro

2016-09-01

Sensitive and specific methods for the detection, characterization and quantification of endogenous steroids in body fluids or tissues are necessary for the diagnosis, pathological analysis and treatment of many diseases. Recently, liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) has been widely used for these purposes due to its specificity and versatility. However, the ESI efficiency and fragmentation behavior of some steroids are poor, which lead to a low sensitivity. Chemical derivatization is one of the most effective methods to improve the detection characteristics of steroids in ESI-MS/MS. Based on this background, this article reviews the recent advances in chemical derivatization for the trace quantification of steroids in biological samples by LC/ESI-MS/MS. The derivatization in ESI-MS/MS is based on tagging a proton-affinitive or permanently charged moiety on the target steroid. Introduction/formation of a fragmentable moiety suitable for the selected reaction monitoring by the derivatization also enhances the sensitivity. The stable isotope-coded derivatization procedures for the steroid analysis are also described. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes.

PubMed

Tulipani, Sara; Palau-Rodriguez, Magali; Miñarro Alonso, Antonio; Cardona, Fernando; Marco-Ramell, Anna; Zonja, Bozo; Lopez de Alda, Miren; Muñoz-Garach, Araceli; Sanchez-Pla, Alejandro; Tinahones, Francisco J; Andres-Lacueva, Cristina

2016-12-01

Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified into four sex-matched groups by their BMI [non-obese versus morbid obese] and the increased risk of developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] was analyzed by LC- and FIA-ESI-MS/MS-driven metabolomic approaches. Altered levels of [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: R=-0.56, p=0.0003; lysoPC C18:1: R=-0.61, p=0.0001; lysoPC C18:2 R=-0.64, p<0.0001]. Several amino acids were biomarkers of risk of diabetes onset associated to obesity. For instance, glutamate significantly associated with fasting insulin [R=0.5, p=0.0019] and HOMA-IR [R=0.46, p=0.0072], while glycine showed negative associations [fasting insulin: R=-0.51, p=0.0017; HOMA-IR: R=-0.49, p=0.0033], and the branched chain amino acid valine associated to prediabetes and insulin resistance in a BMI-independent manner [fasting insulin: R=0.37, p=0.0479; HOMA-IR: R=0.37, p=0.0468]. Minority sphingolipids including specific [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, hence deserving attention as potential targets for early diagnosis or therapeutic intervention. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrated metabolomic profiling of hepatocellular carcinoma in hepatitis C cirrhosis through GC/MS and UPLC/MS-MS.

PubMed

Fitian, Asem I; Nelson, David R; Liu, Chen; Xu, Yiling; Ararat, Miguel; Cabrera, Roniel

2014-10-01

The metabolic pathway disturbances associated with hepatocellular carcinoma (HCC) remain unsatisfactorily characterized. Determination of the metabolic alterations associated with the presence of HCC can improve our understanding of the pathophysiology of this cancer and may provide opportunities for improved disease monitoring of patients at risk for HCC development. To characterize the global metabolic alterations associated with HCC arising from hepatitis C (HCV)-associated cirrhosis using an integrated non-targeted metabolomics methodology employing both gas chromatography/mass spectrometry (GC/MS) and ultrahigh-performance liquid chromatography/electrospray ionization tandem mass spectrometry (UPLC/MS-MS). The global serum metabolomes of 30 HCC patients, 27 hepatitis C cirrhosis disease controls and 30 healthy volunteers were characterized using a metabolomics approach that combined two metabolomics platforms, GC/MS and UPLC/MS-MS. Random forest, multivariate statistics and receiver operator characteristic analysis were performed to identify the most significantly altered metabolites in HCC patients vs. HCV-cirrhosis controls and which therefore exhibited a close association with the presence of HCC. Elevated 12-hydroxyeicosatetraenoic acid (12-HETE), 15-HETE, sphingosine, γ-glutamyl oxidative stress-associated metabolites, xanthine, amino acids serine, glycine and aspartate, and acylcarnitines were strongly associated with the presence of HCC. Elevations in bile acids and dicarboxylic acids were highly correlated with cirrhosis. Integrated metabolomic profiling through GC/MS and UPLC/MS-MS identified global metabolic disturbances in HCC and HCV-cirrhosis. Aberrant amino acid biosynthesis, cell turnover regulation, reactive oxygen species neutralization and eicosanoid pathways may be hallmarks of HCC. Aberrant dicarboxylic acid metabolism, enhanced bile acid metabolism and elevations in fibrinogen cleavage peptides may be signatures of cirrhosis. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Combination of liquid chromatography-Fourier transform ion cyclotron resonance-mass spectrometry with 13C-labeling for chemical assignment of sulfur-containing metabolites in onion bulbs.

PubMed

Nakabayashi, Ryo; Sawada, Yuji; Yamada, Yutaka; Suzuki, Makoto; Hirai, Masami Yokota; Sakurai, Tetsuya; Saito, Kazuki

2013-02-05

Phytochemicals containing heteroatoms (N, O, S, and halogens) often have biological activities that are beneficial to humans. Although targeted profiling methods for such phytochemicals are expected to contribute to rapid chemical assignments, thus making phytochemical genomics and crop breeding much more efficient, there are few profiling methods for the metabolites. Here, as an ultrahigh performance approach, we propose a practical profiling method for S-containing metabolites (S-omics) using onions (Allium cepa) as a representative species and (12)C- and (13)C-based mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analyses by liquid chromatography-Fourier transform ion cyclotron resonance-mass spectrometry (LC-FTICR-MS). Use of the ultrahigh quality data from FTICR-MS enabled simplifying the previous methods to determine specific elemental compositions. MS analysis with a resolution of >250,000 full width at half-maximum and a mass accuracy of <1 ppm can distinguish S-containing monoisotopic ions from other ions on the basis of the natural abundance of (32)S and (34)S and the mass differences among the S isotopes. Comprehensive peak picking using the theoretical mass difference (1.99579 Da) between (32)S-containing monoisotopic ions and their (34)S-substituted counterparts led to the assignment of 67 S-containing monoisotopic ions from the (12)C-based MS spectra, which contained 4693 chromatographic ions. The unambiguous elemental composition of 22 ions was identified through comparative analysis of the (12)C- and (13)C-based MS spectra. Finally, of these, six ions were found to be derived from S-alk(en)ylcysteine sulfoxides and glutathione derivatives. This S-atom-driven approach afforded an efficient chemical assignment of S-containing metabolites, suggesting its potential application for screening not only S but also other heteroatom-containing metabolites in MS-based metabolomics.

Metabolomic profiling of the heart during acute ischemic preconditioning reveals a role for SIRT1 in rapid cardioprotective metabolic adaptation.

PubMed

Nadtochiy, Sergiy M; Urciuoli, William; Zhang, Jimmy; Schafer, Xenia; Munger, Joshua; Brookes, Paul S

2015-11-01

Ischemic preconditioning (IPC) protects tissues such as the heart from prolonged ischemia-reperfusion (IR) injury. We previously showed that the lysine deacetylase SIRT1 is required for acute IPC, and has numerous metabolic targets. While it is known that metabolism is altered during IPC, the underlying metabolic regulatory mechanisms are unknown, including the relative importance of SIRT1. Thus, we sought to test the hypothesis that some of the metabolic adaptations that occur in IPC may require SIRT1 as a regulatory mediator. Using both ex-vivo-perfused and in-vivo mouse hearts, LC-MS/MS based metabolomics and (13)C-labeled substrate tracing, we found that acute IPC altered several metabolic pathways including: (i) stimulation of glycolysis, (ii) increased synthesis of glycogen and several amino acids, (iii) increased reduced glutathione levels, (iv) elevation in the oncometabolite 2-hydroxyglutarate, and (v) inhibition of fatty-acid dependent respiration. The majority (83%) of metabolic alterations induced by IPC were ablated when SIRT1 was acutely inhibited with splitomicin, and a principal component analysis revealed that metabolic changes in response to IPC were fundamentally different in nature when SIRT1 was inhibited. Furthermore, the protective benefit of IPC was abrogated by eliminating glucose from perfusion media while sustaining normal cardiac function by burning fat, thus indicating that glucose dependency is required for acute IPC. Together, these data suggest that SIRT1 signaling is required for rapid cardioprotective metabolic adaptation in acute IPC. Copyright © 2015 Elsevier Ltd. All rights reserved.

A metabolomic study on high-risk stroke patients determines low levels of serum lysine metabolites: a retrospective cohort study.

PubMed

Lee, Yeseung; Khan, Adnan; Hong, Seri; Jee, Sun Ha; Park, Youngja H

2017-05-30

Identifying changes in serum metabolites during cerebral ischemia is an important approach for early diagnosis of thrombotic stroke. Herein, we highlight novel biomarkers for early diagnosis of patients at high risk of thrombotic stroke using high resolution metabolomics (HRM). In this retrospective cohort study, serum samples obtained from patients at risk of thrombotic stroke (n  =  62) and non-risk individuals (n  =  348) were tested using HRM, coupled with LC-MS/MS, to discriminate between metabolic profiles of control and stroke risk patients. Multivariate analysis and orthogonal partial least square-discriminant analysis (OPLS-DA) were performed to determine the top 5% metabolites within 95% group identities, followed by filtering with p-value <0.05 and annotating significant metabolites using a Metlin database. Mapping identified features from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Mummichog resulted in 341 significant features based on OPLS-DA with p-value <0.05. Among these 341 features, nine discriminated the thrombotic stroke risk group from the control group: low levels of N 6 -acetyl-l-lysine, 5-aminopentanoate, cadaverine, 2-oxoglutarate, nicotinamide, l-valine, S-(2-methylpropionyl)-dihydrolipoamide-E and ubiquinone, and elevated levels of homocysteine sulfinic acid. Further analysis showed that these metabolite biomarkers are specifically related to stroke occurrence, and unrelated to other factors such as diabetes or smoking. Lower levels of lysine catabolites in thrombotic stroke risk patients, as compared to the control, supports targeting these compounds as novel biomarkers for early and non-invasive detection of a thrombotic stroke.

Identification and Characterization of Human Proteoforms by Top-Down LC-21 Tesla FT-ICR Mass Spectrometry.

PubMed

Anderson, Lissa C; DeHart, Caroline J; Kaiser, Nathan K; Fellers, Ryan T; Smith, Donald F; Greer, Joseph B; LeDuc, Richard D; Blakney, Greg T; Thomas, Paul M; Kelleher, Neil L; Hendrickson, Christopher L

2017-02-03

Successful high-throughput characterization of intact proteins from complex biological samples by mass spectrometry requires instrumentation capable of high mass resolving power, mass accuracy, sensitivity, and spectral acquisition rate. These limitations often necessitate the performance of hundreds of LC-MS/MS experiments to obtain reasonable coverage of the targeted proteome, which is still typically limited to molecular weights below 30 kDa. The National High Magnetic Field Laboratory (NHMFL) recently installed a 21 T FT-ICR mass spectrometer, which is part of the NHMFL FT-ICR User Facility and available to all qualified users. Here we demonstrate top-down LC-21 T FT-ICR MS/MS of intact proteins derived from human colorectal cancer cell lysate. We identified a combined total of 684 unique protein entries observed as 3238 unique proteoforms at a 1% false discovery rate, based on rapid, data-dependent acquisition of collision-induced and electron-transfer dissociation tandem mass spectra from just 40 LC-MS/MS experiments. Our identifications included 372 proteoforms with molecular weights over 30 kDa detected at isotopic resolution, which substantially extends the accessible mass range for high-throughput top-down LC-MS/MS.

Characterization of Differential Cocaine Metabolism in Mouse and Rat through Metabolomics-Guided Metabolite Profiling

PubMed Central

Yao, Dan; Shi, Xiaolei; Wang, Lei; Gosnell, Blake A.

2013-01-01

Rodent animal models have been widely used for studying neurologic and toxicological events associated with cocaine abuse. It is known that the mouse is more susceptible to cocaine-induced hepatotoxicity (CIH) than the rat. However, the causes behind this species-dependent sensitivity to cocaine have not been elucidated. In this study, cocaine metabolism in the mouse and rat was characterized through LC-MS-based metabolomic analysis of urine samples and were further compared through calculating the relative abundance of individual cocaine metabolites. The results showed that the levels of benzoylecgonine, a major cocaine metabolite from ester hydrolysis, were comparable in the urine from the mice and rats treated with the same dose of cocaine. However, the levels of the cocaine metabolites from oxidative metabolism, such as N-hydroxybenzoylnorecgonine and hydroxybenzoylecgonine, differed dramatically between the two species, indicating species-dependent cocaine metabolism. Subsequent structural analysis through accurate mass analysis and LC-MS/MS fragmentation revealed that N-oxidation reactions, including N-demethylation and N-hydroxylation, are preferred metabolic routes in the mouse, while extensive aryl hydroxylation reactions occur in the rat. Through stable isotope tracing and in vitro enzyme reactions, a mouse-specific α-glucoside of N-hydroxybenzoylnorecgonine and a group of aryl hydroxy glucuronides high in the rat were identified and structurally elucidated. The differences in the in vivo oxidative metabolism of cocaine between the two rodent species were confirmed by the in vitro microsomal incubations. Chemical inhibition of P450 enzymes further revealed that different P450-mediated oxidative reactions in the ecgonine and benzoic acid moieties of cocaine contribute to the species-dependent biotransformation of cocaine. PMID:23034697

Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

PubMed

Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

2016-08-18

A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (<7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed that incorporation of scan-level features have the potential to lead to more accurate purification results by alleviating the loss in information as a result of integrating peaks. We believe cancer biomarker discovery studies that use mass spectrometric analysis of human biospecimens can greatly benefit from topic model-based purification of the data prior to statistical and pathway analyses.

A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

PubMed Central

Zou, Wei; She, Jianwen; Tolstikov, Vladimir V.

2013-01-01

Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC), reversed-phase liquid chromatography (RP–LC), and gas chromatography (GC). All three techniques are coupled to a mass spectrometer (MS) in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM) and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow. PMID:24958150

Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

PubMed

Thonusin, Chanisa; IglayReger, Heidi B; Soni, Tanu; Rothberg, Amy E; Burant, Charles F; Evans, Charles R

2017-11-10

In recent years, mass spectrometry-based metabolomics has increasingly been applied to large-scale epidemiological studies of human subjects. However, the successful use of metabolomics in this context is subject to the challenge of detecting biologically significant effects despite substantial intensity drift that often occurs when data are acquired over a long period or in multiple batches. Numerous computational strategies and software tools have been developed to aid in correcting for intensity drift in metabolomics data, but most of these techniques are implemented using command-line driven software and custom scripts which are not accessible to all end users of metabolomics data. Further, it has not yet become routine practice to assess the quantitative accuracy of drift correction against techniques which enable true absolute quantitation such as isotope dilution mass spectrometry. We developed an Excel-based tool, MetaboDrift, to visually evaluate and correct for intensity drift in a multi-batch liquid chromatography - mass spectrometry (LC-MS) metabolomics dataset. The tool enables drift correction based on either quality control (QC) samples analyzed throughout the batches or using QC-sample independent methods. We applied MetaboDrift to an original set of clinical metabolomics data from a mixed-meal tolerance test (MMTT). The performance of the method was evaluated for multiple classes of metabolites by comparison with normalization using isotope-labeled internal standards. QC sample-based intensity drift correction significantly improved correlation with IS-normalized data, and resulted in detection of additional metabolites with significant physiological response to the MMTT. The relative merits of different QC-sample curve fitting strategies are discussed in the context of batch size and drift pattern complexity. Our drift correction tool offers a practical, simplified approach to drift correction and batch combination in large metabolomics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Determination of formetanate hydrochloride in fruit samples using liquid chromatography-mass selective detection or -tandem mass spectrometry.

PubMed

Podhorniak, Lynda V; Kamel, Alaa; Rains, Diane M

2010-05-26

A rapid multiresidue method that captures residues of the insecticide formetanate hydrochloride (FHCl) in selected fruits is described. The method was used to provide residue data for dietary exposure determinations of FHCl. Using an acetonitrile extraction with a dispersive cleanup based on AOAC International method 2007.01, also known as QuEChERS, which was further modified and streamlined, thousands of samples were successfully analyzed for FHCl residues. FHCl levels were determined both by liquid chromatography-single-stage mass spectrometry (LC-MS) and ultraperformance liquid chromatography (UPLC)-tandem mass spectrometry (LC-MS/MS). The target limit of detection (LOD) and the limit of quantitation (LOQ) achieved for FHCl were 3.33 and 10 ng/g, respectively, with LC-MS and 0.1 and 0.3 ng/g, respectively, with LC-MS/MS. Recoveries at these previously unpublished levels ranged from 95 to 109%. A set of 20-40 samples can be prepared in one working day by two chemists.

A metabolomics-based approach identifies changes in the small molecular weight compound composition of the peanut as a result of dry-roasting.

PubMed

Klevorn, Claire M; Dean, Lisa L

2018-02-01

Raw peanuts in the USA are subjected to thermal processing, such as dry-roasting, prior to consumption. A multi-instrument metabolomics-based platform along with targeted analyses was used to determine changes in the low-molecular-weight compound composition of peanuts due to dry-roasting. Runner and virginia-type peanut seeds were characterized using several analytical platforms including (RP)/UPLC-MS/MS (positive and negative ion mode ESI) and HILIC/UPLC-MS/MS with negative ion mode ESI. Of the 383 compounds identified, 16 compounds were unique to the roasted peanuts. Using pathway analysis, compounds associated with arginine and proline metabolism were found to be the most changed. Products of chemical degradation and compounds contained within the vesicular bodies of the peanut increased after roasting. Dry-roasting had a significant impact on the levels and types of low-molecular-weight compounds present. These findings provide useful information about composition changes due to roasting. Published by Elsevier Ltd.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

PubMed Central

Lv, Haitao; Palacios, Gustavo; Hartil, Kirsten; Kurland, Irwin J.

2014-01-01

In this study a UPLC-tandem (Waters Xevo TQ) MRM based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice; including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a “fingerprint” characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples. PMID:21322650

Serum metabolic profiling study of lung cancer using ultra high performance liquid chromatography/quadrupole time-of-flight mass spectrometry.

PubMed

Li, Yanjie; Song, Xue; Zhao, Xinjie; Zou, Lijuan; Xu, Guowang

2014-09-01

Lung cancer is currently the leading cause of cancer-related mortality worldwide. It is, therefore, important to enhance understanding and add a new auxiliary detection tool of lung cancer. In this work, serum metabolic characteristics of lung cancer were investigated with a non-targeted metabolomics method. The metabolic profiling of 23 patients with lung cancer and 23 healthy controls were analyzed using ultra high performance liquid chromatography/quadrupole time of flight mass spectrometry (UPLC/Q-TOF MS). Partial least squares discriminant analysis (PLS-DA) model of the metabolic data allowed the clear separation of the lung cancer patients from the healthy controls. In total, 27 differential metabolites were identified, which were mostly related to the perturbation of lipid metabolism, including choline, free fatty acids, lysophosphatidylcholines, etc. Choline and linoleic acid were defined as one combinational biomarker using binary logistic regression, which was supported by the validation with a smaller sample-set (9 patients and 9 healthy controls). These findings show that LC/MS-based serum metabolic profiling has potential application in complementary identification of lung cancer patients, and could be a powerful tool for cancer research. Copyright © 2014 Elsevier B.V. All rights reserved.

Comprehensive analysis of the tryptophan metabolome in urine of patients with acute intermittent porphyria.

PubMed

Gomez-Gomez, Alex; Marcos, Josep; Aguilera, Paula; To-Figueras, Jordi; Pozo, Oscar J

2017-08-15

Acute intermittent porphyria (AIP) is a rare metabolic disorder due to a deficiency of porphobilinogen deaminase, the third enzyme of the heme biosynthetic pathway. This low enzymatic activity may predispose to the appearance of acute neurological attacks. Seminal studies suggested that AIP was associated with changes in tryptophan homeostasis with inconclusive results. Therefore, the aim of this study was to analyze the urinary metabolome of AIP patients focusing on tryptophan metabolism using state-of-the-art technology. This was a case-control study including a group of 25 AIP patients with active biochemical disease and increased excretion of heme-precursors and 25 healthy controls. Tryptophan and related compounds and metabolites including: large neutral amino acids (LNAAs), serotonin, kynurenine, kynurenic acid and anthranilic acid were quantified in urine by liquid chromatography tandem-mass spectrometry (LC-MS/MS). Twenty-nine biological markers (including metabolic ratios and absolute concentrations) were compared between patients and controls. Significant differences were found in the tryptophan-kynurenine metabolic pathway. Compared to controls, AIP patients showed: (a) increased urinary excretion of kynurenine and anthranilic acid (P<0.005); (b): elevation of the kynurenine/tryptophan ratio (P<0.001) and (c): decrease of the kynurenic acid/kynurenine ratio (P=0.001). In contrast, no differences were found in the serotonin metabolic pathway independently of the markers and ratios used. The results of the study demonstrate that there is an imbalance in the kynurenine metabolic pathway in AIP patients, with an increase of the kynurenine/tryptophan ratio in urine and a reduction of the kynurenic acid/kynurenine ratio. The modified ratios suggest induction of indoleamine 2,3-deoxygenase and decreased activity of kynurenine aminotransferase in the liver. The results confirm that LC-MS/MS is useful for the characterization of the urinary metabolome of hepatic porphyrias. Copyright © 2017. Published by Elsevier B.V.

Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bingol, Kerem

Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome manual absolute quantitation step of metabolites in 1D 1H NMR spectra. This provides more consistency between inter-laboratory comparisons. Integration of 2D NMR metabolomics databases under a unified web server allowed very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMRmore » and mass spectrometry. These hybrid NMR/MS approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing to profile ever larger number of metabolites in application studies.« less

Validation of metabolomics analysis of human perilymph fluid using liquid chromatography-mass spectroscopy.

PubMed

Mavel, Sylvie; Lefèvre, Antoine; Bakhos, David; Dufour-Rainfray, Diane; Blasco, Hélène; Emond, Patrick

2018-05-22

Although there is some data from animal studies, the metabolome of inner ear fluid in humans remains unknown. Characterization of the metabolome of the perilymph would allow for better understanding of its role in auditory function and for identification of biomarkers that might allow prediction of response to therapeutics. There is a major technical challenge due to the small sample of perilymph fluid available for analysis (sub-microliter). The objectives of this study were to develop and validate a methodology for analysis of perilymph metabolome using liquid chromatography-high resolution mass spectrometry (LC-HRMS). Due to the low availability of perilymph fluid; a methodological study was first performed using low volumes (0.8 μL) of cerebrospinal fluid (CSF) and optimized the LC-HRMS parameters using targeted and non-targeted metabolomics approaches. We obtained excellent parameters of reproducibility for about 100 metabolites. This methodology was then used to analyze perilymph fluid using two complementary chromatographic supports: reverse phase (RP-C18) and hydrophilic interaction liquid chromatography (HILIC). Both methods were highly robust and showed their complementarity, thus reinforcing the interest to combine these chromatographic supports. A fingerprinting was obtained from 98 robust metabolites (analytical variability <30%), where amino acids (e.g., asparagine, valine, glutamine, alanine, etc.), carboxylic acids and derivatives (e.g., lactate, carnitine, trigonelline, creatinine, etc.) were observed as first-order signals. This work lays the foundations of a robust analytical workflow for the exploration of the perilymph metabolome dedicated to the research of biomarkers for the diagnosis/prognosis of auditory pathologies. Copyright © 2018 Elsevier B.V. All rights reserved.

The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics.

PubMed

Gong, Zhi-Gang; Hu, Jing; Wu, Xi; Xu, Yong-Jiang

2017-07-04

Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

Exploring natural variation of Pinus pinaster Aiton using metabolomics: Is it possible to identify the region of origin of a pine from its metabolites?

PubMed

Meijón, Mónica; Feito, Isabel; Oravec, Michal; Delatorre, Carolina; Weckwerth, Wolfram; Majada, Juan; Valledor, Luis

2016-02-01

Natural variation of the metabolome of Pinus pinaster was studied to improve understanding of its role in the adaptation process and phenotypic diversity. The metabolomes of needles and the apical and basal section of buds were analysed in ten provenances of P. pinaster, selected from France, Spain and Morocco, grown in a common garden for 5 years. The employment of complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) together with bioinformatics tools allowed the reliable quantification of 2403 molecular masses. The analysis of the metabolome showed that differences were maintained across provenances and that the metabolites characteristic of each organ are mainly related to amino acid metabolism, while provenances were distinguishable essentially through secondary metabolism when organs were analysed independently. Integrative analyses of metabolome, environmental and growth data provided a comprehensive picture of adaptation plasticity in conifers. These analyses defined two major groups of plants, distinguished by secondary metabolism: that is, either Atlantic or Mediterranean provenance. Needles were the most sensitive organ, where strong correlations were found between flavonoids and the water regime of the geographic origin of the provenance. The data obtained point to genome specialization aimed at maximizing the drought stress resistance of trees depending on their origin. © 2016 John Wiley & Sons Ltd.

Development of an LC-MS based enzyme activity assay for MurC: application to evaluation of inhibitors and kinetic analysis.

PubMed

Deng, Gejing; Gu, Rong-Fang; Marmor, Stephen; Fisher, Stewart L; Jahic, Haris; Sanyal, Gautam

2004-06-29

An enzyme activity assay, based on mass spectrometric (MS) detection of specific reaction product following HPLC separation, has been developed to evaluate pharmaceutical hits identified from primary high throughput screening (HTS) against target enzyme Escherichia coli UDP-N-acetyl-muramyl-L-alanine ligase (MurC), an essential enzyme in the bacterial peptidoglycan biosynthetic pathway, and to study the kinetics of the enzyme. A comparative analysis of this new liquid chromatographic-MS (LC-MS) based assay with a conventional spectrophotometric Malachite Green (MG) assay, which detects phosphate produced in the reaction, was performed. The results demonstrated that the LC-MS assay, which determines specific ligase activity of MurC, offers several advantages including a lower background (0.2% versus 26%), higher sensitivity (> or = 10 fold), lower limit of quantitation (LOQ) (0.02 microM versus 1 microM) and wider linear dynamic range (> or = 4 fold) than the MG assay. Good precision for the LC-MS assay was demonstrated by the low intraday and interday coefficient of variation (CV) values (3 and 6%, respectively). The LC-MS assay, free of the artifacts often seen in the Malachite Green assay, offers a valuable secondary assay for hit evaluation in which the false positives from the primary high throughput screening can be eliminated. In addition, the applicability of this assay to the study of enzyme kinetics has also been demonstrated. Copyright 2004 Elsevier B.V.

Urine Multi-drug Screening with GC-MS or LC-MS-MS Using SALLE-hybrid PPT/SPE.

PubMed

Lee, Junhui; Park, Jiwon; Go, Ahra; Moon, Heesung; Kim, Sujin; Jung, Sohee; Jeong, Wonjoon; Chung, Heesun

2018-05-14

To intoxicated patients in the emergency room, toxicological analysis can be considerably helpful for identifying the involved toxicants. In order to develop a urine multi-drug screening (UmDS) method, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS-MS) were used to determine targeted and unknown toxicants in urine. A GC-MS method in scan mode was validated for selectivity, limit of detection (LOD) and recovery. An LC-MS-MS multiple reaction monitoring (MRM) method was validated for lower LOD, recovery and matrix effect. The results of the screening analysis were compared with patient medical records to check the reliability of the screen. Urine samples collected from an emergency room were extracted through a combination of salting-out assisted liquid-liquid extraction (SALLE) and hybrid protein precipitation/solid phase extraction (hybrid PPT/SPE) plates and examined by GC-MS and LC-MS-MS. GC-MS analysis was performed as unknown drug screen and LC-MS-MS analysis was conducted as targeted drug screen. After analysis by GC-MS, a library search was conducted using an in-house library established with the automated mass spectral deconvolution and identification system (AMDISTM). LC-MS-MS used Cliquid®2.0 software for data processing and acquisition in MRM mode. An UmDS method by GC-MS and LC-MS-MS was developed by using a SALLE-hybrid PPT/SPE and in-house library. The results of UmDS by GC-MS and LC-MS-MS showed that toxicants could be identified from 185 emergency room patient samples containing unknown toxicants. Zolpidem, acetaminophen and citalopram were the most frequently encountered drugs in emergency room patients. The UmDS analysis developed in this study can be used effectively to detect toxic substances in a short time. Hence, it could be utilized in clinical and forensic toxicology practices.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

PubMed

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata , identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata , with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata , as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

PubMed Central

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature. PMID:29719546

MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing.

PubMed

Lommen, Arjen

2009-04-15

Hyphenated full-scan MS technology creates large amounts of data. A versatile easy to handle automation tool aiding in the data analysis is very important in handling such a data stream. MetAlign softwareas described in this manuscripthandles a broad range of accurate mass and nominal mass GC/MS and LC/MS data. It is capable of automatic format conversions, accurate mass calculations, baseline corrections, peak-picking, saturation and mass-peak artifact filtering, as well as alignment of up to 1000 data sets. A 100 to 1000-fold data reduction is achieved. MetAlign software output is compatible with most multivariate statistics programs.

Development of High-Performance Chemical Isotope Labeling LC-MS for Profiling the Carbonyl Submetabolome.

PubMed

Zhao, Shuang; Dawe, Margot; Guo, Kevin; Li, Liang

2017-06-20

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential 12 C- and 13 C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with 12 C-labeling and spiked with a 13 C-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 12 C-/ 13 C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that 12 C-/ 13 C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.

A harmonized immunoassay with liquid chromatography-mass spectrometry analysis in egg allergen determination.

PubMed

Nimata, Masaomi; Okada, Hideki; Kurihara, Kei; Sugimoto, Tsukasa; Honjoh, Tsutomu; Kuroda, Kazuhiko; Yano, Takeo; Tachibana, Hirofumi; Shoji, Masahiro

2018-01-01

Food allergy is a serious health issue worldwide. Implementing allergen labeling regulations is extremely challenging for regulators, food manufacturers, and analytical kit manufacturers. Here we have developed an "amino acid sequence immunoassay" approach to ELISA. The new ELISA comprises of a monoclonal antibody generated via an analyte specific peptide antigen and sodium lauryl sulfate/sulfite solution. This combination enables the antibody to access the epitope site in unfolded analyte protein. The newly developed ELISA recovered 87.1%-106.4% ovalbumin from ovalbumin-incurred model processed foods, thereby demonstrating its applicability as practical egg allergen determination. Furthermore, the comparison of LC-MS/MS and the new ELISA, which targets the amino acid sequence conforming to the LC-MS/MS detection peptide, showed a good agreement. Consequently the harmonization of two methods was demonstrated. The complementary use of the new ELISA and LC-MS analysis can offer a wide range of practical benefits in terms of easiness, cost, accuracy, and efficiency in food allergen analysis. In addition, the new assay is attractive in respect to its easy antigen preparation and predetermined specificity. Graphical abstract The ELISA composing of the monoclonal antibody targeting the amino acid sequence conformed to LC-MS detection peptide, and the protein conformation unfolding reagent was developed. In ovalbumin determination, the developed ELISA showed a good agreement with LC-MS analysis. Consequently the harmonization of immunoassay with LC-MS analysis by using common target amino acid sequence was demonstrated.

Distinct urine metabolome after Asian ginseng and American ginseng intervention based on GC-MS metabolomics approach

PubMed Central

Yang, Liu; Yu, Qing-Tao; Ge, Ya-Zhong; Zhang, Wen-Song; Fan, Yong; Ma, Chung-Wah; Liu, Qun; Qi, Lian-Wen

2016-01-01

Ginseng occupies a prominent position in the list of best-selling natural products worldwide. Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius) show different properties and medicinal applications in pharmacology, even though the main active constituents of them are both thought to be ginsenosides. Metabolomics is a promising method to profile entire endogenous metabolites and monitor their fluctuations related to exogenous stimulus. Herein, an untargeted metabolomics approach was applied to study the overall urine metabolic differences between Asian ginseng and American ginseng in mice. Metabolomics analyses were performed using gas chromatography-mass spectrometry (GC-MS) together with multivariate statistical data analysis. A total of 21 metabolites related to D-glutamine and D-glutamate metabolism, glutathione metabolism, TCA cycle and glyoxylate and dicarboxylate metabolism, differed significantly under the Asian ginseng treatment; 34 metabolites mainly associated with glyoxylate and dicarboxylate metabolism, TCA cycle and taurine and hypotaurine metabolism, were significantly altered after American ginseng treatment. Urinary metabolomics reveal that Asian ginseng and American ginseng can benefit organism physiological and biological functions via regulating multiple metabolic pathways. The important pathways identified from Asian ginseng and American ginseng can also help to explore new therapeutic effects or action targets so as to broad application of these two ginsengs. PMID:27991533

Bisphenol A alters n-6 fatty acid composition and decreases antioxidant enzyme levels in rat testes: a LC-QTOF-based metabolomics study.

PubMed

Chen, Minjian; Xu, Bin; Ji, Wenliang; Qiao, Shanlei; Hu, Nan; Hu, Yanhui; Wu, Wei; Qiu, Lianglin; Zhang, Ruyang; Wang, Yubang; Wang, Shoulin; Zhou, Zuomin; Xia, Yankai; Wang, Xinru

2012-01-01

Male reproductive toxicity induced by exposure to bisphenol A (BPA) has been widely reported. The testes have proven to be a major target organ of BPA toxicity, so studying testicular metabolite variation holds promise for the discovery of mechanisms linked to the toxic effects of BPA on reproduction. Male Sprague-Dawley rats were orally administered doses of BPA at the levels of 0, 50 mg/kg/d for 8 weeks. We used an unbiased liquid chromatography-quadrupole time-of-flight (LC-QTOF)-based metabolomics approach to discover, identify, and analyze the variation of testicular metabolites. Two n-6 fatty acids, linoleic acid (LA) and arachidonic acid (AA) were identified as potential testicular biomarkers. Decreased levels of LA and increased levels of AA as well as AA/LA ratio were observed in the testes of the exposed group. According to these suggestions, testicular antioxidant enzyme levels were detected. Testicular superoxide dismutase (SOD) declined significantly in the exposed group compared with that in the non-exposed group, and the glutathione peroxidase (GSH-Px) as well as catalase (CAT) also showed a decreasing trend in BPA treated group. BPA caused testicular n-6 fatty acid composition variation and decreased antioxidant enzyme levels. This study emphasizes that metabolomics brings the promise of biomarkers identification for the discovery of mechanisms underlying reproductive toxicity.

Serum Metabolic Profiling of Oocyst-Induced Toxoplasma gondii Acute and Chronic Infections in Mice Using Mass-Spectrometry

PubMed Central

Zhou, Chun-Xue; Cong, Wei; Chen, Xiao-Qing; He, Shen-Yi; Elsheikha, Hany M.; Zhu, Xing-Quan

2018-01-01

Toxoplasma gondii is an obligate intracellular parasite causing severe diseases in immunocompromised individuals and congenitally infected neonates, such as encephalitis and chorioretinitis. This study aimed to determine whether serum metabolic profiling can (i) identify metabolites associated with oocyst-induced T. gondii infection and (ii) detect systemic metabolic differences between T. gondii-infected mice and controls. We performed the first global metabolomics analysis of mice serum challenged with 100 sporulated T. gondii Pru oocysts (Genotype II). Sera from acutely infected mice (11 days post-infection, dpi), chronically infected mice (33 dpi) and control mice were collected and analyzed using LC-MS/MS platform. Following False Discovery Rate filtering, we identified 3871 and 2825 ions in ESI+ or ESI− mode, respectively. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) identified metabolomic profiles that clearly differentiated T. gondii-infected and -uninfected serum samples. Acute infection significantly influenced the serum metabolome. Our results identified common and uniquely perturbed metabolites and pathways. Acutely infected mice showed perturbations in metabolites associated with glycerophospholipid metabolism, biosynthesis of amino acid, and tyrosine metabolism. These findings demonstrated that acute T. gondii infection induces a global perturbation of mice serum metabolome, providing new insights into the mechanisms underlying systemic metabolic changes during early stage of T. gondii infection. PMID:29354104

Orthogonal analytical methods for botanical standardization: Determination of green tea catechins by qNMR and LC-MS/MS

PubMed Central

Napolitano, José G.; Gödecke, Tanja; Lankin, David C.; Jaki, Birgit U.; McAlpine, James B.; Chen, Shao-Nong; Pauli, Guido F.

2013-01-01

The development of analytical methods for parallel characterization of multiple phytoconstituents is essential to advance the quality control of herbal products. While chemical standardization is commonly carried out by targeted analysis using gas or liquid chromatography-based methods, more universal approaches based on quantitative 1H NMR (qHNMR) measurements are being used increasingly in the multi-targeted assessment of these complex mixtures. The present study describes the development of a 1D qHNMR-based method for simultaneous identification and quantification of green tea constituents. This approach utilizes computer-assisted 1H iterative Full Spin Analysis (HiFSA) and enables rapid profiling of seven catechins in commercial green tea extracts. The qHNMR results were cross-validated against quantitative profiles obtained with an orthogonal LC-MS/MS method. The relative strengths and weaknesses of both approaches are discussed, with special emphasis on the role of identical reference standards in qualitative and quantitative analyses. PMID:23870106

MetaboLights: An Open-Access Database Repository for Metabolomics Data.

PubMed

Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

2016-03-24

MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

Non-enzymolytic adenosine barcode-mediated dual signal amplification strategy for ultrasensitive protein detection using LC-MS/MS.

PubMed

Yang, Wen; Li, Tengfei; Shu, Chang; Ji, Shunli; Wang, Lei; Wang, Yan; Li, Duo; Mtalimanja, Michael; Sun, Luning; Ding, Li

2018-05-10

A method is described for the determination of proteins with LC-MS/MS enabled by a small molecule (adenosine) barcode and based on a double-recognition sandwich structure. The coagulation protein thrombin was chosen as the model analyte. Magnetic nanoparticles were functionalized with aptamer29 (MNP/apt29) and used to capture thrombin from the samples. MNP/apt29 forms a sandwich with functionalized gold nanoparticles modified with (a) aptamer15 acting as thrombin-recognizing element and (b) a large number of adenosine as mass barcodes. The sandwich formed (MNP/apt29-thrombin-apt15/AuNP/adenosine) can ben magnetically separated from the sample. Mass barcodes are subsequently released from the sandwiched structure for further analysis by adding 11-mercaptoundecanoic acid. Adenosine is then detected by LC-MS/MS as it reflects the level of thrombin with impressively amplified signal. Numerous adenosines introduced into the sandwich proportional to the target concentration further amplify the signal. Under optimized conditions, the response is linearly proportional to the thrombin concentration in the range of 0.02 nM to 10 nM, with a detection limit of 9 fM. The application of this method to the determination of thrombin in spiked plasma samples gave recoveries that ranged from 92.3% to 104.7%. Graphical abstract Schematic representation of a method for the determination of thrombin with LC-MS/MS. The method is based on a double-recognition sandwiched structure. With LC-MS/MS, mass barcodes (adenosine) are detected to quantify thrombin, which amplifies the detection signal impressively.

Biomarker Discovery Using New Metabolomics Software for Automated Processing of High Resolution LC-MS Data

PubMed Central

Hnatyshyn, S.; Reily, M.; Shipkova, P.; McClure, T.; Sanders, M.; Peake, D.

2011-01-01

Robust biomarkers of target engagement and efficacy are required in different stages of drug discovery. Liquid chromatography coupled to high resolution mass spectrometry provides sensitivity, accuracy and wide dynamic range required for identification of endogenous metabolites in biological matrices. LCMS is widely-used tool for biomarker identification and validation. Typical high resolution LCMS profiles from biological samples may contain greater than a million mass spectral peaks corresponding to several thousand endogenous metabolites. Reduction of the total number of peaks, component identification and statistical comparison across sample groups remains to be a difficult and time consuming challenge. Blood samples from four groups of rats (male vs. female, fully satiated and food deprived) were analyzed using high resolution accurate mass (HRAM) LCMS. All samples were separated using a 15 minute reversed-phase C18 LC gradient and analyzed in both positive and negative ion modes. Data was acquired using 15K resolution and 5ppm mass measurement accuracy. The entire data set was analyzed using software developed in collaboration between Bristol Meyers Squibb and Thermo Fisher Scientific to determine the metabolic effects of food deprivation on rats. Metabolomic LC-MS data files are extraordinarily complex and appropriate reduction of the number of spectral peaks via identification of related peaks and background removal is essential. A single component such as hippuric acid generates more than 20 related peaks including isotopic clusters, adducts and dimers. Plasma and urine may contain 500-1500 unique quantifiable metabolites. Noise filtering approaches including blank subtraction were used to reduce the number of irrelevant peaks. By grouping related signals such as isotopic peaks and alkali adducts, data processing was greatly simplified by reducing the total number of components by 10-fold. The software processes 48 samples in under 60minutes. Principle Component Analysis showed substantial differences in endogenous metabolites levels between the animal groups. Annotation of components was accomplished via searching the ChemSpider database. Tentative assignments made using accurate mass need further verification by comparison with the retention time of authentic standards.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guardiola, John J.

Background: Occupational vinyl chloride (VC) exposures have been associated with toxicant-associated steatohepatitis and liver cancer. Metabolomics has been used to clarify mode of action in drug-induced liver injury but has not been performed following VC exposures. Methods: Plasma samples from 17 highly exposed VC workers without liver cancer and 27 unexposed healthy volunteers were obtained for metabolite extraction and GC/MS and LC/MS{sup 2} analysis. Following ion identification/quantification, Ingenuity pathway analysis was performed. Results: 613 unique named metabolites were identified. Of these, 189 metabolites were increased in the VC exposure group while 94 metabolites were decreased. Random Forest analysis indicated thatmore » the metabolite signature could separate the groups with 94% accuracy. VC exposures were associated with increased long chain (including arachidonic acid) and essential (including linoleic acid) fatty acids. Occupational exposure increased lipid peroxidation products including monohydroxy fatty acids (including 13-HODE); fatty acid dicarboxylates; and oxidized arachidonic acid products (including 5,9, and 15-HETE). Carnitine and carnitine esters were decreased, suggesting peroxisomal/mitochondrial dysfunction and alternate modes of lipid oxidation. Differentially regulated metabolites were shown to interact with extracellular-signal-regulated kinase 1/2 (ERK1/2), Akt, AMP-activated protein kinase (AMPK), and the N-Methyl-D-aspartate (NMDA) receptor. The top canonical pathways affected by occupational exposure included tRNA charging, nucleotide degradation, amino acid synthesis/degradation and urea cycle. Methionine and homocysteine was increased with decreased cysteine, suggesting altered 1-carbon metabolism. Conclusions: Occupational exposure generated a distinct plasma metabolome with markedly altered lipid and amino acid metabolites. ERK1/2, Akt, AMPK, and NMDA were identified as protein targets for vinyl chloride toxicity. - Highlights: • Occupational vinyl chloride exposure is linked to toxicant-associated steatohepatitis, liver cancer, and other diseases. • Vinyl chloride exposure led to a distinct plasma metabolome with markedly altered lipid and amino acid metabolites. • A metabolomics approach can provide useful information regarding exposure in chemical workers.« less

A systematic strategy for the identification and determination of pharmaceuticals in environment using advanced LC-MS tools: application to ground water samples.

PubMed

Jindal, Kriti; Narayanam, Mallikarjun; Singh, Saranjit

2015-04-10

In the present study, a novel analytical strategy was employed to study the occurrence of 40 drug residues belonging to different medicinal classes, e.g., antibiotics, β blockers, NSAIDs, antidiabetics, proton pump inhibitors, H2 receptor antagonists, antihypertensives, antihyperlipidemics, etc. in ground water samples collected from villages adjoining to S.A.S. Nagar, Punjab, India. The drug residues were extracted from the samples using solid-phase extraction, and LC-ESI-HRMS and LC-ESI-MS/MS were used for identification and quantitation of the analytes. Initially, qualifier and quantifier MRM transitions were classified for 40 targeted drugs, followed by development of LC-MS methods for the separation of all the drugs, which were divided into three categories to curtail overlapping of peaks. Overall identification was done through matching of retention times and MRM transitions; matching of intensity ratio of qualifier to quantifier transitions; comparison of base peak MS/MS profiles; and evaluation of isotopic abundances (wherever applicable). Final confirmation was carried out through comparison of accurate masses obtained from HRMS studies for both standard and targeted analytes in the samples. The application of the strategy allowed removal of false positives and helped in identification and quantitation of diclofenac in the ground water samples of four villages, and pitavastatin in a sample of one village. Copyright © 2015 Elsevier B.V. All rights reserved.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

PubMed

Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

2016-10-28

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses.

PubMed

Montenegro-Burke, J Rafael; Phommavongsay, Thiery; Aisporna, Aries E; Huan, Tao; Rinehart, Duane; Forsberg, Erica; Poole, Farris L; Thorgersen, Michael P; Adams, Michael W W; Krantz, Gregory; Fields, Matthew W; Northen, Trent R; Robbins, Paul D; Niedernhofer, Laura J; Lairson, Luke; Benton, H Paul; Siuzdak, Gary

2016-10-04

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

PubMed Central

2016-01-01

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism. PMID:27560777

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

DOE PAGES

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.; ...

2016-08-25

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

Brain metabolomic profiling of eastern honey bee (Apis cerana) infested with the mite Varroa destructor.

PubMed

Wu, Jiang-Li; Zhou, Chun-Xue; Wu, Peng-Jie; Xu, Jin; Guo, Yue-Qin; Xue, Fei; Getachew, Awraris; Xu, Shu-Fa

2017-01-01

The mite Varroa destructor is currently the greatest threat to apiculture as it is causing a global decrease in honey bee colonies. However, it rarely causes serious damage to its native hosts, the eastern honey bees Apis cerana. To better understand the mechanism of resistance of A. cerana against the V. destructor mite, we profiled the metabolic changes that occur in the honey bee brain during V. destructor infestation. Brain samples were collected from infested and control honey bees and then measured using an untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based global metabolomics method, in which 7918 and 7462 ions in ESI+ and ESI- mode, respectively, were successfully identified. Multivariate statistical analyses were applied, and 64 dysregulated metabolites, including fatty acids, amino acids, carboxylic acid, and phospholipids, amongst others, were identified. Pathway analysis further revealed that linoleic acid metabolism; propanoate metabolism; and glycine, serine, and threonine metabolism were acutely perturbed. The data obtained in this study offer insight into the defense mechanisms of A. cerana against V. destructor mites and provide a better method for understanding the synergistic effects of parasitism on honey bee colonies.

Brain metabolomic profiling of eastern honey bee (Apis cerana) infested with the mite Varroa destructor

PubMed Central

Wu, Peng-Jie; Xu, Jin; Guo, Yue-Qin; Xue, Fei; Getachew, Awraris; Xu, Shu-Fa

2017-01-01

The mite Varroa destructor is currently the greatest threat to apiculture as it is causing a global decrease in honey bee colonies. However, it rarely causes serious damage to its native hosts, the eastern honey bees Apis cerana. To better understand the mechanism of resistance of A. cerana against the V. destructor mite, we profiled the metabolic changes that occur in the honey bee brain during V. destructor infestation. Brain samples were collected from infested and control honey bees and then measured using an untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based global metabolomics method, in which 7918 and 7462 ions in ESI+ and ESI- mode, respectively, were successfully identified. Multivariate statistical analyses were applied, and 64 dysregulated metabolites, including fatty acids, amino acids, carboxylic acid, and phospholipids, amongst others, were identified. Pathway analysis further revealed that linoleic acid metabolism; propanoate metabolism; and glycine, serine, and threonine metabolism were acutely perturbed. The data obtained in this study offer insight into the defense mechanisms of A. cerana against V. destructor mites and provide a better method for understanding the synergistic effects of parasitism on honey bee colonies. PMID:28403242

iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

PubMed Central

Chang, Hui-Yin; Chen, Ching-Tai; Lih, T. Mamie; Lynn, Ke-Shiuan; Juo, Chiun-Gung; Hsu, Wen-Lian; Sung, Ting-Yi

2016-01-01

Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤0.19) when quantifying the two internal standards and had higher abundance correlation (≥0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html. PMID:26784691

The effect of temperature on the respiration and metabolism of the African burrowing scorpion (Opistophthalmus latimanus).

PubMed

van Aardt, Willie J; le Roux, Jacobus M; Lindeque, Jeremie Z; Mason, Shayne; Louw, Roan

2016-12-01

It is well known that scorpions are highly adapted to thermal temperatures. However, little is known of the metabolic and respiration adaptations caused by temperature fluctuations in these animals. Therefore we used the African burrowing scorpion Opistophthalmus latimanus to measure the effect of temperature on its metabolism and respiration. Radioactive d-glucose was injected into the ventral sinus of the circulatory system and metabolites of d-glucose were determined after six hour incubation at four temperatures (7, 17, 25 and 37°C). The oxygen consumption rate (ṀO 2 ) and carbon dioxide production rate (ṀCO 2 ) were measured simultaneously at 17, 25 and 37°C. The metabolomics investigation included LC-MS, GC-MS and NMR analytical platforms. The average radioactivity recovered after the carbon-14 d-glucose injection, glycogen precipitation and column fractionation at the four temperatures was between 92.4% and 95.0%. Strong acids, CO 2 and neutral compounds all increased with temperature, while glycogen and neutral sugars decreased as the temperature increased. Weak acids initially increased with temperature, then decreased again as the temperature was increased to 37°C. Respiration also gradually increased as the temperature was increased. Metabolomics identified 23 metabolites that were significantly influenced by temperature. Pathway analysis of these metabolites indicated numerous metabolic pathways that were affected by temperature, clearly demonstrating that the scorpion uses proteins, lipids and carbohydrates at higher temperatures to generate energy. However, protein catabolism seems to be the main source of energy at higher temperatures in these animals, although this needs to be confirmed in a more targeted metabolomics study. Copyright © 2016 Elsevier Inc. All rights reserved.

CE-MS for metabolomics: developments and applications in the period 2012-2014.

PubMed

Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

2015-01-01

In the field of metabolomics, CE-MS is now regarded as a useful complementary analytical technique for the profiling of (highly) polar ionogenic metabolites in biological samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolic profiling studies. This paper, which is a follow-up of three previous review papers covering the years 2000-2012 [Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65; Electrophoresis 2013, 34, 86-98], provides an update of these developments covering the scientific literature from July 2012 to June 2014. Attention will be paid to novel interfacing techniques for coupling CE to MS and their implications for metabolomics studies. The potential of CEC-MS and MEKC-MS are also considered, and CE-MS systems for high-throughput metabolic profiling are discussed. The applicability of CE-MS for metabolomics studies is demonstrated by representative examples in the fields of biomedical, clinical, microbial, plant, environmental, and food metabolomics. An overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CE-MS for metabolomics: Developments and applications in the period 2014-2016.

PubMed

Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

2017-01-01

CE-MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolomics studies. In this paper, which is a follow-up of a previous review paper covering the years 2012-2014 (Electrophoresis 2015, 36, 212-224), recent CE-MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE-MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE-MS is also demonstrated. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2016 The Authors ELECTROPHORESIS Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Protocol for an electrospray ionization tandem mass spectral product ion library: development and application for identification of 240 pesticides in foods.

PubMed

Zhang, Kai; Wong, Jon W; Yang, Paul; Hayward, Douglas G; Sakuma, Takeo; Zou, Yunyun; Schreiber, André; Borton, Christopher; Nguyen, Tung-Vi; Kaushik, Banerjee; Oulkar, Dasharath

2012-07-03

Modern determination techniques for pesticides must yield identification quickly with high confidence for timely enforcement of tolerances. A protocol for the collection of liquid chromatography (LC) electrospray ionization (ESI)-quadruple linear ion trap (Q-LIT) mass spectrometry (MS) library spectra was developed. Following the protocol, an enhanced product ion (EPI) library of 240 pesticides was developed by use of spectra collected from two laboratories. A LC-Q-LIT-MS workflow using scheduled multiple reaction monitoring (sMRM) survey scan, information-dependent acquisition (IDA) triggered collection of EPI spectra, and library search was developed and tested to identify the 240 target pesticides in one single LC-Q-LIT MS analysis. By use of LC retention time, one sMRM survey scan transition, and a library search, 75-87% of the 240 pesticides were identified in a single LC/MS analysis at fortified concentrations of 10 ng/g in 18 different foods. A conventional approach with LC-MS/MS using two MRM transitions produced the same identifications and comparable quantitative results with the same incurred foods as the LC-Q-LIT using EPI library search, finding 1.2-49 ng/g of either carbaryl, carbendazim, fenbuconazole, propiconazole, or pyridaben in peaches; carbendazim, imazalil, terbutryn, and thiabendazole in oranges; terbutryn in salmon; and azoxystrobin in ginseng. Incurred broccoli, cabbage, and kale were screened with the same EPI library using three LC-Q-LIT and a LC-quadruple time-of-flight (Q-TOF) instruments. The library search identified azoxystrobin, cyprodinil, fludioxinil, imidacloprid, metalaxyl, spinosyn A, D, and J, amd spirotetramat with each instrument. The approach has a broad application in LC-MS/MS type targeted screening in food analysis.

EU Framework 6 Project: Predictive Toxicology (PredTox)-overview and outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suter, Laura, E-mail: Laura.suter-dick@roche.com; Schroeder, Susanne; Meyer, Kirstin

2011-04-15

In this publication, we report the outcome of the integrated EU Framework 6 Project: Predictive Toxicology (PredTox), including methodological aspects and overall conclusions. Specific details including data analysis and interpretation are reported in separate articles in this issue. The project, partly funded by the EU, was carried out by a consortium of 15 pharmaceutical companies, 2 SMEs, and 3 universities. The effects of 16 test compounds were characterized using conventional toxicological parameters and 'omics' technologies. The three major observed toxicities, liver hypertrophy, bile duct necrosis and/or cholestasis, and kidney proximal tubular damage were analyzed in detail. The combined approach ofmore » 'omics' and conventional toxicology proved a useful tool for mechanistic investigations and the identification of putative biomarkers. In our hands and in combination with histopathological assessment, target organ transcriptomics was the most prolific approach for the generation of mechanistic hypotheses. Proteomics approaches were relatively time-consuming and required careful standardization. NMR-based metabolomics detected metabolite changes accompanying histopathological findings, providing limited additional mechanistic information. Conversely, targeted metabolite profiling with LC/GC-MS was very useful for the investigation of bile duct necrosis/cholestasis. In general, both proteomics and metabolomics were supportive of other findings. Thus, the outcome of this program indicates that 'omics' technologies can help toxicologists to make better informed decisions during exploratory toxicological studies. The data support that hypothesis on mode of action and discovery of putative biomarkers are tangible outcomes of integrated 'omics' analysis. Qualification of biomarkers remains challenging, in particular in terms of identification, mechanistic anchoring, appropriate specificity, and sensitivity.« less

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow.

PubMed

Volani, Chiara; Caprioli, Giulia; Calderisi, Giovanni; Sigurdsson, Baldur B; Rainer, Johannes; Gentilini, Ivo; Hicks, Andrew A; Pramstaller, Peter P; Weiss, Guenter; Smarason, Sigurdur V; Paglia, Giuseppe

2017-10-01

Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. In this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. The latter revealed that prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but if VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months.

Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

PubMed Central

Zordoky, Beshay N.; Sung, Miranda M.; Ezekowitz, Justin; Mandal, Rupasri; Han, Beomsoo; Bjorndahl, Trent C.; Bouatra, Souhaila; Anderson, Todd; Oudit, Gavin Y.; Wishart, David S.; Dyck, Jason R. B.

2015-01-01

Background Heart failure (HF) with preserved ejection fraction (HFpEF) is increasingly recognized as an important clinical entity. Preclinical studies have shown differences in the pathophysiology between HFpEF and HF with reduced ejection fraction (HFrEF). Therefore, we hypothesized that a systematic metabolomic analysis would reveal a novel metabolomic fingerprint of HFpEF that will help understand its pathophysiology and assist in establishing new biomarkers for its diagnosis. Methods and Results Ambulatory patients with clinical diagnosis of HFpEF (n = 24), HFrEF (n = 20), and age-matched non-HF controls (n = 38) were selected for metabolomic analysis as part of the Alberta HEART (Heart Failure Etiology and Analysis Research Team) project. 181 serum metabolites were quantified by LC-MS/MS and 1H-NMR spectroscopy. Compared to non-HF control, HFpEF patients demonstrated higher serum concentrations of acylcarnitines, carnitine, creatinine, betaine, and amino acids; and lower levels of phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins. Medium and long-chain acylcarnitines and ketone bodies were higher in HFpEF than HFrEF patients. Using logistic regression, two panels of metabolites were identified that can separate HFpEF patients from both non-HF controls and HFrEF patients with area under the receiver operating characteristic (ROC) curves of 0.942 and 0.981, respectively. Conclusions The metabolomics approach employed in this study identified a unique metabolomic fingerprint of HFpEF that is distinct from that of HFrEF. This metabolomic fingerprint has been utilized to identify two novel panels of metabolites that can separate HFpEF patients from both non-HF controls and HFrEF patients. Clinical Trial Registration ClinicalTrials.gov NCT02052804 PMID:26010610

Recent advances of liquid chromatography-(tandem) mass spectrometry in clinical and forensic toxicology.

PubMed

Peters, Frank T

2011-01-01

Liquid chromatography (LC) coupled to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) has become increasingly important in clinical and forensic toxicology as well as doping control and is now a robust and reliable technique for routine analysis in these fields. In recent years, methods for LC-MS(/MS)-based systematic toxicological analysis using triple quadrupole or ion trap instruments have been considerably improved and a new screening approach based on high-resolution MS analysis using benchtop time-of-flight MS instruments has been developed. Moreover, many applications for so-called multi-target screening and/or quantification of drugs, poisons, and or their metabolites in various biomatrices have been published. The present paper will provide an overview and discuss these recent developments focusing on the literature published after 2006. Copyright © 2010 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Non-targeted analysis of unexpected food contaminants using LC-HRMS.

PubMed

Kunzelmann, Marco; Winter, Martin; Åberg, Magnus; Hellenäs, Karl-Erik; Rosén, Johan

2018-03-29

A non-target analysis method for unexpected contaminants in food is described. Many current methods referred to as "non-target" are capable of detecting hundreds or even thousands of contaminants. However, they will typically still miss all other possible contaminants. Instead, a metabolomics approach might be used to obtain "true non-target" analysis. In the present work, such a method was optimized for improved detection capability at low concentrations. The method was evaluated using 19 chemically diverse model compounds spiked into milk samples to mimic unknown contamination. Other milk samples were used as reference samples. All samples were analyzed with UHPLC-TOF-MS (ultra-high-performance liquid chromatography time-of-flight mass spectrometry), using reversed-phase chromatography and electrospray ionization in positive mode. Data evaluation was performed by the software TracMass 2. No target lists of specific compounds were used to search for the contaminants. Instead, the software was used to sort out all features only occurring in the spiked sample data, i.e., the workflow resembled a metabolomics approach. Procedures for chemical identification of peaks were outside the scope of the study. Method, study design, and settings in the software were optimized to minimize manual evaluation and faulty or irrelevant hits and to maximize hit rate of the spiked compounds. A practical detection limit was established at 25 μg/kg. At this concentration, most compounds (17 out of 19) were detected as intact precursor ions, as fragments or as adducts. Only 2 irrelevant hits, probably natural compounds, were obtained. Limitations and possible practical use of the approach are discussed.

Preprocessing and Analysis of LC-MS-Based Proteomic Data

PubMed Central

Tsai, Tsung-Heng; Wang, Minkun; Ressom, Habtom W.

2016-01-01

Liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used for profiling protein expression levels. This chapter is focused on LC-MS data preprocessing, which is a crucial step in the analysis of LC-MS based proteomics. We provide a high-level overview, highlight associated challenges, and present a step-by-step example for analysis of data from LC-MS based untargeted proteomic study. Furthermore, key procedures and relevant issues with the subsequent analysis by multiple reaction monitoring (MRM) are discussed. PMID:26519169

Offline pentafluorophenyl (PFP)-RP prefractionation as an alternative to high-pH RP for comprehensive LC-MS/MS proteomics and phosphoproteomics.

PubMed

Grassetti, Andrew V; Hards, Rufus; Gerber, Scott A

2017-07-01

Technological advances in liquid chromatography and tandem mass spectrometry (LC-MS/MS) have enabled comprehensive analyses of proteins and their post-translational modifications from cell culture and tissue samples. However, sample complexity necessitates offline prefractionation via a chromatographic method that is orthogonal to online reversed-phase high-performance liquid chromatography (RP-HPLC). This additional fractionation step improves target identification rates by reducing the complexity of the sample as it is introduced to the instrument. A commonly employed offline prefractionation method is high pH reversed-phase (Hi-pH RP) chromatography. Though highly orthogonal to online RP-HPLC, Hi-pH RP relies on buffers that interfere with electrospray ionization. Thus, samples that are prefractionated using Hi-pH RP are typically desalted prior to LC-MS/MS. In the present work, we evaluate an alternative offline prefractionation method, pentafluorophenyl (PFP)-based reversed-phase chromatography. Importantly, PFP prefractionation results in samples that are dried prior to analysis by LC-MS/MS. This reduction in sample handling relative to Hi-pH RP results in time savings and could facilitate higher target identification rates. Here, we have compared the performances of PFP and Hi-pH RP in offline prefractionation of peptides and phosphopeptides that have been isolated from human cervical carcinoma (HeLa) cells. Given the prevalence of isobaric mass tags for peptide quantification, we evaluated PFP chromatography of peptides labeled with tandem mass tags. Our results suggest that PFP is a viable alternative to Hi-pH RP for both peptide and phosphopeptide offline prefractionation.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.

Current proteomics approaches are comprised of both broad discovery measurements as well as more quantitative targeted measurements. These two different measurement types are used to initially identify potentially important proteins (e.g., candidate biomarkers) and then enable improved quantification for a limited number of selected proteins. However, both approaches suffer from limitations, particularly the lower sensitivity, accuracy, and quantitation precision for discovery approaches compared to targeted approaches, and the limited proteome coverage provided by targeted approaches. Herein, we describe a new proteomics approach that allows both discovery and targeted monitoring (DTM) in a single analysis using liquid chromatography, ion mobility spectrometrymore » and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled peptides for target ions are spiked into tryptic digests and both the labeled and unlabeled peptides are broadly detected using LC-IMS-MS instrumentation, allowing the benefits of discovery and targeted approaches. To understand the possible improvement of the DTM approach, it was compared to LC-MS broad measurements using an accurate mass and time tag database and selected reaction monitoring (SRM) targeted measurements. The DTM results yielded greater peptide/protein coverage and a significant improvement in the detection of lower abundance species compared to LC-MS discovery measurements. DTM was also observed to have similar detection limits as SRM for the targeted measurements indicating its potential for combining the discovery and targeted approaches.« less

Formation of dehydroalanine from mimosine and cysteine: artifacts in gas chromatography/mass spectrometry based metabolomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Young-Mo; Metz, Thomas O.; Hu, Zeping

2011-08-15

Trimethylsilyation is a chemical derivatization procedure routinely applied in gas chromatography-mass spectrometry (GC-MS)-based metabolomics. In this report, through de novo structural elucidation and comparison with authentic standards, we demonstrate that mimosine can be completely converted into dehydroalanine and 3,4-dihydroxypyridine during the trimethylsilyating process. Similarly, dehydroalanine can be formed from derivatization of cysteine. This conversion is a potential interference in GC-MS-based global metabolomics, as well as in analysis of amino acids.

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis

PubMed Central

Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA. PMID:26716989

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

PubMed

Ahn, Joong Kyong; Kim, Sooah; Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows.

PubMed

Tian, He; Wang, Weiyu; Zheng, Nan; Cheng, Jianbo; Li, Songli; Zhang, Yangdong; Wang, Jiaqi

2015-07-01

Controlling heat stress (HS) is a global challenge for the dairy industry. However, simple and reliable biomarkers that aid the diagnoses of HS-induced metabolic disorders have not yet been identified. In this work, an integrated metabolomic and lipidomic approach using (1)H nuclear magnetic resonance and ultra-fast LC-MS was employed to investigate the discrimination of plasma metabolic profiles between HS-free and HS lactating dairy cows. Targeted detection using LC-MS in multiple reaction monitoring mode was used to verify the reliability of the metabolites as biomarker candidates. Overall, 41 metabolites were identified as candidates for lactating dairy cows exposed to HS, among which 13 metabolites, including trimethylamine, glucose, lactate, betaine, creatine, pyruvate, acetoacetate, acetone, β-hydroxybutyrate, C16 sphinganine, lysophosphatidylcholine (18:0), phosphatidylcholine (16:0/14:0), and arachidonic acid, had high sensitivity and specificity in diagnosing HS status, and are likely to be the potential biomarkers of HS dairy cows. All of these potentially diagnostic biomarkers were involved in carbohydrate, amino acid, lipid, or gut microbiome-derived metabolism, indicating that HS affected the metabolic pathways in lactating dairy cows. Further research is warranted to evaluate these biomarkers in practical applications and to elucidate the physiological mechanisms of HS-induced metabolic disorders. Heat stress (HS) annually causes huge losses to global dairy industry, including animal performance decrease, metabolic disorder and health problem. So far, physiological mechanisms underlying HS of dairy cows still remain elusive. To our best knowledge, this is the first attempt to elucidate the HS-induced metabolic disorders of dairy cows using integrated (1)H NMR and LC-MS-based metabolic study. The results not only provided potential diagnostic biomarkers for HS lactating dairy cows, but also significantly explored the related physiological mechanisms of metabolic pathway shifts induced by HS environment. This work offers comprehensive insights into the global metabolic alterations of dairy cows exposed to HS and provides a new perspective for further study. Copyright © 2015 Elsevier B.V. All rights reserved.

Informatics for Metabolomics.

PubMed

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Applications of mass spectrometry in drug metabolism: 50 years of progress.

PubMed

Wen, Bo; Zhu, Mingshe

2015-02-01

Mass spectrometry plays a pivotal role in drug metabolism studies, which are an integral part of drug discovery and development nowadays. Metabolite identification has become critical to understanding the metabolic fate of drug candidates and to aid lead optimization with improved metabolic stability, toxicology and efficacy profiles. Ever since the introduction of atmospheric ionization techniques in the early 1990s, liquid chromatography coupled with mass spectrometry (LC/MS) has secured a central role as the predominant analytical platform for metabolite identification as LC and MS technologies continually advanced. In this review, we discuss the evolution of both MS technology and its applications over the past 50 years to meet the increasing demand of drug metabolism studies. These advances include ionization sources, mass analyzers, a wide range of MS acquisition strategies and data mining tools that have substantially accelerated the metabolite identification process and changed the overall drug metabolism landscape. Exemplary applications for characterization and identification of both small-molecule xenobiotics and biological macromolecules are described. In addition, this review discusses novel MS technologies and applications, including xenobiotic metabolomics that hold additional promise for advancing drug metabolism research, and offers thoughts on remaining challenges in studying the metabolism and disposition of drugs and other xenobiotics.

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

PubMed

Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

2016-08-01

Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Discovery and Validation of Pyridoxic Acid and Homovanillic Acid as Novel Endogenous Plasma Biomarkers of Organic Anion Transporter (OAT) 1 and OAT3 in Cynomolgus Monkeys.

PubMed

Shen, Hong; Nelson, David M; Oliveira, Regina V; Zhang, Yueping; Mcnaney, Colleen A; Gu, Xiaomei; Chen, Weiqi; Su, Ching; Reily, Michael D; Shipkova, Petia A; Gan, Jinping; Lai, Yurong; Marathe, Punit; Humphreys, W Griffith

2018-02-01

Perturbation of organic anion transporter (OAT) 1- and OAT3-mediated transport can alter the exposure, efficacy, and safety of drugs. Although there have been reports of the endogenous biomarkers for OAT1/3, none of these have all of the characteristics required for a clinical useful biomarker. Cynomolgus monkeys were treated with intravenous probenecid (PROB) at a dose of 40 mg/kg in this study. As expected, PROB increased the area under the plasma concentration-time curve (AUC) of coadministered furosemide, a known substrate of OAT1 and OAT3, by 4.1-fold, consistent with the values reported in humans (3.1- to 3.7-fold). Of the 233 plasma metabolites analyzed using a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics method, 29 metabolites, including pyridoxic acid (PDA) and homovanillic acid (HVA), were significantly increased after either 1 or 3 hours in plasma from the monkeys pretreated with PROB compared with the treated animals. The plasma of animals was then subjected to targeted LC-MS/MS analysis, which confirmed that the PDA and HVA AUCs increased by approximately 2- to 3-fold by PROB pretreatments. PROB also increased the plasma concentrations of hexadecanedioic acid (HDA) and tetradecanedioic acid (TDA), although the increases were not statistically significant. Moreover, transporter profiling assessed using stable cell lines constitutively expressing transporters demonstrated that PDA and HVA are substrates for human OAT1, OAT3, OAT2 (HVA), and OAT4 (PDA), but not OCT2, MATE1, MATE2K, OATP1B1, OATP1B3, and sodium taurocholate cotransporting polypeptide. Collectively, these findings suggest that PDA and HVA might serve as blood-based endogenous probes of cynomolgus monkey OAT1 and OAT3, and investigation of PDA and HVA as circulating endogenous biomarkers of human OAT1 and OAT3 function is warranted. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Multi-approach metabolomics analysis and artificial simplified phytocomplexes reveal cultivar-dependent synergy between polyphenols and ascorbic acid in fruits of the sweet cherry (Prunus avium L.)

PubMed Central

Di Carlo, Flavia; Poletti, Stefania; Bulgarini, Alessandra; Munari, Francesca; Negri, Stefano; Stocchero, Matteo; Ceoldo, Stefania; Avesani, Linda; Assfalg, Michael; Zoccatelli, Gianni; Guzzo, Flavia

2017-01-01

Fruits of the sweet cherry (Prunus avium L.) accumulate a range of antioxidants that can help to prevent cardiovascular disease, inflammation and cancer. We tested the in vitro antioxidant activity of 18 sweet cherry cultivars collected from 12 farms in the protected geographical indication region of Marostica (Vicenza, Italy) during two growing seasons. Multiple targeted and untargeted metabolomics approaches (NMR, LC-MS, HPLC-DAD, HPLC-UV) as well as artificial simplified phytocomplexes representing the cultivars Sandra Tardiva, Sandra and Grace Star were then used to determine whether the total antioxidant activity reflected the additive effects of each compound or resulted from synergistic interactions. We found that the composition of each cultivar depended more on genetic variability than environmental factors. Furthermore, phenolic compounds were the principal source of antioxidant activity and experiments with artificial simplified phytocomplexes indicated strong synergy between the anthocyanins and quercetins/ascorbic acid specifically in the cultivar Sandra Tardiva. Our data therefore indicate that the total antioxidant activity of sweet cherry fruits may originate from cultivar-dependent interactions among different classes of metabolite. PMID:28732012

Quantification of peptides from immunoglobulin constant and variable regions by LC-MRM MS for assessment of multiple myeloma patients.

PubMed

Remily-Wood, Elizabeth R; Benson, Kaaron; Baz, Rachid C; Chen, Y Ann; Hussein, Mohamad; Hartley-Brown, Monique A; Sprung, Robert W; Perez, Brianna; Liu, Richard Z; Yoder, Sean J; Teer, Jamie K; Eschrich, Steven A; Koomen, John M

2014-10-01

Quantitative MS assays for Igs are compared with existing clinical methods in samples from patients with plasma cell dyscrasias, for example, multiple myeloma (MM). Using LC-MS/MS data, Ig constant region peptides, and transitions were selected for LC-MRM MS. Quantitative assays were used to assess Igs in serum from 83 patients. RNA sequencing and peptide-based LC-MRM are used to define peptides for quantification of the disease-specific Ig. LC-MRM assays quantify serum levels of Igs and their isoforms (IgG1-4, IgA1-2, IgM, IgD, and IgE, as well as kappa (κ) and lambda (λ) light chains). LC-MRM quantification has been applied to single samples from a patient cohort and a longitudinal study of an IgE patient undergoing treatment, to enable comparison with existing clinical methods. Proof-of-concept data for defining and monitoring variable region peptides are provided using the H929 MM cell line and two MM patients. LC-MRM assays targeting constant region peptides determine the type and isoform of the involved Ig and quantify its expression; the LC-MRM approach has improved sensitivity compared with the current clinical method, but slightly higher inter-assay variability. Detection of variable region peptides is a promising way to improve Ig quantification, which could produce a dramatic increase in sensitivity over existing methods, and could further complement current clinical techniques. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification and Profiling of Specialized Pro-Resolving Mediators in Human Tears by Lipid Mediator Metabolomics.

PubMed

English, Justin T; Norris, Paul C; Hodges, Robin R; Dartt, Darlene A; Serhan, Charles N

2017-02-01

Specialized pro-resolving mediators (SPM), e.g. Resolvin D1, Protectin D1, Lipoxin A₄, and Resolvin E1 have each shown to be active in ocular models reducing inflammation. In general, SPMs have specific agonist functions that stimulate resolution of infection and inflammation in animal disease models. The presence and quantity of SPM in human emotional tears is of interest. Here, utilizing a targeted LC-MS-MS metabololipidomics based approach we document the identification of pro-inflammatory (Prostaglandins and Leukotriene B₄) and pro-resolving lipid mediators (D-series Resolvins, Protectin D1, and Lipoxin A₄) in human emotional tears from 12 healthy individuals. SPMs from the Maresin family (Maresin 1 and Maresin 2) were not present in these samples. Principal Component Analysis (PCA) revealed gender differences in the production of specific mediators within these tear samples as the SPMs were essentially absent in these female donors. These results indicate that specific SPM signatures are present in human emotional tears at concentrations known to be bioactive. Moreover, they will help to further appreciate the mechanisms of production and action of SPMs in the eye, as well as their physiologic roles in human ocular disease resolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Silibinin-mediated metabolic reprogramming attenuates pancreatic cancer-induced cachexia and tumor growth.

PubMed

Shukla, Surendra K; Dasgupta, Aneesha; Mehla, Kamiya; Gunda, Venugopal; Vernucci, Enza; Souchek, Joshua; Goode, Gennifer; King, Ryan; Mishra, Anusha; Rai, Ibha; Nagarajan, Sangeetha; Chaika, Nina V; Yu, Fang; Singh, Pankaj K

2015-12-01

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths in the US. Cancer-associated cachexia is present in up to 80% of PDAC patients and is associated with aggressive disease and poor prognosis. In the present studies we evaluated an anti-cancer natural product silibinin for its effectiveness in targeting pancreatic cancer aggressiveness and the cachectic properties of pancreatic cancer cells and tumors. Our results demonstrate that silibinin inhibits pancreatic cancer cell growth in a dose-dependent manner and reduces glycolytic activity of cancer cells. Our LC-MS/MS based metabolomics data demonstrates that silibinin treatment induces global metabolic reprogramming in pancreatic cancer cells. Silibinin treatment diminishes c-MYC expression, a key regulator of cancer metabolism. Furthermore, we observed reduced STAT3 signaling in silibinin-treated cancer cells. Overexpression of constitutively active STAT3 was sufficient to substantially revert the silibinin-induced downregulation of c-MYC and the metabolic phenotype. Our in vivo investigations demonstrate that silibinin reduces tumor growth and proliferation in an orthotopic mouse model of pancreatic cancer and prevents the loss of body weight and muscle. It also improves physical activity including grip strength and latency to fall in tumor-bearing mice. In conclusion, silibinin-induced metabolic reprogramming diminishes cell growth and cachectic properties of pancreatic cancer cells and animal models.

Quantification of proteins in urine samples using targeted mass spectrometry methods.

PubMed

Khristenko, Nina; Domon, Bruno

2015-01-01

Numerous clinical proteomics studies are focused on the development of biomarkers to improve either diagnostics for early disease detection or the monitoring of the response to the treatment. Although, a wealth of biomarker candidates are available, their evaluation and validation in a true clinical setup remains challenging. In biomarkers evaluation studies, a panel of proteins of interest are systematically analyzed in a large cohort of samples. However, in spite of the latest progresses in mass spectrometry, the consistent detection of pertinent proteins in high complex biological samples is still a challenging task. Thus, targeted LC-MS/MS methods are better suited for the systematic analysis of biomarkers rather than shotgun approaches. This chapter describes the workflow used to perform targeted quantitative analyses of proteins in urinary samples. The peptides, as surrogates of the protein of interest, are commonly measured using a triple quadrupole mass spectrometers operated in selected reaction monitoring (SRM) mode. More recently, the advances in targeted LC-MS/MS analysis based on parallel reaction monitoring (PRM) performed on a quadrupole-orbitrap instrument have allowed to increase the specificity and selectivity of the measurements.

A metabolomic study of low estimated GFR in non-proteinuric type 2 diabetes mellitus.

PubMed

Ng, D P K; Salim, A; Liu, Y; Zou, L; Xu, F G; Huang, S; Leong, H; Ong, C N

2012-02-01

We carried out a urinary metabolomic study to gain insight into low estimated GFR (eGFR) in patients with non-proteinuric type 2 diabetes. Patients were identified as being non-proteinuric using multiple urinalyses. Cases (n = 44) with low eGFR and controls (n = 46) had eGFR values <60 and ≥60 ml min(-1) 1.73 m(-2), respectively, as calculated using the Modification of Diet in Renal Disease formula. Urine samples were analysed by liquid chromatography/mass spectrometry (LC/MS) and GC/MS. False discovery rates were used to adjust for multiple hypotheses testing, and selection of metabolites that best predicted low eGFR status was achieved using least absolute shrinkage and selection operator logistic regression. Eleven GC/MS metabolites were strongly associated with low eGFR after correction for multiple hypotheses testing (smallest adjusted p value = 2.62 × 10(-14), largest adjusted p value = 3.84 × 10(-2)). In regression analysis, octanol, oxalic acid, phosphoric acid, benzamide, creatinine, 3,5-dimethoxymandelic amide and N-acetylglutamine were selected as the best subset for prediction and allowed excellent classification of low eGFR (AUC = 0.996). In LC/MS, 19 metabolites remained significant after multiple hypotheses testing had been taken into account (smallest adjusted p value = 2.04 × 10(-4), largest adjusted p value = 4.48 × 10(-2)), and several metabolites showed stronger evidence of association relative to the uraemic toxin, indoxyl sulphate (adjusted p value = 3.03 × 10(-2)). The potential effect of confounding on the association between metabolites was excluded. Our study has yielded substantial new insight into low eGFR and provided a collection of potential urinary biomarkers for its detection.

Bisphenol A Alters n-6 Fatty Acid Composition and Decreases Antioxidant Enzyme Levels in Rat Testes: A LC-QTOF-Based Metabolomics Study

PubMed Central

Qiao, Shanlei; Hu, Nan; Hu, Yanhui; Wu, Wei; Qiu, Lianglin; Zhang, Ruyang; Wang, Yubang; Wang, Shoulin; Zhou, Zuomin; Xia, Yankai; Wang, Xinru

2012-01-01

Background Male reproductive toxicity induced by exposure to bisphenol A (BPA) has been widely reported. The testes have proven to be a major target organ of BPA toxicity, so studying testicular metabolite variation holds promise for the discovery of mechanisms linked to the toxic effects of BPA on reproduction. Methodology/Principal Findings Male Sprague-Dawley rats were orally administered doses of BPA at the levels of 0, 50 mg/kg/d for 8 weeks. We used an unbiased liquid chromatography-quadrupole time-of-flight (LC-QTOF)-based metabolomics approach to discover, identify, and analyze the variation of testicular metabolites. Two n-6 fatty acids, linoleic acid (LA) and arachidonic acid (AA) were identified as potential testicular biomarkers. Decreased levels of LA and increased levels of AA as well as AA/LA ratio were observed in the testes of the exposed group. According to these suggestions, testicular antioxidant enzyme levels were detected. Testicular superoxide dismutase (SOD) declined significantly in the exposed group compared with that in the non-exposed group, and the glutathione peroxidase (GSH-Px) as well as catalase (CAT) also showed a decreasing trend in BPA treated group. Conclusions/Significance BPA caused testicular n-6 fatty acid composition variation and decreased antioxidant enzyme levels. This study emphasizes that metabolomics brings the promise of biomarkers identification for the discovery of mechanisms underlying reproductive toxicity. PMID:23024759

Intake of Hydrolyzed Casein is Associated with Reduced Body Fat Accretion and Enhanced Phase II Metabolism in Obesity Prone C57BL/6J Mice

PubMed Central

Clausen, Morten Rahr; Zhang, Xumin; Yde, Christian C.; Ditlev, Ditte B.; Lillefosse, Haldis H.; Madsen, Lise; Kristiansen, Karsten; Liaset, Bjørn; Bertram, Hanne C.

2015-01-01

The amount and form of dietary casein have been shown to affect energy metabolism and lipid accumulation in mice, but the underlying mechanisms are not fully understood. We investigated 48 hrs urinary metabolome, hepatic lipid composition and gene expression in male C57BL/6J mice fed Western diets with 16 or 32 energy% protein in the form of extensively hydrolyzed or intact casein. LC-MS based metabolomics revealed a very strong impact of casein form on the urinary metabolome. Evaluation of the discriminatory metabolites using tandem mass spectrometry indicated that intake of extensively hydrolyzed casein modulated Phase II metabolism associated with an elevated urinary excretion of glucuronic acid- and sulphate conjugated molecules, whereas glycine conjugated molecules were more abundant in urine from mice fed the intact casein diets. Despite the differences in the urinary metabolome, we observed no differences in hepatic expression of genes involved in Phase II metabolism, but it was observed that expression of Abcc3 encoding ATP binding cassette c3 (transporter of glucuronic acid conjugates) was increased in livers of mice fed hydrolyzed casein. As glucuronic acid is derived from glucose and sulphate is derived from cysteine, our metabolomic data provided evidence for changes in carbohydrate and amino acid metabolism and we propose that this modulation of metabolism was associated with the reduced glucose and lipid levels observed in mice fed the extensively hydrolyzed casein diets. PMID:25738501

Complementarity of SOMAscan to LC-MS/MS and RNA-seq for quantitative profiling of human embryonic and mesenchymal stem cells.

PubMed

Billing, Anja M; Ben Hamidane, Hisham; Bhagwat, Aditya M; Cotton, Richard J; Dib, Shaima S; Kumar, Pankaj; Hayat, Shahina; Goswami, Neha; Suhre, Karsten; Rafii, Arash; Graumann, Johannes

2017-01-06

Dynamic range limitations are challenging to proteomics, particularly in clinical samples. Affinity proteomics partially overcomes this, yet suffers from dependence on reagent quality. SOMAscan, an aptamer-based platform for over 1000 proteins, avoids that issue using nucleic acid binders. Targets include low expressed proteins not easily accessible by other approaches. Here we report on the potential of SOMAscan for the study of differently sourced mesenchymal stem cells (MSC) in comparison to LC-MS/MS and RNA sequencing. While targeting fewer analytes, SOMAscan displays high precision and dynamic range coverage, allowing quantification of proteins not measured by the other platforms. Expression between cell types (ESC and MSC) was compared across techniques and uncovered the expected large differences. Sourcing was investigated by comparing subtypes: bone marrow-derived, standard in clinical studies, and ESC-derived MSC, thought to hold similar potential but devoid of inter-donor variability and proliferating faster in vitro. We confirmed subtype-equivalency, as well as vesicle and extracellular matrix related processes in MSC. In contrast, the proliferative nature of ESC was captured less by SOMAscan, where nuclear proteins are underrepresented. The complementary of SOMAscan allowed the comprehensive exploration of CD markers and signaling molecules, not readily accessible otherwise and offering unprecedented potential in subtype characterization. Mesenchymal stem cells (MSC) represent promising stem cell-derived therapeutics as indicated by their application in >500 clinical trials currently registered with the NIH. Tissue-derived MSC require invasive harvesting and imply donor-to-donor differences, to which embryonic stem cell (ESC)-derived MSC may provide an alternative and thus warrant thorough characterization. In continuation of our previous study where we compared in depth embryonic stem cells (ESC) and MSC from two sources (bone marrow and ESC-derived), we included the aptamer-based SOMAscan assay, complementing LC-MS/MS and RNA-seq data. Furthermore, SOMAscan, a targeted proteomics platform developed for analyzing clinical samples, has been benchmarked against established analytical platforms (LC-MS/MS and RNA-seq) using stem cell comparisons as a model. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Impact of Pre-analytic Blood Sample Collection Factors on Metabolomics.

PubMed

Townsend, Mary K; Bao, Ying; Poole, Elizabeth M; Bertrand, Kimberly A; Kraft, Peter; Wolpin, Brian M; Clish, Clary B; Tworoger, Shelley S

2016-05-01

Many epidemiologic studies are using metabolomics to discover markers of carcinogenesis. However, limited data are available on the influence of pre-analytic blood collection factors on metabolite measurement. We quantified 166 metabolites in archived plasma from 423 Health Professionals Follow-up Study and Nurses' Health Study participants using liquid chromatography-tandem mass spectrometry (LC-MS). We compared multivariable-adjusted geometric mean metabolite LC-MS peak areas across fasting time, season of blood collection, and time of day of blood collection categories. The majority of metabolites (160 of 166 metabolites) had geometric mean peak areas that were within 15% comparing samples donated after fasting 9 to 12 versus ≥13 hours; greater differences were observed in samples donated after fasting ≤4 hours. Metabolite peak areas generally were similar across season of blood collection, although levels of certain metabolites (e.g., bile acids and purines/pyrimidines) tended to be different in the summer versus winter months. After adjusting for fasting status, geometric mean peak areas for bile acids and vitamins, but not other metabolites, differed by time of day of blood collection. Fasting, season of blood collection, and time of day of blood collection were not important sources of variability in measurements of most metabolites in our study. However, considering blood collection variables in the design or analysis of studies may be important for certain specific metabolites, particularly bile acids, purines/pyrimidines, and vitamins. These results may be useful for investigators formulating analysis plans for epidemiologic metabolomics studies, including determining which metabolites to a priori exclude from analyses. Cancer Epidemiol Biomarkers Prev; 25(5); 823-9. ©2016 AACR. ©2016 American Association for Cancer Research.

Identification and determination of fat-soluble vitamins and metabolites in human serum by liquid chromatography/triple quadrupole mass spectrometry with multiple reaction monitoring.

PubMed

Priego Capote, Feliciano; Jiménez, José Ruiz; Granados, José María Mata; de Castro, María Dolores Luque

2007-01-01

A method for determination of fat-soluble vitamins K(1), K(3), A, D(2), D(3) and E (as alpha- and delta-tocopherol) and metabolites 25-hydroxyvitamin D(2) and D(3) and 1,25-dihydroxyvitamin D(3) in human serum by liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) in positive mode is proposed. Highly selective identification of the target compounds in serum was confirmed by the most representative transitions from precursor ion to product ion. Quantitative MS/MS analysis was carried out by multiple reaction monitoring optimizing the most sensitive transition for each analyte in order to achieve low detection limits (from 0.012 to 0.3 ng/mL estimated with serum). The analysis was performed with 1 mL of serum, which was subjected to protein precipitation, liquid-liquid extraction to an organic phase, evaporation to dryness and reconstitution with methanol. The precision of the overall method ranged from 3.17-6.76% as intra-day variability and from 5.07-11.53% as inter-day variability. The method, validated by the standard addition method, provides complete information on the fat-soluble vitamins profile, which is of interest in clinical and metabolomics studies.

Two-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.

PubMed

Schripsema, Jan; Dagnino, Denise

2018-01-01

Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them, and to provide hypothesis to explain those differences [1]. But obtaining complete metabolic fingerprints is not an easy task. Metabolite extraction is a key step during this process, and much research has been devoted to finding the best solvent mixture to extract as much metabolites as possible.Here a procedure is described for analysis of both polar and apolar metabolites using a two-phase extraction system. D 2 O and CDCl 3 are the solvents of choice, and their major advantage is that, for the identification of the compounds, standard databases can be used because D 2 O and CDCl 3 are the solvents most commonly used for pure compound NMR spectra. The procedure enables the absolute quantification of components via the addition of suitable internal standards. The extracts are also suitable for further analysis with other systems like LC-MS or GC-MS.

Patulin and secondary metabolite production by marine-derived Penicillium strains.

PubMed

Vansteelandt, Marieke; Kerzaon, Isabelle; Blanchet, Elodie; Fossi Tankoua, Olivia; Robiou Du Pont, Thibaut; Joubert, Yolaine; Monteau, Fabrice; Le Bizec, Bruno; Frisvad, Jens C; Pouchus, Yves François; Grovel, Olivier

2012-09-01

Genus Penicillium represents an important fungal group regarding to its mycotoxin production. Secondary metabolomes of eight marine-derived strains belonging to subgenera Furcatum and Penicillium were investigated using dereplication by liquid chromatography (LC)-Diode Array Detector (DAD)-mass spectrometry (MS)/MS. Each strain was grown on six different culture media to enhance the number of observable metabolites. Thirty-two secondary metabolites were detected in crude extracts with twenty first observations for studied species. Patulin, a major mycotoxin, was classically detected in extracts of Penicillium expansum, and was also isolated from Penicillium antarcticum cultures, whose secondary metabolome is still to be done. These detections constituted the first descriptions of patulin in marine strains of Penicillium, highlighting the risk for shellfish and their consumers due to the presence of these fungi in shellfish farming areas. Patulin induced acute neurotoxicity on Diptera larvae, indicating the interest of this bioassay as an additional tool for detection of this major mycotoxin in crude extracts. Copyright © 2012 The British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Contaminant screening of wastewater with HPLC-IM-qTOF-MS and LC+LC-IM-qTOF-MS using a CCS database.

PubMed

Stephan, Susanne; Hippler, Joerg; Köhler, Timo; Deeb, Ahmad A; Schmidt, Torsten C; Schmitz, Oliver J

2016-09-01

Non-target analysis has become an important tool in the field of water analysis since a broad variety of pollutants from different sources are released to the water cycle. For identification of compounds in such complex samples, liquid chromatography coupled to high resolution mass spectrometry are often used. The introduction of ion mobility spectrometry provides an additional separation dimension and allows determining collision cross sections (CCS) of the analytes as a further physicochemical constant supporting the identification. A CCS database with more than 500 standard substances including drug-like compounds and pesticides was used for CCS data base search in this work. A non-target analysis of a wastewater sample was initially performed with high performance liquid chromatography (HPLC) coupled to an ion mobility-quadrupole-time of flight mass spectrometer (IM-qTOF-MS). A database search including exact mass (±5 ppm) and CCS (±1 %) delivered 22 different compounds. Furthermore, the same sample was analyzed with a two-dimensional LC method, called LC+LC, developed in our group for the coupling to IM-qTOF-MS. This four dimensional separation platform revealed 53 different compounds, identified over exact mass and CCS, in the examined wastewater sample. It is demonstrated that the CCS database can also help to distinguish between isobaric structures exemplified for cyclophosphamide and ifosfamide. Graphical Abstract Scheme of sample analysis and database screening.

Development of a Metabolic Biosignature for Detection of Early Lyme Disease

PubMed Central

Molins, Claudia R.; Ashton, Laura V.; Wormser, Gary P.; Hess, Ann M.; Delorey, Mark J.; Mahapatra, Sebabrata; Schriefer, Martin E.; Belisle, John T.

2015-01-01

Background. Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing 2-tier serology-based assays yield low sensitivities (29%–40%) for early infection. The lack of an accurate laboratory test for early Lyme disease contributes to misconceptions about diagnosis and treatment, and underscores the need for new diagnostic approaches. Methods. Retrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients' LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard 2-tier serology. Results. Metabolic biosignature development selected 95 molecular features that distinguished early Lyme disease patients from healthy controls. Statistical modeling reduced the biosignature to 44 molecular features, and correctly classified early Lyme disease patients and healthy controls with a sensitivity of 88% (84%–95%), and a specificity of 95% (90%–100%). Importantly, the metabolic biosignature correctly classified 77%–95% of the of serology negative Lyme disease patients. Conclusions. The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (P < .0001) diagnostic sensitivity than current 2-tier serology, while retaining high specificity. PMID:25761869

Identification of human plasma metabolites exhibiting time-of-day variation using an untargeted liquid chromatography-mass spectrometry metabolomic approach.

PubMed

Ang, Joo Ern; Revell, Victoria; Mann, Anuska; Mäntele, Simone; Otway, Daniella T; Johnston, Jonathan D; Thumser, Alfred E; Skene, Debra J; Raynaud, Florence

2012-08-01

Although daily rhythms regulate multiple aspects of human physiology, rhythmic control of the metabolome remains poorly understood. The primary objective of this proof-of-concept study was identification of metabolites in human plasma that exhibit significant 24-h variation. This was assessed via an untargeted metabolomic approach using liquid chromatography-mass spectrometry (LC-MS). Eight lean, healthy, and unmedicated men, mean age 53.6 (SD ± 6.0) yrs, maintained a fixed sleep/wake schedule and dietary regime for 1 wk at home prior to an adaptation night and followed by a 25-h experimental session in the laboratory where the light/dark cycle, sleep/wake, posture, and calorific intake were strictly controlled. Plasma samples from each individual at selected time points were prepared using liquid-phase extraction followed by reverse-phase LC coupled to quadrupole time-of-flight MS analysis in positive ionization mode. Time-of-day variation in the metabolites was screened for using orthogonal partial least square discrimination between selected time points of 10:00 vs. 22:00 h, 16:00 vs. 04:00 h, and 07:00 (d 1) vs. 16:00 h, as well as repeated-measures analysis of variance with time as an independent variable. Subsequently, cosinor analysis was performed on all the sampled time points across the 24-h day to assess for significant daily variation. In this study, analytical variability, assessed using known internal standards, was low with coefficients of variation <10%. A total of 1069 metabolite features were detected and 203 (19%) showed significant time-of-day variation. Of these, 34 metabolites were identified using a combination of accurate mass, tandem MS, and online database searches. These metabolites include corticosteroids, bilirubin, amino acids, acylcarnitines, and phospholipids; of note, the magnitude of the 24-h variation of these identified metabolites was large, with the mean ratio of oscillation range over MESOR (24-h time series mean) of 65% (95% confidence interval [CI]: 49-81%). Importantly, several of these human plasma metabolites, including specific acylcarnitines and phospholipids, were hitherto not known to be 24-h variant. These findings represent an important baseline and will be useful in guiding the design and interpretation of future metabolite-based studies.

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease

PubMed Central

Choi1, Yong Seok; Lee, Kelvin H.

2016-01-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (> 90%) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R2 = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78%), and inter-day reproducibility (average CV = 9.85%). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard. PMID:26404792

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease.

PubMed

Choi, Yong Seok; Lee, Kelvin H

2016-03-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (>90 %) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems in laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R(2) = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78 %), and inter-day reproducibility (average CV = 9.85 %). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard.

Strategy to improve the quantitative LC-MS analysis of molecular ions resistant to gas-phase collision induced dissociation: application to disulfide-rich cyclic peptides.

PubMed

Ciccimaro, Eugene; Ranasinghe, Asoka; D'Arienzo, Celia; Xu, Carrie; Onorato, Joelle; Drexler, Dieter M; Josephs, Jonathan L; Poss, Michael; Olah, Timothy

2014-12-02

Due to observed collision induced dissociation (CID) fragmentation inefficiency, developing sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) assays for CID resistant compounds is especially challenging. As an alternative to traditional LC-MS/MS, we present here a methodology that preserves the intact analyte ion for quantification by selectively filtering ions while reducing chemical noise. Utilizing a quadrupole-Orbitrap MS, the target ion is selectively isolated while interfering matrix components undergo MS/MS fragmentation by CID, allowing noise-free detection of the analyte's surviving molecular ion. In this manner, CID affords additional selectivity during high resolution accurate mass analysis by elimination of isobaric interferences, a fundamentally different concept than the traditional approach of monitoring a target analyte's unique fragment following CID. This survivor-selected ion monitoring (survivor-SIM) approach has allowed sensitive and specific detection of disulfide-rich cyclic peptides extracted from plasma.

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data.

PubMed

Uppal, Karan; Soltow, Quinlyn A; Strobel, Frederick H; Pittard, W Stephen; Gernert, Kim M; Yu, Tianwei; Jones, Dean P

2013-01-16

Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

Multiple reaction monitoring-ion pair finder: a systematic approach to transform nontargeted mode to pseudotargeted mode for metabolomics study based on liquid chromatography-mass spectrometry.

PubMed

Luo, Ping; Dai, Weidong; Yin, Peiyuan; Zeng, Zhongda; Kong, Hongwei; Zhou, Lina; Wang, Xiaolin; Chen, Shili; Lu, Xin; Xu, Guowang

2015-01-01

Pseudotargeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from quadrupole time-of-flight (Q-TOF) MS by information-dependent acquisition (IDA) and then picks targeted ion pairs and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of the pseudotargeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS(2) spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was first analyzed; the representative ion pairs were correctly picked out. Then, pooled serum samples were further studied, and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, and a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer; 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudotargeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.

A liquid chromatography-tandem mass spectrometry-based targeted proteomics assay for monitoring P-glycoprotein levels in human breast tissue.

PubMed

Yang, Ting; Chen, Fei; Xu, Feifei; Wang, Fengliang; Xu, Qingqing; Chen, Yun

2014-09-25

P-glycoprotein (P-gp) can efflux drugs from cancer cells, and its overexpression is commonly associated with multi-drug resistance (MDR). Thus, the accurate quantification of P-gp would help predict the response to chemotherapy and for prognosis of breast cancer patients. An advanced liquid chromatography-tandem mass spectrometry (LC/MS/MS)-based targeted proteomics assay was developed and validated for monitoring P-gp levels in breast tissue. Tryptic peptide 368IIDNKPSIDSYSK380 was selected as a surrogate analyte for quantification, and immuno-depleted tissue extract was used as a surrogate matrix. Matched pairs of breast tissue samples from 60 patients who were suspected to have drug resistance were subject to analysis. The levels of P-gp were quantified. Using data from normal tissue, we suggested a P-gp reference interval. The experimental values of tumor tissue samples were compared with those obtained from Western blotting and immunohistochemistry (IHC). The result indicated that the targeted proteomics approach was comparable to IHC but provided a lower limit of quantification (LOQ) and could afford more reliable results at low concentrations than the other two methods. LC/MS/MS-based targeted proteomics may allow the quantification of P-gp in breast tissue in a more accurate manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study.

PubMed

Kellogg, Joshua J; Graf, Tyler N; Paine, Mary F; McCune, Jeannine S; Kvalheim, Olav M; Oberlies, Nicholas H; Cech, Nadja B

2017-05-26

A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods-untargeted ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1 HNMR-were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products.

Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study

PubMed Central

2017-01-01

A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods—untargeted ultraperformance liquid chromatography–mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1HNMR—were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products. PMID:28453261

Towards the Fecal Metabolome Derived from Moderate Red Wine Intake

PubMed Central

Jiménez-Girón, Ana; Muñoz-González, Irene; Martín-Álvarez, Pedro J.; Moreno-Arribas, María Victoria; Bartolomé, Begoña

2014-01-01

Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others) seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33). It assembles data from two analytical approaches: (1) UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis); and (2) UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis). Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota. PMID:25532710

The differential metabolite profiles of acute lymphoblastic leukaemic patients treated with 6-mercaptopurine using untargeted metabolomics approach.

PubMed

Bannur, Z; Teh, L K; Hennesy, T; Rosli, W R W; Mohamad, N; Nasir, A; Ankathil, R; Zakaria, Z A; Baba, A; Salleh, M Z

2014-04-01

Acute lymphoblastic leukaemia (ALL) has posed challenges to the clinician due to variable patients' responses and late diagnosis. With the advance in metabolomics, early detection and personalised treatment are possible. Metabolomic profile of 21 ALL patients treated with 6-mercaptopurine and 10 healthy volunteers were analysed using liquid chromatography/mass spectrometry quadrupole-time of flight (LC/MS Q-TOF). Principal components analysis (PCA), recursive analysis, clustering and pathway analysis were performed using MassHunter Qualitative and Mass Profiler Professional (MPP) software. Several metabolites were found to be expressed differently in patients treated with 6-mercaptopurine. Interestingly, 13 metabolites were significantly differently expressed [p-value <0.01 (unpaired t-test) and 2-fold change] in 19% of the patients who had relapses in their treatment. Down-regulated metabolites in relapsed patients were 1-tetrahexanoyl-2-(8-[3]-ladderane-octanyl)-sn-GPEtn, GPEtn (18:1(9Z)/0:0), GPCho(O-6:0/O-6:0), GPCho(O-2:0/O-1:0), methyl 8-[2-(2-formyl-vinyl)-3-hydroxy-5-oxo-cyclopentyl]-octanoate and plasma free amino acids (PFAA). Characterizing the subjects according to their ITPA 94C>A genotypes reveal differential expression of metabolites. Our research contributes to identification of metabolites that could be used to monitor disease progress of patients and allow targeted therapy for ALL at different stages, especially in preventing complication of relapse. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Simultaneous Detection of Human C-Terminal p53 Isoforms by Single Template Molecularly Imprinted Polymers (MIPs) Coupled with Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Targeted Proteomics.

PubMed

Jiang, Wenting; Liu, Liang; Chen, Yun

2018-03-06

Abnormal expression of C-terminal p53 isoforms α, β, and γ can cause the development of cancers including breast cancer. To date, much evidence has demonstrated that these isoforms can differentially regulate target genes and modulate their expression. Thus, quantification of individual isoforms may help to link clinical outcome to p53 status and to improve cancer patient treatment. However, there are few studies on accurate determination of p53 isoforms, probably due to sequence homology of these isoforms and also their low abundance. In this study, a targeted proteomics assay combining molecularly imprinted polymers (MIPs) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed for simultaneous quantification of C-terminal p53 isoforms. Isoform-specific surrogate peptides (i.e., KPLDGEYFTLQIR (peptide-α) for isoform α, KPLDGEYFTLQDQTSFQK (peptide-β) for isoform β, and KPLDGEYFTLQMLLDLR (peptide-γ) for isoform γ) were first selected and used in both MIPs enrichment and mass spectrometric detection. The common sequence KPLDGEYFTLQ of these three surrogate peptides was used as single template in MIPs. In addition to optimization of imprinting conditions and characterization of the prepared MIPs, binding affinity and cross-reactivity of the MIPs for each surrogate peptide were also evaluated. As a result, a LOQ of 5 nM was achieved, which was >15-fold more sensitive than that without MIPs. Finally, the assay was validated and applied to simultaneous quantitative analysis of C-terminal p53 isoforms α, β, and γ in several human breast cell lines (i.e., MCF-10A normal cells, MCF-7 and MDA-MB-231 cancer cells, and drug-resistant MCF-7/ADR cancer cells). This study is among the first to employ single template MIPs and cross-reactivity phenomenon to select isoform-specific surrogate peptides and enable simultaneous quantification of protein isoforms in LC-MS/MS-based targeted proteomics.

Evaluation of the potential use of hybrid LC-MS/MS for active drug quantification applying the 'free analyte QC concept'.

PubMed

Jordan, Gregor; Onami, Ichio; Heinrich, Julia; Staack, Roland F

2017-11-01

Assessment of active drug exposure of biologics may be crucial for drug development. Typically, ligand-binding assay methods are used to provide free/active drug concentrations. To what extent hybrid LC-MS/MS procedures enable correct 'active' drug quantification is currently under consideration. Experimental & results: The relevance of appropriate extraction condition was evaluated by a hybrid target capture immuno-affinity LC-MS/MS method using total and free/active quality controls (QCs). The rapid extraction (10 min) provided correct results, whereas overnight incubation resulted in significant overestimation of the free/active drug (monclonal antibody) concentration. Conventional total QCs were inappropriate to determine optimal method conditions in contrast to free/active QCs. The 'free/active analyte QC concept' enables development of appropriate extraction conditions for correct active drug quantification by hybrid LC-MS/MS.

Development of multiclass methods for drug residues in eggs: hydrophilic solid-phase extraction cleanup and liquid chromatography/tandem mass spectrometry analysis of tetracycline, fluoroquinolone, sulfonamide, and beta-lactam residues.

PubMed

Heller, David N; Nochetto, Cristina B; Rummel, Nathan G; Thomas, Michael H

2006-07-26

A method was developed for detection of a variety of polar drug residues in eggs via liquid chromatography/tandem mass spectrometry (LC/MS/MS) with electrospray ionization (ESI). A total of twenty-nine target analytes from four drug classes-sulfonamides, tetracyclines, fluoroquinolones, and beta-lactams-were extracted from eggs using a hydrophilic-lipophilic balance polymer solid-phase extraction (SPE) cartridge. The extraction technique was developed for use at a target concentration of 100 ng/mL (ppb), and it was applied to eggs containing incurred residues from dosed laying hens. The ESI source was tuned using a single, generic set of tuning parameters, and analytes were separated with a phenyl-bonded silica cartridge column using an LC gradient. In a related study, residues of beta-lactam drugs were not found by LC/MS/MS in eggs from hens dosed orally with beta-lactam drugs. LC/MS/MS performance was evaluated on two generations of ion trap mass spectrometers, and key operational parameters were identified for each instrument. The ion trap acquisition methods could be set up for screening (a single product ion) or confirmation (multiple product ions). The lower limit of detection for screening purposes was 10-50 ppb (sulfonamides), 10-20 ppb (fluoroquinolones), and 10-50 ppb (tetracyclines), depending on the drug, instrument, and acquisition method. Development of this method demonstrates the feasibility of generic SPE, LC, and MS conditions for multiclass LC/MS residue screening.

Fast targeted analysis of 132 acidic and neutral drugs and poisons in whole blood using LC-MS/MS.

PubMed

Di Rago, Matthew; Saar, Eva; Rodda, Luke N; Turfus, Sophie; Kotsos, Alex; Gerostamoulos, Dimitri; Drummer, Olaf H

2014-10-01

The aim of this study was to develop an LC-MS/MS based screening technique that covers a broad range of acidic and neutral drugs and poisons by combining a small sample volume and efficient extraction technique with simple automated data processing. After protein precipitation of 100μL of whole blood, 132 common acidic and neutral drugs and poisons including non-steroidal anti-inflammatory drugs, barbiturates, anticonvulsants, antidiabetics, muscle relaxants, diuretics and superwarfarin rodenticides (47 quantitated, 85 reported as detected) were separated using a Shimadzu Prominence HPLC system with a C18 separation column (Kinetex XB-C18, 4.6mm×150mm, 5μm), using gradient elution with a mobile phase of 25mM ammonium acetate buffer (pH 7.5)/acetonitrile. The drugs were detected using an ABSciex(®) API 2000 LC-MS/MS system (ESI+ and -, MRM mode, two transitions per analyte). The method was fully validated in accordance with international guidelines. Quantification data obtained using one-point calibration compared favorably to that using multiple calibrants. The presented LC-MS/MS assay has proven to be applicable for determination of the analytes in blood. The fast and reliable extraction method combined with automated processing gives the opportunity for high throughput and fast turnaround times for forensic and clinical toxicology. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS).

PubMed

Abbatiello, Susan E; Mani, D R; Schilling, Birgit; Maclean, Brendan; Zimmerman, Lisa J; Feng, Xingdong; Cusack, Michael P; Sedransk, Nell; Hall, Steven C; Addona, Terri; Allen, Simon; Dodder, Nathan G; Ghosh, Mousumi; Held, Jason M; Hedrick, Victoria; Inerowicz, H Dorota; Jackson, Angela; Keshishian, Hasmik; Kim, Jong Won; Lyssand, John S; Riley, C Paige; Rudnick, Paul; Sadowski, Pawel; Shaddox, Kent; Smith, Derek; Tomazela, Daniela; Wahlander, Asa; Waldemarson, Sofia; Whitwell, Corbin A; You, Jinsam; Zhang, Shucha; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Borchers, Christoph H; Buck, Charles; Fisher, Susan J; Gibson, Bradford W; Liebler, Daniel; Maccoss, Michael; Neubert, Thomas A; Paulovich, Amanda; Regnier, Fred; Skates, Steven J; Tempst, Paul; Wang, Mu; Carr, Steven A

2013-09-01

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)*

PubMed Central

Abbatiello, Susan E.; Mani, D. R.; Schilling, Birgit; MacLean, Brendan; Zimmerman, Lisa J.; Feng, Xingdong; Cusack, Michael P.; Sedransk, Nell; Hall, Steven C.; Addona, Terri; Allen, Simon; Dodder, Nathan G.; Ghosh, Mousumi; Held, Jason M.; Hedrick, Victoria; Inerowicz, H. Dorota; Jackson, Angela; Keshishian, Hasmik; Kim, Jong Won; Lyssand, John S.; Riley, C. Paige; Rudnick, Paul; Sadowski, Pawel; Shaddox, Kent; Smith, Derek; Tomazela, Daniela; Wahlander, Asa; Waldemarson, Sofia; Whitwell, Corbin A.; You, Jinsam; Zhang, Shucha; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Borchers, Christoph H.; Buck, Charles; Fisher, Susan J.; Gibson, Bradford W.; Liebler, Daniel; MacCoss, Michael; Neubert, Thomas A.; Paulovich, Amanda; Regnier, Fred; Skates, Steven J.; Tempst, Paul; Wang, Mu; Carr, Steven A.

2013-01-01

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities. PMID:23689285

Absolute quantification of histone PTM marks by MRM-based LC-MS/MS.

PubMed

Gao, Jun; Liao, Rijing; Yu, Yanyan; Zhai, Huili; Wang, Yingqi; Sack, Ragna; Peters, Antoine H F M; Chen, Jiajia; Wu, Haiping; Huang, Zheng; Hu, Min; Qi, Wei; Lu, Chris; Atadja, Peter; Oyang, Counde; Li, En; Yi, Wei; Zhou, Shaolian

2014-10-07

The N-terminal tails of core histones harbor the sites of numerous post-translational modifications (PTMs) with important roles in the regulation of chromatin structure and function. Profiling histone PTM marks provides data that help understand the epigenetics events in cells and their connections with cancer and other diseases. Our previous study demonstrated that specific derivatization of histone peptides by NHS propionate significantly improved their chromatographic performance on reversed phase columns for LC/MS analysis. As a step forward, we recently developed a multiple reaction monitoring (MRM) based LC-MS/MS method to analyze 42 targeted histone peptides. By using stable isotopic labeled peptides as internal standards that are spiked into the reconstituted solutions, this method allows to measure absolute concentration of the tryptic peptides of H3 histone proteins extracted from cancer cell lines. The method was thoroughly validated for the accuracy and reproducibility through analyzing recombinant histone proteins and cellular samples. The linear dynamic range of the MRM assays was achieved in 3 orders of magnitude from 1 nM to 1 μM for all targeted peptides. Excellent intrabatch and interbatch reproducibility (<15% CV) was obtained. This method has been used to study translocated NSD2 (a histone lysine methyltransferase that catalyzes the histone lysine 36 methylation) function with its overexpression in KMS11 multiple myeloma cells. From the results we have successfully quantitated both individual and combinatorial histone marks in parental and NSD2 selective knockout KMS11 cells.

Atmo-metabolomics: a new measurement approach for investigating aerosol composition and ecosystem functioning.

NASA Astrophysics Data System (ADS)

Rivas-Ubach, A.; Liu, Y.; Sardans, J.; Tfaily, M. M.; Kim, Y. M.; Bourrianne, E.; Paša-Tolić, L.; Penuelas, J.; Guenther, A. B.

2016-12-01

Aerosols play crucial roles in the processes controlling the composition of the atmosphere and the functioning of ecosystems. Gaining a deeper understanding of the chemical composition of aerosols is one of the major challenges for atmospheric and climate scientists and is beginning to be recognized as important for ecological research. Better comprehension of aerosol chemistry can potentially provide valuable information on atmospheric processes such as oxidation of organics and the production of cloud condensation nuclei as well as provide an approximation of the general status of an ecosystem through the measurement of certain stress biomarkers. In this study, we describe an efficient aerosol sampling method, the metabolite extraction and the analytical procedures for the chemical characterization of aerosols, namely, the atmo-metabolome. We used mass spectrometry (MS) coupled to liquid chromatography (LC-MS), gas chromatography (GC-MS) and Fourier transform ion cyclotron resonance (FT-ICR-MS) to characterize the atmo-metabolome of two marked seasons; spring and summer. Our sampling and extraction methods demonstrated to be suitable for aerosol chemical characterization with any of the analytical platforms used in this study. The atmo-metabolome between spring and summer showed overall statistically differences. We identified several metabolites that can be attributed to pollen and other plant-related aerosols. Spring aerosols exhibit higher concentrations of metabolites linked to higher plant activity while summer samples had higher concentrations of metabolites that may reflect certain oxidative stresses in primary producers. Moreover, the elemental composition of aerosols showed clear different between seasons. Summer aerosols were generally higher in molecular weight and with higher O/C ratios, indicating higher oxidation levels and condensation of compounds relative to spring. Our method represents an advanced approach for characterizing the composition of aerosols that will benefit scientists attempting to understand complex atmospheric processes and the ecosystem status across a whole ecoregion.

Integrated and global pseudotargeted metabolomics strategy applied to screening for quality control markers of Citrus TCMs.

PubMed

Shu, Yisong; Liu, Zhenli; Zhao, Siyu; Song, Zhiqian; He, Dan; Wang, Menglei; Zeng, Honglian; Lu, Cheng; Lu, Aiping; Liu, Yuanyan

2017-08-01

Traditional Chinese medicine (TCM) exerts its therapeutic effect in a holistic fashion with the synergistic function of multiple characteristic constituents. The holism philosophy of TCM is coincident with global and systematic theories of metabolomics. The proposed pseudotargeted metabolomics methodologies were employed for the establishment of reliable quality control markers for use in the screening strategy of TCMs. Pseudotargeted metabolomics integrates the advantages of both targeted and untargeted methods. In the present study, targeted metabolomics equipped with the gold standard RRLC-QqQ-MS method was employed for in vivo quantitative plasma pharmacochemistry study of characteristic prototypic constituents. Meanwhile, untargeted metabolomics using UHPLC-QE Orbitrap HRMS with better specificity and selectivity was employed for identification of untargeted metabolites in the complex plasma matrix. In all, 32 prototypic metabolites were quantitatively determined, and 66 biotransformed metabolites were convincingly identified after being orally administered with standard extracts of four labeled Citrus TCMs. The global absorption and metabolism process of complex TCMs was depicted in a systematic manner.

Ash leaf metabolomes reveal differences between trees tolerant and susceptible to ash dieback disease.

PubMed

Sambles, Christine M; Salmon, Deborah L; Florance, Hannah; Howard, Thomas P; Smirnoff, Nicholas; Nielsen, Lene R; McKinney, Lea V; Kjær, Erik D; Buggs, Richard J A; Studholme, David J; Grant, Murray

2017-12-19

European common ash, Fraxinus excelsior, is currently threatened by Ash dieback (ADB) caused by the fungus, Hymenoscyphus fraxineus. To detect and identify metabolites that may be products of pathways important in contributing to resistance against H. fraxineus, we performed untargeted metabolomic profiling on leaves from five high-susceptibility and five low-susceptibility F. excelsior individuals identified during Danish field trials. We describe in this study, two datasets. The first is untargeted LC-MS metabolomics raw data from ash leaves with high-susceptibility and low-susceptibility to ADB in positive and negative mode. These data allow the application of peak picking, alignment, gap-filling and retention-time correlation analyses to be performed in alternative ways. The second, a processed dataset containing abundances of aligned features across all samples enables further mining of the data. Here we illustrate the utility of this dataset which has previously been used to identify putative iridoid glycosides, well known anti-herbivory terpenoid derivatives, and show differential abundance in tolerant and susceptible ash samples.

Ash leaf metabolomes reveal differences between trees tolerant and susceptible to ash dieback disease

PubMed Central

Sambles, Christine M.; Salmon, Deborah L.; Florance, Hannah; Howard, Thomas P.; Smirnoff, Nicholas; Nielsen, Lene R.; McKinney, Lea V.; Kjær, Erik D.; Buggs, Richard J. A.; Studholme, David J.; Grant, Murray

2017-01-01

European common ash, Fraxinus excelsior, is currently threatened by Ash dieback (ADB) caused by the fungus, Hymenoscyphus fraxineus. To detect and identify metabolites that may be products of pathways important in contributing to resistance against H. fraxineus, we performed untargeted metabolomic profiling on leaves from five high-susceptibility and five low-susceptibility F. excelsior individuals identified during Danish field trials. We describe in this study, two datasets. The first is untargeted LC-MS metabolomics raw data from ash leaves with high-susceptibility and low-susceptibility to ADB in positive and negative mode. These data allow the application of peak picking, alignment, gap-filling and retention-time correlation analyses to be performed in alternative ways. The second, a processed dataset containing abundances of aligned features across all samples enables further mining of the data. Here we illustrate the utility of this dataset which has previously been used to identify putative iridoid glycosides, well known anti-herbivory terpenoid derivatives, and show differential abundance in tolerant and susceptible ash samples. PMID:29257137

A proteomics assay to detect eight CBRN-relevant toxins in food.

PubMed

Gilquin, Benoit; Jaquinod, Michel; Louwagie, Mathilde; Kieffer-Jaquinod, Sylvie; Kraut, Alexandra; Ferro, Myriam; Becher, François; Brun, Virginie

2017-01-01

A proteomics assay was set up to analyze food substrates for eight toxins of the CBRN (chemical, biological, radiological and nuclear) threat, namely ricin, Clostridium perfringens epsilon toxin (ETX), Staphylococcus aureus enterotoxins (SEA, SEB and SED), shigatoxins from Shigella dysenteriae and entero-hemorragic Escherichia coli strains (STX1 and STX2) and Campylobacter jejuni cytolethal distending toxin (CDT). The assay developed was based on an antibody-free sample preparation followed by bottom-up LC-MS/MS analysis operated in targeted mode. Highly specific detection and absolute quantification were obtained using isotopically labeled proteins (PSAQ standards) spiked into the food matrix. The sensitivity of the assay for the eight toxins was lower than the oral LD50 which would likely be used in a criminal contamination of food supply. This assay should be useful in monitoring biological threats. In the public-health domain, it opens the way for multiplex investigation of food-borne toxins using targeted LC-MS/MS. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Combining targeted and nontargeted data analysis for liquid chromatography/high-resolution mass spectrometric analyses.

PubMed

Croley, Timothy R; White, Kevin D; Wong, Jon; Callahan, John H; Musser, Steven M; Antler, Margaret; Lashin, Vitaly; McGibbon, Graham A

2013-03-01

Increasing importation of food and the diversity of potential contaminants have necessitated more analytical testing of these foods. Historically, mass spectrometric methods for testing foods were confined to monitoring selected ions (SIM or MRM), achieving sensitivity by focusing on targeted ion signals. A limiting factor in this approach is that any contaminants not included on the target list are not typically identified and retrospective data mining is limited. A potential solution is to utilize high-resolution MS to acquire accurate mass full-scan data. Based on the instrumental resolution, these data can be correlated to the actual mass of a contaminant, which would allow for identification of both target compounds and compounds that are not on a target list (nontargets). The focus of this research was to develop software algorithms to provide rapid and accurate data processing of LC/MS data to identify both targeted and nontargeted analytes. Software from a commercial vendor was developed to process LC/MS data and the results were compared to an alternate, vendor-supplied solution. The commercial software performed well and demonstrated the potential for a fully automated processing solution. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative Evaluation of Preprocessing Freeware on Chromatography/Mass Spectrometry Data for Signature Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coble, Jamie B.; Fraga, Carlos G.

2014-07-07

Preprocessing software is crucial for the discovery of chemical signatures in metabolomics, chemical forensics, and other signature-focused disciplines that involve analyzing large data sets from chemical instruments. Here, four freely available and published preprocessing tools known as metAlign, MZmine, SpectConnect, and XCMS were evaluated for impurity profiling using nominal mass GC/MS data and accurate mass LC/MS data. Both data sets were previously collected from the analysis of replicate samples from multiple stocks of a nerve-agent precursor. Each of the four tools had their parameters set for the untargeted detection of chromatographic peaks from impurities present in the stocks. The peakmore » table generated by each preprocessing tool was analyzed to determine the number of impurity components detected in all replicate samples per stock. A cumulative set of impurity components was then generated using all available peak tables and used as a reference to calculate the percent of component detections for each tool, in which 100% indicated the detection of every component. For the nominal mass GC/MS data, metAlign performed the best followed by MZmine, SpectConnect, and XCMS with detection percentages of 83, 60, 47, and 42%, respectively. For the accurate mass LC/MS data, the order was metAlign, XCMS, and MZmine with detection percentages of 80, 45, and 35%, respectively. SpectConnect did not function for the accurate mass LC/MS data. Larger detection percentages were obtained by combining the top performer with at least one of the other tools such as 96% by combining metAlign with MZmine for the GC/MS data and 93% by combining metAlign with XCMS for the LC/MS data. In terms of quantitative performance, the reported peak intensities had average absolute biases of 41, 4.4, 1.3 and 1.3% for SpectConnect, metAlign, XCMS, and MZmine, respectively, for the GC/MS data. For the LC/MS data, the average absolute biases were 22, 4.5, and 3.1% for metAlign, MZmine, and XCMS, respectively. In summary, metAlign performed the best in terms of peak discovery; however, more than one preprocessing tool should be considered to avoid missing potential chemical signatures.« less

MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.

PubMed

Jeffryes, James G; Colastani, Ricardo L; Elbadawi-Sidhu, Mona; Kind, Tobias; Niehaus, Thomas D; Broadbelt, Linda J; Hanson, Andrew D; Fiehn, Oliver; Tyo, Keith E J; Henry, Christopher S

2015-01-01

In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography-mass spectrometry (LC-MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC-MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences.

PubMed

Padliya, Neerav D; Garrett, Wesley M; Campbell, Kimberly B; Tabb, David L; Cooper, Bret

2007-11-01

LC-MS/MS has demonstrated potential for detecting plant pathogens. Unlike PCR or ELISA, LC-MS/MS does not require pathogen-specific reagents for the detection of pathogen-specific proteins and peptides. However, the MS/MS approach we and others have explored does require a protein sequence reference database and database-search software to interpret tandem mass spectra. To evaluate the limitations of database composition on pathogen identification, we analyzed proteins from cultured Ustilago maydis, Phytophthora sojae, Fusarium graminearum, and Rhizoctonia solani by LC-MS/MS. When the search database did not contain sequences for a target pathogen, or contained sequences to related pathogens, target pathogen spectra were reliably matched to protein sequences from nontarget organisms, giving an illusion that proteins from nontarget organisms were identified. Our analysis demonstrates that when database-search software is used as part of the identification process, a paradox exists whereby additional sequences needed to detect a wide variety of possible organisms may lead to more cross-species protein matches and misidentification of pathogens.

Metabolomics: A potential way to know the role of vitamin D on multiple sclerosis.

PubMed

Luque-Córdoba, Diego; Luque de Castro, María D

2017-03-20

The literature about the influence of vitamin D on multiple sclerosis (MS) is very controversial, possibly as a result of the way through which the research on the subject has been conducted. The studies developed so far have been focused exclusively on gene expression: the effect of a given vitamin D metabolite on target receptors. The influence of the vitamin D status (either natural or after supplementation) on MS has been studied by measurement of the 25 monohydroxylated metabolite (also known as circulating form), despite the 1,25 dihydroxylated metabolite is considered the active form. In the light of the multiple metabolic pathways in which both forms of vitamin D (D 2 and D 3 ) are involved, monitoring of the metabolites is crucial to know the activity of the target enzymes as a function of both the state of the MS patient and the clinical treatment applied. The study of metabolomics aspects is here proposed to clarify the present controversy. In "omics" terms, our proposal is to take profit from up-stream information-thus is, from metabolomics to genomics-with a potential subsequent step to systems biology, if required. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

PubMed Central

Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

2011-01-01

Background Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract. Conclusions/Significance Our findings suggest that metabolic profiling is a useful approach for nutraceutical evaluation of the health promotion effects of diverse tea cultivars. This may propose a novel strategy for functional food design. PMID:21853132

Conventional-Flow Liquid Chromatography-Mass Spectrometry for Exploratory Bottom-Up Proteomic Analyses.

PubMed

Lenčo, Juraj; Vajrychová, Marie; Pimková, Kristýna; Prokšová, Magdaléna; Benková, Markéta; Klimentová, Jana; Tambor, Vojtěch; Soukup, Ondřej

2018-04-17

Due to its sensitivity and productivity, bottom-up proteomics based on liquid chromatography-mass spectrometry (LC-MS) has become the core approach in the field. The de facto standard LC-MS platform for proteomics operates at sub-μL/min flow rates, and nanospray is required for efficiently introducing peptides into a mass spectrometer. Although this is almost a "dogma", this view is being reconsidered in light of developments in highly efficient chromatographic columns, and especially with the introduction of exceptionally sensitive MS instruments. Although conventional-flow LC-MS platforms have recently penetrated targeted proteomics successfully, their possibilities in discovery-oriented proteomics have not yet been thoroughly explored. Our objective was to determine what are the extra costs and what optimization and adjustments to a conventional-flow LC-MS system must be undertaken to identify a comparable number of proteins as can be identified on a nanoLC-MS system. We demonstrate that the amount of a complex tryptic digest needed for comparable proteome coverage can be roughly 5-fold greater, providing the column dimensions are properly chosen, extra-column peak dispersion is minimized, column temperature and flow rate are set to levels appropriate for peptide separation, and the composition of mobile phases is fine-tuned. Indeed, we identified 2 835 proteins from 2 μg of HeLa cells tryptic digest separated during a 60 min gradient at 68 μL/min on a 1.0 mm × 250 mm column held at 55 °C and using an aqua-acetonitrile mobile phases containing 0.1% formic acid, 0.4% acetic acid, and 3% dimethyl sulfoxide. Our results document that conventional-flow LC-MS is an attractive alternative for bottom-up exploratory proteomics.

Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

PubMed

Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

2016-01-01

Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

Metabolomic approach with LC-MS reveals significant effect of pressure on diver's plasma.

PubMed

Ciborowski, Michal; Javier Rupérez, F; Martínez-Alcázar, Ma Paz; Angulo, Santiago; Radziwon, Piotr; Olszanski, Romuald; Kloczko, Janusz; Barbas, Coral

2010-08-06

Professional and recreational diving are growing activities in modern life. Diving has been associated with increased prevalence of stroke, hypertension, asthma, diabetes, or bone necrosis. We evaluated the effect of increased pressure equivalent to diving at 30 and 60 m for 30 min in two groups of divers using an untargeted approach with LC-MS fingerprinting of plasma. We found over 100 metabolites to be altered in plasma post exposure and after the corresponding decompression procedures. Among them, a group of lysophosphatidylcholines and lysophosphatidylethanolamines were increased, including lysoplasmalogen, a thrombosis promoter, together with changes in metabolic rate-associated molecules such as acylcarnitines and hemolysis-related compounds. Moreover, three metabolites that could be associated to bone degradation show different intensities between experimental groups. Ultimately, this nontargeted, short-term study opens the possibility of discovering markers of long-term effect of pressure that could be employed in routine health control of divers and could facilitate the development of safer decompression procedures.

Development of a metabolic biosignature for detection of early Lyme disease.

PubMed

Molins, Claudia R; Ashton, Laura V; Wormser, Gary P; Hess, Ann M; Delorey, Mark J; Mahapatra, Sebabrata; Schriefer, Martin E; Belisle, John T

2015-06-15

Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing 2-tier serology-based assays yield low sensitivities (29%-40%) for early infection. The lack of an accurate laboratory test for early Lyme disease contributes to misconceptions about diagnosis and treatment, and underscores the need for new diagnostic approaches. Retrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients' LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard 2-tier serology. Metabolic biosignature development selected 95 molecular features that distinguished early Lyme disease patients from healthy controls. Statistical modeling reduced the biosignature to 44 molecular features, and correctly classified early Lyme disease patients and healthy controls with a sensitivity of 88% (84%-95%), and a specificity of 95% (90%-100%). Importantly, the metabolic biosignature correctly classified 77%-95% of the of serology negative Lyme disease patients. The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (P < .0001) diagnostic sensitivity than current 2-tier serology, while retaining high specificity. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Metabolomic biomarkers identify differences in milk produced by Holstein cows and other minor dairy animals.

PubMed

Yang, Yongxin; Zheng, Nan; Zhao, Xiaowei; Zhang, Yangdong; Han, Rongwei; Yang, Jinhui; Zhao, Shengguo; Li, Songli; Guo, Tongjun; Zang, Changjiang; Wang, Jiaqi

2016-03-16

Several milk metabolites are associated with breeds or species of dairy animals. A better understanding of milk metabolites from different dairy animals would advance their use in evaluating milk traits and detecting milk adulteration. The objective of this study was to characterize the milk metabolite profiles of Chinese Holstein, Jersey, yak, buffalo, goat, camel, and horse and identify any differences using non-targeted metabolomic approaches. Milk samples were tested using nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS). Data were analyzed using a multivariate analysis of variance and differences in milk metabolites between Holstein and the other dairy animals were assessed using orthogonal partial least-squares discriminant analysis. Differential metabolites were identified and some metabolites, such as choline and succinic acid, were used to distinguish Holstein milk from that of the other studied animals. Metabolic pathway analysis of different metabolites revealed that glycerophospholipid metabolism as well as valine, leucine, and isoleucine biosynthesis were shared in the other ruminant animals (Jersey, buffalo, yak, and goat), and biosynthesis of unsaturated fatty acids was shared in the non-ruminant animals (camel and horse). These results can be useful for gaining a better understanding of the differences in milk synthesis between Holstein and the other dairy animals. Copyright © 2016. Published by Elsevier B.V.

The Development of Metabolomic Sampling Procedures for Pichia pastoris, and Baseline Metabolome Data

PubMed Central

Tredwell, Gregory D.; Edwards-Jones, Bryn; Leak, David J.; Bundy, Jacob G.

2011-01-01

Metabolic profiling is increasingly being used to investigate a diverse range of biological questions. Due to the rapid turnover of intracellular metabolites it is important to have reliable, reproducible techniques for sampling and sample treatment. Through the use of non-targeted analytical techniques such as NMR and GC-MS we have performed a comprehensive quantitative investigation of sampling techniques for Pichia pastoris. It was clear that quenching metabolism using solutions based on the standard cold methanol protocol caused some metabolite losses from P. pastoris cells. However, these were at a low level, with the NMR results indicating metabolite increases in the quenching solution below 5% of their intracellular level for 75% of metabolites identified; while the GC-MS results suggest a slightly higher level with increases below 15% of their intracellular values. There were subtle differences between the four quenching solutions investigated but broadly, they all gave similar results. Total culture extraction of cells + broth using high cell density cultures typical of P. pastoris fermentations, was an efficient sampling technique for NMR analysis and provided a gold standard of intracellular metabolite levels; however, salts in the media affected the GC-MS analysis. Furthermore, there was no benefit in including an additional washing step in the quenching process, as the results were essentially identical to those obtained just by a single centrifugation step. We have identified the major high-concentration metabolites found in both the extra- and intracellular locations of P. pastoris cultures by NMR spectroscopy and GC-MS. This has provided us with a baseline metabolome for P. pastoris for future studies. The P. pastoris metabolome is significantly different from that of Saccharomyces cerevisiae, with the most notable difference being the production of high concentrations of arabitol by P. pastoris. PMID:21283710

Silibinin-mediated metabolic reprogramming attenuates pancreatic cancer-induced cachexia and tumor growth

PubMed Central

Shukla, Surendra K.; Dasgupta, Aneesha; Mehla, Kamiya; Gunda, Venugopal; Vernucci, Enza; Souchek, Joshua; Goode, Gennifer; King, Ryan; Mishra, Anusha; Rai, Ibha; Nagarajan, Sangeetha; Chaika, Nina V.; Yu, Fang; Singh, Pankaj K.

2015-01-01

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths in the US. Cancer-associated cachexia is present in up to 80% of PDAC patients and is associated with aggressive disease and poor prognosis. In the present studies we evaluated an anti-cancer natural product silibinin for its effectiveness in targeting pancreatic cancer aggressiveness and the cachectic properties of pancreatic cancer cells and tumors. Our results demonstrate that silibinin inhibits pancreatic cancer cell growth in a dose-dependent manner and reduces glycolytic activity of cancer cells. Our LC-MS/MS based metabolomics data demonstrates that silibinin treatment induces global metabolic reprogramming in pancreatic cancer cells. Silibinin treatment diminishes c-MYC expression, a key regulator of cancer metabolism. Furthermore, we observed reduced STAT3 signaling in silibinin-treated cancer cells. Overexpression of constitutively active STAT3 was sufficient to substantially revert the silibinin-induced downregulation of c-MYC and the metabolic phenotype. Our in vivo investigations demonstrate that silibinin reduces tumor growth and proliferation in an orthotopic mouse model of pancreatic cancer and prevents the loss of body weight and muscle. It also improves physical activity including grip strength and latency to fall in tumor-bearing mice. In conclusion, silibinin-induced metabolic reprogramming diminishes cell growth and cachectic properties of pancreatic cancer cells and animal models. PMID:26510913

SWAPDT: A method for Short-time Withering Assessment of Probability for Drought Tolerance in Camellia sinensis validated by targeted metabolomics.

PubMed

Nyarukowa, Christopher; Koech, Robert; Loots, Theodor; Apostolides, Zeno

2016-07-01

Climate change is causing droughts affecting crop production on a global scale. Classical breeding and selection strategies for drought-tolerant cultivars will help prevent crop losses. Plant breeders, for all crops, need a simple and reliable method to identify drought-tolerant cultivars, but such a method is missing. Plant metabolism is often disrupted by abiotic stress conditions. To survive drought, plants reconfigure their metabolic pathways. Studies have documented the importance of metabolic regulation, i.e. osmolyte accumulation such as polyols and sugars (mannitol, sorbitol); amino acids (proline) during drought. This study identified and quantified metabolites in drought tolerant and drought susceptible Camellia sinensis cultivars under wet and drought stress conditions. For analyses, GC-MS and LC-MS were employed for metabolomics analysis.%RWC results show how the two drought tolerant and two drought susceptible cultivars differed significantly (p≤0.05) from one another; the drought susceptible exhibited rapid water loss compared to the drought tolerant. There was a significant variation (p<0.05) in metabolite content (amino acid, sugars) between drought tolerant and drought susceptible tea cultivars after short-time withering conditions. These metabolite changes were similar to those seen in other plant species under drought conditions, thus validating this method. The Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method presented here provides an easy method to identify drought tolerant tea cultivars that will mitigate the effects of drought due to climate change on crop losses. Copyright © 2016. Published by Elsevier GmbH.

Cross-Classification of Human Urinary Lipidome by Sex, Age, and Body Mass Index.

PubMed

Okemoto, Kazuo; Maekawa, Keiko; Tajima, Yoko; Tohkin, Masahiro; Saito, Yoshiro

2016-01-01

Technological advancements in past decades have led to the development of integrative analytical approaches to lipidomics, such as liquid chromatography-mass spectrometry (LC/MS), and information about biogenic lipids is rapidly accumulating. Although several cohort-based studies have been conducted on the composition of urinary lipidome, the data on urinary lipids cross-classified by sex, age, and body mass index (BMI) are insufficient to screen for various abnormalities. To promote the development of urinary lipid metabolome-based diagnostic assay, we analyzed 60 urine samples from healthy white adults (young (c.a., 30 years) and old (c.a., 60 years) men/women) using LC/MS. Women had a higher urinary concentration of omega-3 12-lipoxygenase (LOX)-generated oxylipins with anti-inflammatory activity compared to men. In addition, young women showed increased abundance of poly-unsaturated fatty acids (PUFAs) and cytochrome P450 (P450)-produced oxylipins with anti-hypertensive activity compared with young men, whereas elderly women exhibited higher concentration of 5-LOX-generated anti-inflammatory oxylipins than elderly men. There were no significant differences in urinary oxylipin levels between young and old subjects or between subjects with low and high BMI. Our findings suggest that sex, but neither ages nor BMI could be a confounding factor for measuring the composition of urinary lipid metabolites in the healthy population. The information showed contribute to the development of reliable biomarker findings from urine.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry*

PubMed Central

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.; Monroe, Matthew E.; Orton, Daniel J.; Ibrahim, Yehia M.; Gritsenko, Marina A.; Clauss, Therese R. W.; Shukla, Anil K.; Moore, Ronald J.; Purvine, Samuel O.; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S.; Smith, Richard D.

2016-01-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. PMID:27670688

Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers.

PubMed

Xu, Jing; Chen, Yanhua; Zhang, Ruiping; Song, Yongmei; Cao, Jianzhong; Bi, Nan; Wang, Jingbo; He, Jiuming; Bai, Jinfa; Dong, Lijia; Wang, Luhua; Zhan, Qimin; Abliz, Zeper

2013-05-01

Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)(1) analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated over the treatment course. The results suggest that these biomarkers may be useful in diagnosis, as well as in monitoring therapeutic responses and predicting outcomes of the ESCC.

Orange juice affects acylcarnitine metabolism in healthy volunteers as revealed by a mass-spectrometry based metabolomics approach.

PubMed

Moreira, Vanessa; Brasili, Elisa; Fiamoncini, Jarlei; Marini, Federico; Miccheli, Alfredo; Daniel, Hannelore; Lee, Jennifer Ji Hye; Hassimotto, Neuza Mariko Aymoto; Lajolo, Franco Maria

2018-05-01

Citrus juices, especially orange juice, constitute rich sources of bioactive compounds with a wide range of health-promoting activities. Data from epidemiological and in vitro studies suggest that orange juice (OJ) may have a positive impact on lipid metabolism. However, the effect of orange juice intake on blood lipid profile is still poorly understood. We have used two different blood samples, Dried Blood Spots (DBS) and plasma, to assess the effect of two-week orange juice consumption in healthy volunteers by a mass-spectrometry based metabolomics approach. DBS were analysed by liquid chromatography mass spectrometry (LC-MS) and plasma samples were analysed by the gas chromatography mass spectrometry (GC-MS). One hundred sixty-nine lipids including acylcarnitines (AC), lysophosphatidylcholines (LysoPC), (diacyl- and acyl-alkyl-) phosphatidylcholines (PC aa and PC ae) and sphingomyelins (SM) were identified and quantified in DBS. Eighteen fatty acids were identified and quantified in plasma. Multivariate analysis allowed to identify an increase in C3:1, C5-DC(C6-OH), C5-M-DC, C5:1-DC, C8, C12-DC, lysoPC18:3, myristic acid, pentadecanoic acid, palmitoleic and palmitic acid and a decrease in nervonic acid, C0, C2, C10, C10:1, C16:1, C16-OH, C16:1-OH, C18-OH, PC aa C40:4, PC ae C38:4, PC ae C42:3, PC ae C42:4 and cholesterol levels after orange juice intake. A two-week period of orange juice intake could affect fatty acids β-oxidation through mitochondrial and peroxisomal pathways, leading to an increase of short-chain acylcarnitines and a decrease of medium and long-chain acylcarnitines. This is the first report analyzing the effect of orange juice intake in healthy volunteers using a dried blood spot-based metabolomics approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

Interrogation of Benzomalvin Biosynthesis Using Fungal Artificial Chromosomes with Metabolomic Scoring (FAC-MS): Discovery of a Benzodiazepine Synthase Activity.

PubMed

Clevenger, Kenneth D; Ye, Rosa; Bok, Jin Woo; Thomas, Paul M; Islam, Md Nurul; Miley, Galen P; Robey, Matthew T; Chen, Cynthia; Yang, KaHoua; Swyers, Michael; Wu, Edward; Gao, Peng; Wu, Chengcang C; Keller, Nancy P; Kelleher, Neil L

2018-03-20

The benzodiazepine benzomalvin A/D is a fungally derived specialized metabolite and inhibitor of the substance P receptor NK1, biosynthesized by a three-gene nonribosomal peptide synthetase cluster. Here, we utilize fungal artificial chromosomes with metabolomic scoring (FAC-MS) to perform molecular genetic pathway dissection and targeted metabolomics analysis to assign the in vivo role of each domain in the benzomalvin biosynthetic pathway. The use of FAC-MS identified the terminal cyclizing condensation domain as BenY-C T and the internal C-domains as BenZ-C 1 and BenZ-C 2 . Unexpectedly, we also uncovered evidence suggesting BenY-C T or a yet to be identified protein mediates benzodiazepine formation, representing the first reported benzodiazepine synthase enzymatic activity. This work informs understanding of what defines a fungal C T domain and shows how the FAC-MS platform can be used as a tool for in vivo analyses of specialized metabolite biosynthesis and for the discovery and dissection of new enzyme activities.

Changes of Metabolomic Profile in Helianthus annuus under Exposure to Chromium(VI) Studied by capHPLC-ESI-QTOF-MS and MS/MS

PubMed Central

Gonzalez Ibarra, Alan Alexander; Wrobel, Kazimierz; Yanez Barrientos, Eunice; Corrales Escobosa, Alma Rosa; Gutierrez Corona, J. Felix; Enciso Donis, Israel

2017-01-01

The application of capHPLC-ESI-QTOF-MS and MS/MS to study the impact of Cr(VI) on metabolites profile in Helianthus annuus is reported. Germinated seeds were grown hydroponically in the presence of Cr(VI) (25 mgCr/L) and root extracts of the exposed and control plants were analyzed by untargeted metabolomic approach. The main goal was to detect which metabolite groups were mostly affected by Cr(VI) stress; two data analysis tools (ProfileAnalysis, Bruker, and online XCMS) were used under criteria of intensity threshold 5 · 104 cps, fold change ≥ 5, and p ≤ 0.01, yielding precursor ions. Molecular formulas were assigned based on data processing with two computational tools (SIRIUS and MS-Finder); annotation of candidate structures was performed by database search using CSI:FingerID and MS-Finder. Even though ultimate identification has not been achieved, it was demonstrated that secondary metabolism became activated under Cr(VI) stress. Among 42 candidate compounds returned from database search for seven molecular formulas, ten structures corresponded to isocoumarin derivatives and eleven were sesquiterpenes or sesquiterpene lactones; three benzofurans and four glycoside or pyrane derivatives of phenolic compounds were also suggested. To gain further insight on the effect of Cr(VI) in sunflower, isocoumarins and sesquiterpenes were selected as the target compounds for future study. PMID:29359067

Lipid Informed Quantitation and Identification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevin Crowell, PNNL

2014-07-21

LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to showmore » the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets« less

Biotransformation and detectability of the new psychoactive substances N,N-diallyltryptamine (DALT) derivatives 5-fluoro-DALT, 7-methyl-DALT, and 5,6-methylenedioxy-DALT in urine using GC-MS, LC-MSn, and LC-HR-MS/MS.

PubMed

Michely, Julian A; Brandt, Simon D; Meyer, Markus R; Maurer, Hans H

2017-02-01

Derivatives of N,N-diallyltryptamine (DALT) can be classified as new psychoactive substances. Biotransformation and detectability of 5-fluoro-DALT (5-F-DALT), 7-methyl-DALT (7-Me-DALT), and 5,6-methylenedioxy-DALT (5,6-MD-DALT) are described here. Their metabolites detected in rat urine and pooled human liver microsomes were identified by liquid chromatography (LC)-high resolution (HR)-tandem mass spectrometry (MS/MS). In addition, the human cytochrome-P450 (CYP) isoenzymes involved in the main metabolic steps were identified and detectability tested in urine by the authors' urine screening approaches using GC-MS, LC-MS n , or LC-HR-MS/MS. Aromatic and aliphatic hydroxylations, N-dealkylation, N-oxidation, and combinations could be proposed for all compounds as main pathways. Carboxylation after initial hydroxylation of the methyl group could also be detected for 7-Me-DALT and O-demethylenation was observed for 5,6-MD-DALT. All phase I metabolites were extensively glucuronidated or sulfated. Initial phase I reactions were catalyzed by CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5. Rat urine samples were analyzed following two different low-dose administrations. GC-MS was not able to monitor consumption reliably, but all three compounds are predicted to be detectable in cases of overdose. The LC-MS n and LC-HR-MS/MS approaches were suitable for detecting an intake of all three compounds mainly via their metabolites. However, after the lowest dose, a reliable monitoring could only be achieved for 5-F-DALT via LC-MS n and LC-HR-MS/MS and for 7-Me-DALT via LC-HR-MS/MS. The most abundant targets in both LC-MS screenings were one of two hydroxy-aryl metabolites and both corresponding glucuronides for 5-F-DALT, one N-deallyl hydroxy-aryl, the carboxy, and one dihydroxy-aryl metabolite for 7-Me-DALT, and the demethylenyl metabolite, its oxo metabolite, and glucuronide for 5,6-MD-DALT.

Tissue Multiplatform-Based Metabolomics/Metabonomics for Enhanced Metabolome Coverage.

PubMed

Vorkas, Panagiotis A; Abellona U, M R; Li, Jia V

2018-01-01

The use of tissue as a matrix to elucidate disease pathology or explore intervention comes with several advantages. It allows investigation of the target alteration directly at the focal location and facilitates the detection of molecules that could become elusive after secretion into biofluids. However, tissue metabolomics/metabonomics comes with challenges not encountered in biofluid analyses. Furthermore, tissue heterogeneity does not allow for tissue aliquoting. Here we describe a multiplatform, multi-method workflow which enables metabolic profiling analysis of tissue samples, while it can deliver enhanced metabolome coverage. After applying a dual consecutive extraction (organic followed by aqueous), tissue extracts are analyzed by reversed-phase (RP-) and hydrophilic interaction liquid chromatography (HILIC-) ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) spectroscopy. This pipeline incorporates the required quality control features, enhances versatility, allows provisional aliquoting of tissue extracts for future guided analyses, expands the range of metabolites robustly detected, and supports data integration. It has been successfully employed for the analysis of a wide range of tissue types.

Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

PubMed

Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

2017-05-02

Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments

PubMed Central

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-01-01

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. PMID:27827849

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments.

PubMed

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-11-02

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio ( m / z ) values and retention times) that serves as a reference, the tool recognizes both m / z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m / z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley.

Metabolic signatures and risk of type 2 diabetes in a Chinese population: an untargeted metabolomics study using both LC-MS and GC-MS.

PubMed

Lu, Yonghai; Wang, Yeli; Ong, Choon-Nam; Subramaniam, Tavintharan; Choi, Hyung Won; Yuan, Jian-Min; Koh, Woon-Puay; Pan, An

2016-11-01

Metabolomics has provided new insight into diabetes risk assessment. In this study we characterised the human serum metabolic profiles of participants in the Singapore Chinese Health Study cohort to identify metabolic signatures associated with an increased risk of type 2 diabetes. In this nested case-control study, baseline serum metabolite profiles were measured using LC-MS and GC-MS during a 6-year follow-up of 197 individuals with type 2 diabetes but without a history of cardiovascular disease or cancer before diabetes diagnosis, and 197 healthy controls matched by age, sex and date of blood collection. A total of 51 differential metabolites were identified between cases and controls. Of these, 35 were significantly associated with diabetes risk in the multivariate analysis after false discovery rate adjustment, such as increased branched-chain amino acids (leucine, isoleucine and valine), non-esterified fatty acids (palmitic acid, stearic acid, oleic acid and linoleic acid) and lysophosphatidylinositol (LPI) species (16:1, 18:1, 18:2, 20:3, 20:4 and 22:6). A combination of six metabolites including proline, glycerol, aminomalonic acid, LPI (16:1), 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid and urea showed the potential to predict type 2 diabetes in at-risk individuals with high baseline HbA1c levels (≥6.5% [47.5 mmol/mol]) with an AUC of 0.935. Combined lysophosphatidylglycerol (LPG) (12:0) and LPI (16:1) also showed the potential to predict type 2 diabetes in individuals with normal baseline HbA1c levels (<6.5% [47.5 mmol/mol]; AUC = 0.781). Our findings show that branched-chain amino acids and NEFA are potent predictors of diabetes development in Chinese adults. Our results also indicate the potential of lysophospholipids for predicting diabetes.

AssayR: A Simple Mass Spectrometry Software Tool for Targeted Metabolic and Stable Isotope Tracer Analyses.

PubMed

Wills, Jimi; Edwards-Hicks, Joy; Finch, Andrew J

2017-09-19

Metabolic analyses generally fall into two classes: unbiased metabolomic analyses and analyses that are targeted toward specific metabolites. Both techniques have been revolutionized by the advent of mass spectrometers with detectors that afford high mass accuracy and resolution, such as time-of-flights (TOFs) and Orbitraps. One particular area where this technology is key is in the field of metabolic flux analysis because the resolution of these spectrometers allows for discrimination between 13 C-containing isotopologues and those containing 15 N or other isotopes. While XCMS-based software is freely available for untargeted analysis of mass spectrometric data sets, it does not always identify metabolites of interest in a targeted assay. Furthermore, there is a paucity of vendor-independent software that deals with targeted analyses of metabolites and of isotopologues in particular. Here, we present AssayR, an R package that takes high resolution wide-scan liquid chromatography-mass spectrometry (LC-MS) data sets and tailors peak detection for each metabolite through a simple, iterative user interface. It automatically integrates peak areas for all isotopologues and outputs extracted ion chromatograms (EICs), absolute and relative stacked bar charts for all isotopologues, and a .csv data file. We demonstrate several examples where AssayR provides more accurate and robust quantitation than XCMS, and we propose that tailored peak detection should be the preferred approach for targeted assays. In summary, AssayR provides easy and robust targeted metabolite and stable isotope analyses on wide-scan data sets from high resolution mass spectrometers.

AssayR: A Simple Mass Spectrometry Software Tool for Targeted Metabolic and Stable Isotope Tracer Analyses

PubMed Central

2017-01-01

Metabolic analyses generally fall into two classes: unbiased metabolomic analyses and analyses that are targeted toward specific metabolites. Both techniques have been revolutionized by the advent of mass spectrometers with detectors that afford high mass accuracy and resolution, such as time-of-flights (TOFs) and Orbitraps. One particular area where this technology is key is in the field of metabolic flux analysis because the resolution of these spectrometers allows for discrimination between 13C-containing isotopologues and those containing 15N or other isotopes. While XCMS-based software is freely available for untargeted analysis of mass spectrometric data sets, it does not always identify metabolites of interest in a targeted assay. Furthermore, there is a paucity of vendor-independent software that deals with targeted analyses of metabolites and of isotopologues in particular. Here, we present AssayR, an R package that takes high resolution wide-scan liquid chromatography–mass spectrometry (LC-MS) data sets and tailors peak detection for each metabolite through a simple, iterative user interface. It automatically integrates peak areas for all isotopologues and outputs extracted ion chromatograms (EICs), absolute and relative stacked bar charts for all isotopologues, and a .csv data file. We demonstrate several examples where AssayR provides more accurate and robust quantitation than XCMS, and we propose that tailored peak detection should be the preferred approach for targeted assays. In summary, AssayR provides easy and robust targeted metabolite and stable isotope analyses on wide-scan data sets from high resolution mass spectrometers. PMID:28850215

Tissue phosphoproteomics with PolyMAC identifies potential therapeutic targets in a transgenic mouse model of HER2 positive breast cancer

PubMed Central

Searleman, Adam C.; Iliuk, Anton B.; Collier, Timothy S.; Chodosh, Lewis A.; Tao, W. Andy; Bose, Ron

2014-01-01

Altered protein phosphorylation is a feature of many human cancers that can be targeted therapeutically. Phosphopeptide enrichment is a critical step for maximizing the depth of phosphoproteome coverage by MS, but remains challenging for tissue specimens because of their high complexity. We describe the first analysis of a tissue phosphoproteome using polymer-based metal ion affinity capture (PolyMAC), a nanopolymer that has excellent yield and specificity for phosphopeptide enrichment, on a transgenic mouse model of HER2-driven breast cancer. By combining phosphotyrosine immunoprecipitation with PolyMAC, 411 unique peptides with 139 phosphotyrosine, 45 phosphoserine, and 29 phosphothreonine sites were identified from five LC-MS/MS runs. Combining reverse phase liquid chromatography fractionation at pH 8.0 with PolyMAC identified 1571 unique peptides with 1279 phosphoserine, 213 phosphothreonine, and 21 phosphotyrosine sites from eight LC-MS/MS runs. Linear motif analysis indicated that many of the phosphosites correspond to well-known phosphorylation motifs. Analysis of the tyrosine phosphoproteome with the Drug Gene Interaction database uncovered a network of potential therapeutic targets centered on Src family kinases with inhibitors that are either FDA-approved or in clinical development. These results demonstrate that PolyMAC is well suited for phosphoproteomic analysis of tissue specimens. PMID:24723360

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

PubMed

Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D; Rodland, Karin D; Camp, David G

2016-01-01

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications.

PubMed

Zhu, Rui; Song, Ehwang; Hussein, Ahmed; Kobeissy, Firas H; Mechref, Yehia

2017-01-01

Proteins and glycoproteins play important biological roles in central nervous systems (CNS). Qualitative and quantitative evaluation of proteins and glycoproteins expression in CNS is critical to reveal the inherent biomolecular mechanism of CNS diseases. This chapter describes proteomic and glycoproteomic approaches based on liquid chromatography/tandem mass spectrometry (LC-MS or LC-MS/MS) for the qualitative and quantitative assessment of proteins and glycoproteins expressed in CNS. Proteins and glycoproteins, extracted by a mass spectrometry friendly surfactant from CNS samples, were subjected to enzymatic (tryptic) digestion and three down-stream analyses: (1) a nano LC system coupled with a high-resolution MS instrument to achieve qualitative proteomic profile, (2) a nano LC system combined with a triple quadrupole MS to quantify identified proteins, and (3) glycoprotein enrichment prior to LC-MS/MS analysis. Enrichment techniques can be applied to improve coverage of low abundant glycopeptides/glycoproteins. An example described in this chapter is hydrophilic interaction liquid chromatographic (HILIC) enrichment to capture glycopeptides, allowing efficient removal of peptides. The combination of three LC-MS/MS-based approaches is capable of the investigation of large-scale proteins and glycoproteins from CNS with an in-depth coverage, thus offering a full view of proteins and glycoproteins changes in CNS.

Optimization study for metabolomics analysis of human sweat by liquid chromatography-tandem mass spectrometry in high resolution mode.

PubMed

Calderón-Santiago, M; Priego-Capote, F; Jurado-Gámez, B; Luque de Castro, M D

2014-03-14

Sweat has recently gained popularity as a potential tool for diagnostics and biomarker monitoring as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis, which increases chloride levels in sweat. The aim of the present study was to develop an analytical method for analysis of human sweat by liquid chromatography-mass spectrometry (LC-Q-TOF MS/MS) in high resolution mode. Thus, different sample preparation strategies and different chromatographic modes (HILIC and C18 reverse modes) were compared to check their effect on the profile of sweat metabolites. Forty-one compounds were identified by the MS/MS information obtained with a mass tolerance window below 4 ppm. Amino acids, dicarboxylic acids and other interesting metabolites such as inosine, choline, uric acid and tyramine were identified. Among the tested protocols, direct analysis after dilution was a suited option to obtain a representative snapshot of sweat metabolome. In addition, sample clean up by C18 SpinColumn SPE cartridges improved the sensitivity of most identified compounds and reduced the number of interferents. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders. Copyright © 2014 Elsevier B.V. All rights reserved.

LC-MS/MS-based approach for obtaining exposure estimates of metabolites in early clinical trials using radioactive metabolites as reference standards.

PubMed

Zhang, Donglu; Raghavan, Nirmala; Chando, Theodore; Gambardella, Janice; Fu, Yunlin; Zhang, Duxi; Unger, Steve E; Humphreys, W Griffith

2007-12-01

An LC-MS/MS-based approach that employs authentic radioactive metabolites as reference standards was developed to estimate metabolite exposures in early drug development studies. This method is useful to estimate metabolite levels in studies done with non-radiolabeled compounds where metabolite standards are not available to allow standard LC-MS/MS assay development. A metabolite mixture obtained from an in vivo source treated with a radiolabeled compound was partially purified, quantified, and spiked into human plasma to provide metabolite standard curves. Metabolites were analyzed by LC-MS/MS using the specific mass transitions and an internal standard. The metabolite concentrations determined by this approach were found to be comparable to those determined by valid LC-MS/MS assays. This approach does not requires synthesis of authentic metabolites or the knowledge of exact structures of metabolites, and therefore should provide a useful method to obtain early estimates of circulating metabolites in early clinical or toxicological studies.

Identification of N-Acetyltaurine as a Novel Metabolite of Ethanol through Metabolomics-guided Biochemical Analysis*

PubMed Central

Shi, Xiaolei; Yao, Dan; Chen, Chi

2012-01-01

The influence of ethanol on the small molecule metabolome and the role of CYP2E1 in ethanol-induced hepatotoxicity were investigated using liquid chromatography-mass spectrometry (LC-MS)-based metabolomics platform and Cyp2e1-null mouse model. Histological and biochemical examinations of ethanol-exposed mice indicated that the Cyp2e1-null mice were more resistant to ethanol-induced hepatic steatosis and transaminase leakage than the wild-type mice, suggesting CYP2E1 contributes to ethanol-induced toxicity. Metabolomic analysis of urinary metabolites revealed time- and dose-dependent changes in the chemical composition of urine. Along with ethyl glucuronide and ethyl sulfate, N-acetyltaurine (NAT) was identified as a urinary metabolite that is highly responsive to ethanol exposure and is correlated with the presence of CYP2E1. Subsequent stable isotope labeling analysis using deuterated ethanol determined that NAT is a novel metabolite of ethanol. Among three possible substrates of NAT biosynthesis (taurine, acetyl-CoA, and acetate), the level of taurine was significantly reduced, whereas the levels of acetyl-CoA and acetate were dramatically increased after ethanol exposure. In vitro incubation assays suggested that acetate is the main precursor of NAT, which was further confirmed by the stable isotope labeling analysis using deuterated acetate. The incubations of tissues and cellular fractions with taurine and acetate indicated that the kidney has the highest NAT synthase activity among the tested organs, whereas the cytosol is the main site of NAT biosynthesis inside the cell. Overall, the combination of biochemical and metabolomic analysis revealed NAT is a novel metabolite of ethanol and a potential biomarker of hyperacetatemia. PMID:22228769

Metabolism of the new psychoactive substances N,N-diallyltryptamine (DALT) and 5-methoxy-DALT and their detectability in urine by GC-MS, LC-MSn, and LC-HR-MS-MS.

PubMed

Michely, Julian A; Helfer, Andreas G; Brandt, Simon D; Meyer, Markus R; Maurer, Hans H

2015-10-01

N,N-Diallyltryptamine (DALT) and 5-methoxy-DALT (5-MeO-DALT) are synthetic tryptamine derivatives commonly referred to as so-called new psychoactive substances (NPS). They have psychoactive effects that may be similar to those of other tryptamine derivatives. The objectives of this work were to study the metabolic fate and detectability, in urine, of DALT and 5-MeO-DALT. For metabolism studies, rat urine obtained after high-dose administration was prepared by precipitation and analyzed by liquid chromatography-high-resolution mass spectrometry (LC-HR-MS-MS). On the basis of the metabolites identified, several aromatic and aliphatic hydroxylations, N-dealkylation, N-oxidation, and combinations thereof are proposed as the main metabolic pathways for both compounds. O-Demethylation of 5-MeO-DALT was also observed, in addition to extensive glucuronidation or sulfation of both compounds after phase I transformation. The cytochrome P450 (CYP) isoenzymes predominantly involved in DALT metabolism were CYP2C19, CYP2D6, and CYP3A4; those mainly involved in 5-MeO-DALT metabolism were CYP1A2, CYP2C19, CYP2D6, and CYP3A4. For detectability studies, rat urine was screened by GC-MS, LC-MS(n), and LC-HR-MS-MS after administration of low doses. LC-MS(n) and LC-HR-MS-MS were deemed suitable for monitoring consumption of both compounds. The most abundant targets were a ring hydroxy metabolite of DALT, the N,O-bis-dealkyl metabolite of 5-MeO-DALT, and their glucuronides. GC-MS enabled screening of DALT by use of its main metabolites only.

Sensitivity of GC-EI/MS, GC-EI/MS/MS, LC-ESI/MS/MS, LC-Ag(+) CIS/MS/MS, and GC-ESI/MS/MS for analysis of anabolic steroids in doping control.

PubMed

Cha, Eunju; Kim, Sohee; Kim, Ho Jun; Lee, Kang Mi; Kim, Ki Hun; Kwon, Oh-Seung; Lee, Jaeick

2015-01-01

This study compared the sensitivity of various separation and ionization methods, including gas chromatography with an electron ionization source (GC-EI), liquid chromatography with an electrospray ionization source (LC-ESI), and liquid chromatography with a silver ion coordination ion spray source (LC-Ag(+) CIS), coupled to a mass spectrometer (MS) for steroid analysis. Chromatographic conditions, mass spectrometric transitions, and ion source parameters were optimized. The majority of steroids in GC-EI/MS/MS and LC-Ag(+) CIS/MS/MS analysis showed higher sensitivities than those obtained with other analytical methods. The limits of detection (LODs) of 65 steroids by GC-EI/MS/MS, 68 steroids by LC-Ag(+) CIS/MS/MS, 56 steroids by GC-EI/MS, 54 steroids by LC-ESI/MS/MS, and 27 steroids by GC-ESI/MS/MS were below cut-off value of 2.0 ng/mL. LODs of steroids that formed protonated ions in LC-ESI/MS/MS analysis were all lower than the cut-off value. Several steroids such as unconjugated C3-hydroxyl with C17-hydroxyl structure showed higher sensitivities in GC-EI/MS/MS analysis relative to those obtained using the LC-based methods. The steroids containing 4, 9, 11-triene structures showed relatively poor sensitivities in GC-EI/MS and GC-ESI/MS/MS analysis. The results of this study provide information that may be useful for selecting suitable analytical methods for confirmatory analysis of steroids. Copyright © 2015 John Wiley & Sons, Ltd.

Updates in metabolomics tools and resources: 2014-2015.

PubMed

Misra, Biswapriya B; van der Hooft, Justin J J

2016-01-01

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Separation and characterization of unknown impurities and isomers in flomoxef sodium by LC-IT-TOF MS and study of their negative-ion fragmentation regularities.

PubMed

Yu, Xu; Wang, Fan; Li, Jiani; Shan, Weiguang; Zhu, Bingqi; Wang, Jian

2017-06-05

Thirteen unknown impurities in flomoxef sodium were separated and characterized by liquid chromatography coupled with high resolution ion trap/time-of-flight mass spectrometry (LC-IT-TOF MS)with positive and negative modes of electrospray ionization method for further improvement of official monographs in pharmacopoeias. The fragmentation patterns of impurities in flomoxef in the negative ion mode were studied in detail, and new negative-ion fragmentation regularities were discovered. Chromatographic separation was performed on a Kromasil C18 column (250mm×4.6mm, 5μm). The mobile phase consisted of (A) ammonium formate aqueous solution (10mM)-methanol (84:16, v/v) and (B) ammonium formate aqueous solution (10mM)-methanol (47:53, v/v). In order to determine the m/z values of the molecular ions and formulas of all detected impurities, full scan LC-MS in both positive and negative ion modes was firstly executed to obtain the m/z value of the molecules. Then LC-MS 2 and LC-MS 3 were carried out on target compounds to obtain as much structural information as possible. Complete fragmentation patterns of impurities were studied and used to obtain information about the structures of these impurities. Structures of thirteen unknown degradation products in flomoxef sodium were deduced based on the high resolution MS n data with both positive and negative modes. The forming mechanisms of degradation products in flomoxef sodium were also studied. Copyright © 2017. Published by Elsevier B.V.

Integrated Omic Analysis of a Guinea Pig Model of Heart Failure and Sudden Cardiac Death.

PubMed

Foster, D Brian; Liu, Ting; Kammers, Kai; O'Meally, Robert; Yang, Ni; Papanicolaou, Kyriakos N; Talbot, C Conover; Cole, Robert N; O'Rourke, Brian

2016-09-02

Here, we examine key regulatory pathways underlying the transition from compensated hypertrophy (HYP) to decompensated heart failure (HF) and sudden cardiac death (SCD) in a guinea pig pressure-overload model by integrated multiome analysis. Relative protein abundances from sham-operated HYP and HF hearts were assessed by iTRAQ LC-MS/MS. Metabolites were quantified by LC-MS/MS or GC-MS. Transcriptome profiles were obtained using mRNA microarrays. The guinea pig HF proteome exhibited classic biosignatures of cardiac HYP, left ventricular dysfunction, fibrosis, inflammation, and extravasation. Fatty acid metabolism, mitochondrial transcription/translation factors, antioxidant enzymes, and other mitochondrial procsses, were downregulated in HF but not HYP. Proteins upregulated in HF implicate extracellular matrix remodeling, cytoskeletal remodeling, and acute phase inflammation markers. Among metabolites, acylcarnitines were downregulated in HYP and fatty acids accumulated in HF. The correlation of transcript and protein changes in HF was weak (R(2) = 0.23), suggesting post-transcriptional gene regulation in HF. Proteome/metabolome integration indicated metabolic bottlenecks in fatty acyl-CoA processing by carnitine palmitoyl transferase (CPT1B) as well as TCA cycle inhibition. On the basis of these findings, we present a model of cardiac decompensation involving impaired nuclear integration of Ca(2+) and cyclic nucleotide signals that are coupled to mitochondrial metabolic and antioxidant defects through the CREB/PGC1α transcriptional axis.

The future of targeted peptidomics.

PubMed

Findeisen, Peter

2013-12-01

Targeted MS is becoming increasingly important for sensitive and specific quantitative detection of proteins and respective PTMs. In this article, Ceglarek et al. [Proteomics Clin. Appl. 2013, 7, 794-801] present an LC-MS-based method for simultaneous quantitation of seven apolipoproteins in serum specimens. The assay fulfills many necessities of routine diagnostic applications, namely, low cost, high throughput, and good reproducibility. We anticipate that validation of new biomarkers will speed up with this technology and the palette of laboratory-based diagnostic tools will hopefully be augmented significantly in the near future. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Profiling pneumococcal type 3-derived oligosaccharides by high resolution liquid chromatography-tandem mass spectrometry

PubMed Central

Li, Guoyun; Li, Lingyun; Xue, Changhu; Middleton, Dustin; Linhardt, Robert J.; Avci, Fikri Y.

2015-01-01

Pneumococcal type-3 polysaccharide (Pn3P) is considered a major target for the development of a human vaccine to protect against Streptococcus pneumonia infection. Thus, it is critical to develop methods for the preparation and analysis of Pn3P-derived oligosaccharides to better understand its immunological properties. In this paper, we profile oligosaccharides, generated by the free radical depolymerization of Pn3P, using liquid chromatography (LC)-tandem mass spectrometry (MS/MS). Hydrophilic liquid interaction chromatography (HILIC)-mass spectrometry (MS) revealed a series of oligosaccharides with an even- and odd-number of saccharide residues, ranging from monosaccharide, degree of polymerization (dp1) to large oligosaccharides up to dp 20, generated by free radical depolymerization. Isomers of oligosaccharides with an even number of sugar residues were easily separated on a HILIC column, and their sequences could be distinguished by comparing MS/MS of these oligosaccharides and their reduced alditols. Fluorescent labeling with 2-aminoacridone (AMAC) followed by reversed phase (RP)-LC-MS/MS was applied to analyze and sequence poorly separated product mixtures, as RP-LC affords higher resolution of AMAC-labeled oligosaccharides than does HILIC-based separation. The present methodology can be potentially applied to profiling other capsular polysaccharides. PMID:25913329

Profiling pneumococcal type 3-derived oligosaccharides by high resolution liquid chromatography-tandem mass spectrometry.

PubMed

Li, Guoyun; Li, Lingyun; Xue, Changhu; Middleton, Dustin; Linhardt, Robert J; Avci, Fikri Y

2015-06-05

Pneumococcal type-3 polysaccharide (Pn3P) is considered a major target for the development of a human vaccine to protect against Streptococcus pneumoniae infection. Thus, it is critical to develop methods for the preparation and analysis of Pn3P-derived oligosaccharides to better understand its immunological properties. In this paper, we profile oligosaccharides, generated by the free radical depolymerization of Pn3P, using liquid chromatography (LC)-tandem mass spectrometry (MS/MS). Hydrophilic liquid interaction chromatography (HILIC)-mass spectrometry (MS) revealed a series of oligosaccharides with an even- and odd-number of saccharide residues, ranging from monosaccharide, degree of polymerization (dp1) to large oligosaccharides up to dp 20, generated by free radical depolymerization. Isomers of oligosaccharides with an even number of sugar residues were easily separated on a HILIC column, and their sequences could be distinguished by comparing MS/MS of these oligosaccharides and their reduced alditols. Fluorescent labeling with 2-aminoacridone (AMAC) followed by reversed phase (RP)-LC-MS/MS was applied to analyze and sequence poorly separated product mixtures, as RP-LC affords higher resolution of AMAC-labeled oligosaccharides than does HILIC-based separation. The present methodology can be potentially applied to profiling other capsular polysaccharides. Copyright © 2015 Elsevier B.V. All rights reserved.

LC-MS/MS imaging with thermal film-based laser microdissection.

PubMed

Oya, Michiko; Suzuki, Hiromi; Anas, Andrea Roxanne J; Oishi, Koichi; Ono, Kenji; Yamaguchi, Shun; Eguchi, Megumi; Sawada, Makoto

2018-01-01

Mass spectrometry (MS) imaging is a useful tool for direct and simultaneous visualization of specific molecules. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is used to evaluate the abundance of molecules in tissues using sample homogenates. To date, however, LC-MS/MS has not been utilized as an imaging tool because spatial information is lost during sample preparation. Here we report a new approach for LC-MS/MS imaging using a thermal film-based laser microdissection (LMD) technique. To isolate tissue spots, our LMD system uses a 808-nm near infrared laser, the diameter of which can be freely changed from 2.7 to 500 μm; for imaging purposes in this study, the diameter was fixed at 40 μm, allowing acquisition of LC-MS/MS images at a 40-μm resolution. The isolated spots are arranged on a thermal film at 4.5-mm intervals, corresponding to the well spacing on a 384-well plate. Each tissue spot is handled on the film in such a manner as to maintain its spatial information, allowing it to be extracted separately in its individual well. Using analytical LC-MS/MS in combination with the spatial information of each sample, we can reconstruct LC-MS/MS images. With this imaging technique, we successfully obtained the distributions of pilocarpine, glutamate, γ-aminobutyric acid, acetylcholine, and choline in a cross-section of mouse hippocampus. The protocol we established in this study is applicable to revealing the neurochemistry of pilocarpine model of epilepsy. Our system has a wide range of uses in fields such as biology, pharmacology, pathology, and neuroscience. Graphical abstract Schematic Indication of LMD-LC-MS/MS imaging.

Cartilaginous Metabolomic Study Reveals Potential Mechanisms of Osteophyte Formation in Osteoarthritis.

PubMed

Xu, Zhongwei; Chen, Tingmei; Luo, Jiao; Ding, Shijia; Gao, Sichuan; Zhang, Jian

2017-04-07

Osteophyte is one of the inevitable consequences of progressive osteoarthritis with the main characteristics of cartilage degeneration and endochondral ossification. The pathogenesis of osteophyte formation is not fully understood to date. In this work, metabolomic approaches were employed to explore potential mechanisms of osteophyte formation by detecting metabolic variations between extracts of osteophyte cartilage tissues (n = 32) and uninvolved control cartilage tissues (n = 34), based on the platform of ultraperformance liquid chromatography tandem quadrupole time-of-flight mass spectrometry, as well as the use of multivariate statistic analysis and univariate statistic analysis. The osteophyte group was significantly separated from the control group by the orthogonal partial least-squares discriminant analysis models, indicating that metabolic state of osteophyte cartilage had been changed. In total, 28 metabolic variations further validated by mass spectrum (MS) match, tandom mass spectrum (MS/MS) match, and standards match mainly included amino acids, sulfonic acids, glycerophospholipids, and fatty acyls. These metabolites were related to some specific physiological or pathological processes (collagen dissolution, boundary layers destroyed, self-restoration triggered, etc.) which might be associated with the procedure of osteophyte formation. Pathway analysis showed phenylalanine metabolism (PI = 0.168, p = 0.004) was highly correlative to this degenerative process. Our findings provided a direction for targeted metabolomic study and an insight into further reveal the molecular mechanisms of ostophyte formation.

Simultaneous quantification of protein phosphorylation sites using liquid chromatography-tandem mass spectrometry-based targeted proteomics: a linear algebra approach for isobaric phosphopeptides.

PubMed

Xu, Feifei; Yang, Ting; Sheng, Yuan; Zhong, Ting; Yang, Mi; Chen, Yun

2014-12-05

As one of the most studied post-translational modifications (PTM), protein phosphorylation plays an essential role in almost all cellular processes. Current methods are able to predict and determine thousands of phosphorylation sites, whereas stoichiometric quantification of these sites is still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics is emerging as a promising technique for site-specific quantification of protein phosphorylation using proteolytic peptides as surrogates of proteins. However, several issues may limit its application, one of which relates to the phosphopeptides with different phosphorylation sites and the same mass (i.e., isobaric phosphopeptides). While employment of site-specific product ions allows for these isobaric phosphopeptides to be distinguished and quantified, site-specific product ions are often absent or weak in tandem mass spectra. In this study, linear algebra algorithms were employed as an add-on to targeted proteomics to retrieve information on individual phosphopeptides from their common spectra. To achieve this simultaneous quantification, a LC-MS/MS-based targeted proteomics assay was first developed and validated for each phosphopeptide. Given the slope and intercept of calibration curves of phosphopeptides in each transition, linear algebraic equations were developed. Using a series of mock mixtures prepared with varying concentrations of each phosphopeptide, the reliability of the approach to quantify isobaric phosphopeptides containing multiple phosphorylation sites (≥ 2) was discussed. Finally, we applied this approach to determine the phosphorylation stoichiometry of heat shock protein 27 (HSP27) at Ser78 and Ser82 in breast cancer cells and tissue samples.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

PubMed

Burnum-Johnson, Kristin E; Nie, Song; Casey, Cameron P; Monroe, Matthew E; Orton, Daniel J; Ibrahim, Yehia M; Gritsenko, Marina A; Clauss, Therese R W; Shukla, Anil K; Moore, Ronald J; Purvine, Samuel O; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S; Smith, Richard D

2016-12-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Chromatographic behavior of co-eluted plasma compounds and effect on screening of drugs by APCI-LC-MS(/MS): Applications to selected cardiovascular drugs.

PubMed

Tahboub, Yahya R

2014-12-01

Chromatographic behavior of co-eluted compounds from un-extracted drug-free plasma samples was studied by LC-MS and LC-MS/MS with positive APCI. Under soft gradient, total ion chromatogram (TIC) consisted of two major peaks separated by a constant lower intensity region. Early peak (0.15-0.4 min) belongs to polar plasma compounds and consisted of smaller mass ions ( m / z <250); late peak (3.6-4.6 min) belongs to thermally unstable phospholipids and consisted of fragments with m / z <300. Late peak is more sensitive to variations in chromatographic and MS parameters. Screening of most targeted cardiovascular drugs at levels lower than 50 ng/mL has been possible by LC-MS for drugs with retention factors larger than three. Matrix effects and recovery, at 20 and 200 ng/mL, were evaluated for spiked plasma samples with 15 cardiovascular drugs, by MRM-LC-MS/MS. Average recoveries were above 90% and matrix effects expressed as percent matrix factor (% MF) were above 100%, indicating enhancement character for APCI. Large uncertainties were significant for drugs with smaller masses ( m / z <250) and retention factors lower than two.

(1)H NMR and GC-MS Based Metabolomics Reveal Defense and Detoxification Mechanism of Cucumber Plant under Nano-Cu Stress.

PubMed

Zhao, Lijuan; Huang, Yuxiong; Hu, Jerry; Zhou, Hongjun; Adeleye, Adeyemi S; Keller, Arturo A

2016-02-16

Because copper nanoparticles are being increasingly used in agriculture as pesticides, it is important to assess their potential implications for agriculture. Concerns have been raised about the bioaccumulation of nano-Cu and their toxicity to crop plants. Here, the response of cucumber plants in hydroponic culture at early development stages to two concentrations of nano-Cu (10 and 20 mg/L) was evaluated by proton nuclear magnetic resonance spectroscopy ((1)H NMR) and gas chromatography-mass spectrometry (GC-MS) based metabolomics. Changes in mineral nutrient metabolism induced by nano-Cu were determined by inductively coupled plasma-mass spectrometry (ICP-MS). Results showed that nano-Cu at both concentrations interferes with the uptake of a number of micro- and macro-nutrients, such as Na, P, S, Mo, Zn, and Fe. Metabolomics data revealed that nano-Cu at both levels triggered significant metabolic changes in cucumber leaves and root exudates. The root exudate metabolic changes revealed an active defense mechanism against nano-Cu stress: up-regulation of amino acids to sequester/exclude Cu/nano-Cu; down-regulation of citric acid to reduce the mobilization of Cu ions; ascorbic acid up-regulation to combat reactive oxygen species; and up-regulation of phenolic compounds to improve antioxidant system. Thus, we demonstrate that nontargeted (1)H NMR and GC-MS based metabolomics can successfully identify physiological responses induced by nanoparticles. Root exudates metabolomics revealed important detoxification mechanisms.

Determination of 17alpha-ethynylestradiol, carbamazepine, diazepam, simvastatin, and oxybenzone in fish livers.

PubMed

Kwon, Jeong-Wook; Armbrust, Kevin L; Vidal-Dorsch, Doris; Bay, Steven M

2009-01-01

A method using liquid chromatography/tandem mass spectrometry (LC/MS/MS) was developed for the determination of 17alpha-ethynylestradiol in fish liver; a second method using LC/MS was developed for the determination of carbamazepine, diazepam, simvastatin, and oxybenzone in fish liver. The fish liver samples were extracted and cleaned up by using liquid-liquid extraction and solid-phase extraction before the extracts were analyzed by LC/MS or LC/MS/MS with electrospray negative and positive ionization. Recoveries of the 5 target compounds from spiked catfish liver ranged from 72 +/- 2 to 100 +/- 3%. Limits of quantification for the 5 compounds were between 4.2 and 12.3 ng/g (wet weight). Ten turbot (Pleuronichthys verticalis) liver samples were analyzed; levels of 17alpha-ethynylestradiol, carbamazepine, simvastatin, and oxybenzone were below the detection limits. Diazepam was detected in all 10 fish liver samples at concentrations ranging from 23 to 110 ng/g (wet weight).

Review of sample preparation strategies for MS-based metabolomic studies in industrial biotechnology.

PubMed

Causon, Tim J; Hann, Stephan

2016-09-28

Fermentation and cell culture biotechnology in the form of so-called "cell factories" now play an increasingly significant role in production of both large (e.g. proteins, biopharmaceuticals) and small organic molecules for a wide variety of applications. However, associated metabolic engineering optimisation processes relying on genetic modification of organisms used in cell factories, or alteration of production conditions remain a challenging undertaking for improving the final yield and quality of cell factory products. In addition to genomic, transcriptomic and proteomic workflows, analytical metabolomics continues to play a critical role in studying detailed aspects of critical pathways (e.g. via targeted quantification of metabolites), identification of biosynthetic intermediates, and also for phenotype differentiation and the elucidation of previously unknown pathways (e.g. via non-targeted strategies). However, the diversity of primary and secondary metabolites and the broad concentration ranges encompassed during typical biotechnological processes means that simultaneous extraction and robust analytical determination of all parts of interest of the metabolome is effectively impossible. As the integration of metabolome data with transcriptome and proteome data is an essential goal of both targeted and non-targeted methods addressing production optimisation goals, additional sample preparation steps beyond necessary sampling, quenching and extraction protocols including clean-up, analyte enrichment, and derivatisation are important considerations for some classes of metabolites, especially those present in low concentrations or exhibiting poor stability. This contribution critically assesses the potential of current sample preparation strategies applied in metabolomic studies of industrially-relevant cell factory organisms using mass spectrometry-based platforms primarily coupled to liquid-phase sample introduction (i.e. flow injection, liquid chromatography, or capillary electrophoresis). Particular focus is placed on the selectivity and degree of enrichment attainable, as well as demands of speed, absolute quantification, robustness and, ultimately, consideration of fully-integrated bioanalytical solutions to optimise sample handling and throughput. Copyright © 2016 Elsevier B.V. All rights reserved.

Chip-LC-MS for label-free profiling of human serum.

PubMed

Horvatovich, Peter; Govorukhina, Natalia I; Reijmers, Theo H; van der Zee, Ate G J; Suits, Frank; Bischoff, Rainer

2007-12-01

The discovery of biomarkers in easily accessible body fluids such as serum is one of the most challenging topics in proteomics requiring highly efficient separation and detection methodologies. Here, we present the application of a microfluidics-based LC-MS system (chip-LC-MS) to the label-free profiling of immunodepleted, trypsin-digested serum in comparison to conventional capillary LC-MS (cap-LC-MS). Both systems proved to have a repeatability of approximately 20% RSD for peak area, all sample preparation steps included, while repeatability of the LC-MS part by itself was less than 10% RSD for the chip-LC-MS system. Importantly, the chip-LC-MS system had a two times higher resolution in the LC dimension and resulted in a lower average charge state of the tryptic peptide ions generated in the ESI interface when compared to cap-LC-MS while requiring approximately 30 times less (~5 pmol) sample. In order to characterize both systems for their capability to find discriminating peptides in trypsin-digested serum samples, five out of ten individually prepared, identical sera were spiked with horse heart cytochrome c. A comprehensive data processing methodology was applied including 2-D smoothing, resolution reduction, peak picking, time alignment, and matching of the individual peak lists to create an aligned peak matrix amenable for statistical analysis. Statistical analysis by supervised classification and variable selection showed that both LC-MS systems could discriminate the two sample groups. However, the chip-LC-MS system allowed to assign 55% of the overall signal to selected peaks against 32% for the cap-LC-MS system.

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

PubMed Central

Röst, Hannes L.; Liu, Yansheng; D’Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C.; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-01-01

Large scale, quantitative proteomic studies have become essential for the analysis of clinical cohorts, large perturbation experiments and systems biology studies. While next-generation mass spectrometric techniques such as SWATH-MS have substantially increased throughput and reproducibility, ensuring consistent quantification of thousands of peptide analytes across multiple LC-MS/MS runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we have developed the TRIC software which utilizes fragment ion data to perform cross-run alignment, consistent peak-picking and quantification for high throughput targeted proteomics. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate peak elution information from all LC-MS/MS runs acquired in a study. When compared to state-of-the-art SWATH-MS data analysis, the algorithm was able to reduce the identification error by more than 3-fold at constant recall, while correcting for highly non-linear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem (iPS) cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups and substantially increased the quantitative completeness and biological information in the data, providing insights into protein dynamics of iPS cells. Overall, this study demonstrates the importance of consistent quantification in highly challenging experimental setups, and proposes an algorithm to automate this task, constituting the last missing piece in a pipeline for automated analysis of massively parallel targeted proteomics datasets. PMID:27479329

An integrated platform for directly widely-targeted quantitative analysis of feces part I: Platform configuration and method validation.

PubMed

Song, Yuelin; Song, Qingqing; Li, Jun; Zheng, Jiao; Li, Chun; Zhang, Yuan; Zhang, Lingling; Jiang, Yong; Tu, Pengfei

2016-07-08

Direct analysis is of great importance to understand the real chemical profile of a given sample, notably biological materials, because either chemical degradation or diverse errors and uncertainties might be resulted from sophisticated protocols. In comparison with biofluids, it is still challenging for direct analysis of solid biological samples using high performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Herein, a new analytical platform was configured by online hyphenating pressurized liquid extraction (PLE), turbulent flow chromatography (TFC), and LC-MS/MS. A facile, but robust PLE module was constructed based on the phenomenon that noticeable back-pressure can be generated during rapid fluid passing through a narrow tube. TFC column that is advantageous at extracting low molecular analytes from rushing fluid was employed to link at the outlet of the PLE module to capture constituents-of-interest. An electronic 6-port/2-position valve was introduced between TFC column and LC-MS/MS to fragment each measurement into extraction and elution phases, whereas LC-MS/MS took the charge of analyte separation and monitoring. As a proof of concept, simultaneous determination of 24 endogenous substances including eighteen steroids, five eicosanoids, and one porphyrin in feces was carried out in this paper. Method validation assays demonstrated the analytical platform to be qualified for directly simultaneous measurement of diverse endogenous analytes in fecal matrices. Application of this integrated platform on homolog-focused profiling of feces is discussed in a companion paper. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of the Nutritional Quality of Chinese Kale (Brassica alboglabra Bailey) Using UHPLC-Quadrupole-Orbitrap MS/MS-Based Metabolomics.

PubMed

Wang, Ya-Qin; Hu, Li-Ping; Liu, Guang-Min; Zhang, De-Shuang; He, Hong-Ju

2017-07-27

Chinese kale ( Brassica alboglabra Bailey) is a widely consumed vegetable which is rich in antioxidants and anticarcinogenic compounds. Herein, we used an untargeted ultra-high-performance liquid chromatography (UHPLC)-Quadrupole-Orbitrap MS/MS-based metabolomics strategy to study the nutrient profiles of Chinese kale. Seven Chinese kale cultivars and three different edible parts were evaluated, and amino acids, sugars, organic acids, glucosinolates and phenolic compounds were analysed simultaneously. We found that two cultivars, a purple-stem cultivar W1 and a yellow-flower cultivar Y1, had more health-promoting compounds than others. The multivariate statistical analysis results showed that gluconapin was the most important contributor for discriminating both cultivars and edible parts. The purple-stem cultivar W1 had higher levels of some phenolic acids and flavonoids than the green stem cultivars. Compared to stems and leaves, the inflorescences contained more amino acids, glucosinolates and most of the phenolic acids. Meanwhile, the stems had the least amounts of phenolic compounds among the organs tested. Metabolomics is a powerful approach for the comprehensive understanding of vegetable nutritional quality. The results provide the basis for future metabolomics-guided breeding and nutritional quality improvement.

ROMANCE: A new software tool to improve data robustness and feature identification in CE-MS metabolomics.

PubMed

González-Ruiz, Víctor; Gagnebin, Yoric; Drouin, Nicolas; Codesido, Santiago; Rudaz, Serge; Schappler, Julie

2018-05-01

The use of capillary electrophoresis coupled to mass spectrometry (CE-MS) in metabolomics remains an oddity compared to the widely adopted use of liquid chromatography. This technique is traditionally regarded as lacking the reproducibility to adequately identify metabolites by their migration times. The major reason is the variability of the velocity of the background electrolyte, mainly coming from shifts in the magnitude of the electroosmotic flow and from the suction caused by electrospray interfaces. The use of the effective electrophoretic mobility is one solution to overcome this issue as it is a characteristic feature of each compound. To date, such an approach has not been applied to metabolomics due to the complexity and size of CE-MS data obtained in such studies. In this paper, ROMANCE (RObust Metabolomic Analysis with Normalized CE) is introduced as a new software for CE-MS-based metabolomics. It allows the automated conversion of batches of CE-MS files with minimal user intervention. ROMANCE converts the x-axis of each MS file from the time into the effective mobility scale and the resulting files are already pseudo-aligned, present normalized peak areas and improved reproducibility, and can eventually follow existing metabolomic workflows. The software was developed in Scala, so it is multi-platform and computationally-efficient. It is available for download under a CC license. In this work, the versatility of ROMANCE was demonstrated by using data obtained in the same and in different laboratories, as well as its application to the analysis of human plasma samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Shifts in plant foliar and floral metabolomes in response to the suppression of the associated microbiota.

PubMed

Gargallo-Garriga, Albert; Sardans, Jordi; Pérez-Trujillo, Míriam; Guenther, Alex; Llusià, Joan; Rico, Laura; Terradas, Jaume; Farré-Armengol, Gerard; Filella, Iolanda; Parella, Teodor; Peñuelas, Josep

2016-04-06

The phyllospheric microbiota is assumed to play a key role in the metabolism of host plants. Its role in determining the epiphytic and internal plant metabolome, however, remains to be investigated. We analyzed the Liquid Chromatography-Mass Spectrometry (LC-MS) profiles of the epiphytic and internal metabolomes of the leaves and flowers of Sambucus nigra with and without external antibiotic treatment application. The epiphytic metabolism showed a degree of complexity similar to that of the plant organs. The suppression of microbial communities by topical applications of antibiotics had a greater impact on the epiphytic metabolome than on the internal metabolomes of the plant organs, although even the latter changed significantly both in leaves and flowers. The application of antibiotics decreased the concentration of lactate in both epiphytic and organ metabolomes, and the concentrations of citraconic acid, acetyl-CoA, isoleucine, and several secondary compounds such as terpenes and phenols in the epiphytic extracts. The metabolite pyrogallol appeared in the floral epiphytic community only after the treatment. The concentrations of the amino acid precursors of the ketoglutarate-synthesis pathway tended to decrease in the leaves and to increase in the foliar epiphytic extracts. These results suggest that anaerobic and/or facultative anaerobic bacteria were present in high numbers in the phyllosphere and in the apoplasts of S. nigra. The results also show that microbial communities play a significant role in the metabolomes of plant organs and could have more complex and frequent mutualistic, saprophytic, and/or parasitic relationships with internal plant metabolism than currently assumed.

Reduction in cardiometabolic risk factors by a multifunctional diet is mediated via several branches of metabolism as evidenced by nontargeted metabolite profiling approach.

PubMed

Tovar, Juscelino; de Mello, Vanessa D; Nilsson, Anne; Johansson, Maria; Paananen, Jussi; Lehtonen, Marko; Hanhineva, Kati; Björck, Inger

2017-02-01

Multifunctional diet (MFD), a diet based on multiple functional concepts and ingredients with anti-inflammatory activity, was previously shown to improve different cardiometabolic risk-associated markers in healthy subjects. Here, we assessed the impact of MFD on plasma metabolome and explored associations of the differential metabolites with clinical parameters, searching for metabolic determinants related to the effects of MFD. Forty-four overweight healthy volunteers completed a randomized crossover intervention comparing MFD with a control diet devoid of the active components of MFD. Fasting plasma samples were analyzed with nontargeted metabolite profiling at baseline and at the end (4 wk) of each diet period by LC coupled to quadrupole-TOF-MS system, revealing a vast impact of MFD on metabolic homeostasis. Main metabolite classes affected included acylcarnitines, furan fatty acids, phospholipids (plasmalogens, phosphatidylcholines, phosphatidylethanolamines), and various low-molecular weight products from the bioactivity of gut microbiota. Circulating levels of several of these metabolites correlated with changes in clinical blood lipid biomarkers. The metabolomics approach revealed that consumption of MFD affected different areas of metabolism, highlighting the impact of a healthy diet on plasma metabolome. This seems linked to reduced cardiometabolic risk and provides mechanistic insight into the effects of MFD. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GC-TOF/MS-based metabolomic profiling of estrogen deficiency-induced obesity in ovariectomized rats

PubMed Central

Ma, Bo; Zhang, Qi; Wang, Guang-ji; A, Ji-ye; Wu, Di; Liu, Ying; Cao, Bei; Liu, Lin-sheng; Hu, Ying-ying; Wang, Yong-lu; Zheng, Ya-ya

2011-01-01

Aim: To explore the alteration of endogenous metabolites and identify potential biomarkers using metabolomic profiling with gas chromatography coupled a time-of-flight mass analyzer (GC/TOF-MS) in a rat model of estrogen-deficiency-induced obesity. Methods: Twelve female Sprague-Dawley rats six month of age were either sham-operated or ovariectomized (OVX). Rat blood was collected, and serum was analyzed for biomarkers using standard colorimetric methods with commercial assay kits and a metabolomic approach with GC/TOF-MS. The data were analyzed using multivariate statistical techniques. Results: A high body weight and body mass index inversely correlated with serum estradiol (E2) in the OVX rats compared to the sham rats. Estrogen deficiency also significantly increased serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol. Utilizing GC/TOF-MS-based metabolomic analysis and the partial least-squares discriminant analysis, the OVX samples were discriminated from the shams. Elevated levels of cholesterol, glycerol, glucose, arachidonic acid, glutamic acid, glycine, and cystine and reduced alanine levels were observed. Serum glucose metabolism, energy metabolism, lipid metabolism, and amino acid metabolism were involved in estrogen-deficiency-induced obesity in OVX rats. Conclusion: The series of potential biomarkers identified in the present study provided fingerprints of rat metabolomic changes during obesity and an overview of multiple metabolic pathways during the progression of obesity involving glucose metabolism, lipid metabolism, and amino acid metabolism. PMID:21293480

Mass spectrometry as a quantitative tool in plant metabolomics

PubMed Central

Jorge, Tiago F.; Mata, Ana T.

2016-01-01

Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644967

Direct-injection screening for acidic drugs in plasma and neutral drugs in equine urine by differential-gradient LC-LC coupled MS/MS.

PubMed

Stanley, Shawn M R; Wee, Wei Khee; Lim, Boon Huat; Foo, Hsiao Ching

2007-04-01

Direct-injection LC-LC hybrid tandem MS methods have been developed for undertaking broad-based screening for acidic drugs in protein-precipitated plasma and neutral doping agents in equine urine. In both analyses, analytes present in the matrix were trapped using a HLB extraction column before being refocused and separated on a Chromolith RP-18e monolithic analytical column using a controlled differential gradient generated by proportional dilution of the first column's eluent with water. Each method has been optimised by the adoption of a mobile phase and gradient that was tailored to enhance ionisation in the MS source while maintaining good chromatographic behaviour for the majority of the target drugs. The analytical column eluent was fed into the heated nebulizer (HN) part of the Duospray interface attached to a 4000 QTRAP mass spectrometer. Information dependent acquisition (IDA) with dynamic background subtraction (DBS) was configured to trigger a sensitive enhanced product ion (EPI) scan when a multiple reaction monitoring (MRM) survey scan signal exceeded the defined criteria. Ninety-one percent of acidic drugs in protein-precipitated plasma and 80% of the neutral compounds in equine urine were detected when spiked at 10 ng/ml.

Effects of N source concentration and NH4(+)/NO3(-) ratio on phenylethanoid glycoside pattern in tissue cultures of Plantago lanceolata L.: a metabolomics driven full-factorial experiment with LC-ESI-MS(3.).

PubMed

Gonda, Sándor; Kiss-Szikszai, Attila; Szűcs, Zsolt; Máthé, Csaba; Vasas, Gábor

2014-10-01

Tissue cultures of a medicinal plant, Plantago lanceolata L. were screened for phenylethanoid glycosides (PGs) and other natural products (NPs) with LC-ESI-MS(3). The effects of N source concentration and NH4(+)/NO3(-) ratio were evaluated in a full-factorial (FF) experiment. N concentrations of 10, 20, 40 and 60mM, and NH4(+)/NO3(-) ratios of 0, 0.11, 0.20 and 0.33 (ratio of NH4(+) in total N source) were tested. Several peaks could be identified as PGs, of which, 16 could be putatively identified from the MS/MS/MS spectra. N source concentration and NH4(+)/NO3(-) ratio had significant effects on the metabolome, their effects on individual PGs were different despite these metabolites were of the same biosynthethic class. Chief PGs were plantamajoside and acteoside (verbascoside), their highest concentrations were 3.54±0.83% and 1.30±0.40% of dry weight, on media 10(0.33) and 40(0.33), respectively. NH4(+)/NO3(-) ratio and N source concentration effects were examined on a set of 89 NPs. For most NPs, high increases in abundance were observed compared to Murashige-Skoog medium. Abundances of 42 and 10 NPs were significantly influenced by the N source concentration and the NH4(+)/NO3(-) ratio, respectively. Optimal media for production of different NP clusters were 10(0), 10(0.11) and 40(0.33). Interaction was observed between NH4(+)/NO3(-) ratio and N source concentration for many NPs. It was shown in simulated experiments, that one-factor at a time (OFAT) experimental designs lead to sub-optimal media compositions for production of many NPs, and alternative experimental designs (e.g. FF) should be preferred when optimizing medium N source for optimal yield of NPs. If using OFAT, the N source concentration is to be optimized first, followed by NH4(+)/NO3(-) ratio, as this reduces the likeliness of suboptimal yield results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

PubMed

Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context

PubMed Central

Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group. PMID:29324799

Screening of 23 β-lactams in foodstuffs by LC-MS/MS using an alkaline QuEChERS-like extraction.

PubMed

Bessaire, Thomas; Mujahid, Claudia; Beck, Andrea; Tarres, Adrienne; Savoy, Marie-Claude; Woo, Pei-Mun; Mottier, Pascal; Desmarchelier, Aurélien

2018-04-01

A fast and robust high performance LC-MS/MS screening method was developed for the analysis of β-lactam antibiotics in foods of animal origin: eggs, raw milk, processed dairy ingredients, infant formula, and meat- and fish-based products including baby foods. QuEChERS extraction with some adaptations enabled 23 drugs to be simultaneously monitored. Screening target concentrations were set at levels adequate to ensure compliance with current European, Chinese, US and Canadian regulations. The method was fully validated according to the European Community Reference Laboratories Residues Guidelines using 93 food samples of different composition. False-negative and false-positive rates were below 5% for all analytes. The method is adequate for use in high-routine laboratories. A 1-year study was additionally conducted to assess the stability of the 23 analytes in the working standard solution.

LC-MS/MS Identification of Species-Specific Muscle Peptides in Processed Animal Proteins.

PubMed

Marchis, Daniela; Altomare, Alessandra; Gili, Marilena; Ostorero, Federica; Khadjavi, Amina; Corona, Cristiano; Ru, Giuseppe; Cappelletti, Benedetta; Gianelli, Silvia; Amadeo, Francesca; Rumio, Cristiano; Carini, Marina; Aldini, Giancarlo; Casalone, Cristina

2017-12-06

An innovative analytical strategy has been applied to identify signature peptides able to distinguish among processed animal proteins (PAPs) derived from bovine, pig, fish, and milk products. Proteomics was first used to elucidate the proteome of each source. Starting from the identified proteins and using a funnel based approach, a set of abundant and well characterized peptides with suitable physical-chemical properties (signature peptides) and specific for each source was selected. An on-target LC-ESI-MS/MS method (MRM mode) was set up using standard peptides and was then applied to selectively identify the PAP source and also to distinguish proteins from bovine carcass and milk proteins. We believe that the method described meets the request of the European Commission which has developed a strategy for gradually lifting the "total ban" toward "species to species ban", therefore requiring official methods for species-specific discrimination in feed.

A novel NMR-based assay to measure circulating concentrations of branched-chain amino acids: Elevation in subjects with type 2 diabetes mellitus and association with carotid intima media thickness.

PubMed

Wolak-Dinsmore, Justyna; Gruppen, Eke G; Shalaurova, Irina; Matyus, Steven P; Grant, Russell P; Gegen, Ray; Bakker, Stephan J L; Otvos, James D; Connelly, Margery A; Dullaart, Robin P F

2018-04-01

Plasma branched-chain amino acid (BCAA) levels, measured on nuclear magnetic resonance (NMR) metabolomics research platforms or by mass spectrometry, have been shown to be associated with type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). We developed a new test for quantification of BCAA on a clinical NMR analyzer and used this test to determine the clinical correlates of BCAA in 2 independent cohorts. The performance of the NMR-based BCAA assay was evaluated. A method comparison study was performed with mass spectrometry (LC-MS/MS). Plasma BCAA were measured in the Insulin Resistance Atherosclerosis Study (IRAS, n = 1209; 376 T2DM subjects) and in a Groningen cohort (n = 123; 67 T2DM subjects). In addition, carotid intima media thickness (cIMT) was measured successfully in 119 subjects from the Groningen cohort. NMR-based BCAA assay results were linear over a range of concentrations. Coefficients of variation for inter- and intra-assay precision ranged from 1.8-6.0, 1.7-5.4, 4.4-9.1, and 8.8-21.3%, for total BCAA, valine, leucine, and isoleucine, respectively. BCAA quantified from the same samples using NMR and LC-MS/MS were highly correlated (R 2  = 0.97, 0.95 and 0.90 for valine, leucine and isoleucine). In both cohorts total and individual BCAA were elevated in T2DM (P = 0.01 to ≤0.001). Moreover, cIMT was associated with BCAA independent of age, sex, T2DM and metabolic syndrome (MetS) categorization or alternatively of individual MetS components. BCAA levels, measured by NMR in the clinical laboratory, are elevated in T2DM and may be associated with cIMT, a proxy of subclinical atherosclerosis. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data.

PubMed

Kyle, Jennifer E; Crowell, Kevin L; Casey, Cameron P; Fujimoto, Grant M; Kim, Sangtae; Dautel, Sydney E; Smith, Richard D; Payne, Samuel H; Metz, Thomas O

2017-06-01

We introduce an open-source software, LIQUID, for semi-automated processing and visualization of LC-MS/MS-based lipidomics data. LIQUID provides users with the capability to process high throughput data and contains a customizable target library and scoring model per project needs. The graphical user interface provides visualization of multiple lines of spectral evidence for each lipid identification, allowing rapid examination of data for making confident identifications of lipid molecular species. LIQUID was compared to other freely available software commonly used to identify lipids and other small molecules (e.g. CFM-ID, MetFrag, GNPS, LipidBlast and MS-DIAL), and was found to have a faster processing time to arrive at a higher number of validated lipid identifications. LIQUID is available at http://github.com/PNNL-Comp-Mass-Spec/LIQUID . jennifer.kyle@pnnl.gov or thomas.metz@pnnl.gov. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

LC-MS/MS quantification of next-generation biotherapeutics: a case study for an IgE binding Nanobody in cynomolgus monkey plasma.

PubMed

Sandra, Koen; Mortier, Kjell; Jorge, Lucie; Perez, Luis C; Sandra, Pat; Priem, Sofie; Poelmans, Sofie; Bouche, Marie-Paule

2014-05-01

Nanobodies(®) are therapeutic proteins derived from the smallest functional fragments of heavy chain-only antibodies. The development and validation of an LC-MS/MS-based method for the quantification of an IgE binding Nanobody in cynomolgus monkey plasma is presented. Nanobody quantification was performed making use of a proteotypic tryptic peptide chromatographically enriched prior to LC-MS/MS analysis. The validated LLOQ at 36 ng/ml was measured with an intra- and inter-assay precision and accuracy <20%. The required sensitivity could be obtained based on the selectivity of 2D LC combined with MS/MS. No analyte specific tools for affinity purification were used. Plasma samples originating from a PK/PD study were analyzed and compared with the results obtained with a traditional ligand-binding assay. Excellent correlations between the two techniques were obtained, and similar PK parameters were estimated. A 2D LC-MS/MS method was successfully developed and validated for the quantification of a next generation biotherapeutic.

Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era.

PubMed

Zhou, Zhiwei; Tu, Jia; Zhu, Zheng-Jiang

2018-02-01

Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Advances in computational metabolomics and databases deepen the understanding of metabolisms.

PubMed

Tsugawa, Hiroshi

2018-01-29

Mass spectrometry (MS)-based metabolomics is the popular platform for metabolome analyses. Computational techniques for the processing of MS raw data, for example, feature detection, peak alignment, and the exclusion of false-positive peaks, have been established. The next stage of untargeted metabolomics would be to decipher the mass fragmentation of small molecules for the global identification of human-, animal-, plant-, and microbiota metabolomes, resulting in a deeper understanding of metabolisms. This review is an update on the latest computational metabolomics including known/expected structure databases, chemical ontology classifications, and mass spectrometry cheminformatics for the interpretation of mass fragmentations and for the elucidation of unknown metabolites. The importance of metabolome 'databases' and 'repositories' is also discussed because novel biological discoveries are often attributable to the accumulation of data, to relational databases, and to their statistics. Lastly, a practical guide for metabolite annotations is presented as the summary of this review. Copyright © 2018 Elsevier Ltd. All rights reserved.

Boosting Sensitivity in Liquid Chromatography–Fourier Transform Ion Cyclotron Resonance–Tandem Mass Spectrometry for Product Ion Analysis of Monoterpene Indole Alkaloids

PubMed Central

Nakabayashi, Ryo; Tsugawa, Hiroshi; Kitajima, Mariko; Takayama, Hiromitsu; Saito, Kazuki

2015-01-01

In metabolomics, the analysis of product ions in tandem mass spectrometry (MS/MS) is noteworthy to chemically assign structural information. However, the development of relevant analytical methods are less advanced. Here, we developed a method to boost sensitivity in liquid chromatography–Fourier transform ion cyclotron resonance–tandem mass spectrometry analysis (MS/MS boost analysis). To verify the MS/MS boost analysis, both quercetin and uniformly labeled 13C quercetin were analyzed, revealing that the origin of the product ions is not the instrument, but the analyzed compounds resulting in sensitive product ions. Next, we applied this method to the analysis of monoterpene indole alkaloids (MIAs). The comparative analyses of MIAs having indole basic skeleton (ajmalicine, catharanthine, hirsuteine, and hirsutine) and oxindole skeleton (formosanine, isoformosanine, pteropodine, isopteropodine, rhynchophylline, isorhynchophylline, and mitraphylline) identified 86 and 73 common monoisotopic ions, respectively. The comparative analyses of the three pairs of stereoisomers showed more than 170 common monoisotopic ions in each pair. This method was also applied to the targeted analysis of MIAs in Catharanthus roseus and Uncaria rhynchophylla to profile indole and oxindole compounds using the product ions. This analysis is suitable for chemically assigning features of the metabolite groups, which contributes to targeted metabolome analysis. PMID:26734034

Determination of target fat-soluble micronutrients in rainbow trout's muscle and liver tissues by liquid chromatography with diode array-tandem mass spectrometry detection.

PubMed

Pérez Fernández, Virginia; Ventura, Salvatore; Tomai, Pierpaolo; Curini, Roberta; Gentili, Alessandra

2017-03-01

This paper describes an analytical approach, based on LC-diode array detector-MS/MS (LC-DAD-MS/MS), for characterizing the fat-soluble micronutrient fraction in rainbow trout (Oncorhynchus mykiss). Two different procedures were applied to isolate the analytes from liver and muscle tissue: overnight cold saponification to hydrolyze bound forms and to simplify the analysis; matrix solid-phase dispersion to avoid artifacts and to maintain unaltered the naturally occurring forms. Analytes were separated on a C 30 analytical column by using a nonaqueous reversed mobile phase compatible with the atmospheric pressure chemical ionization. Compared to other works, the most relevant advantage of the here illustrated method is the large amount of information obtained with few analytical steps: nine fat-soluble vitamins (3,4-dehydroretinol, retinol, cholecalciferol, ergocalciferol, α-tocopherol, γ-tocopherol, δ-tocopherol, phylloquinone, and menaquinone-4) and eight carotenoids (all-trans-lutein, all-trans-astaxanthin, all-trans-zeaxanthin, all-trans-β-cryptoxanthin, all-trans-canthaxanthin, all-trans-ζ-carotene, all-trans-β-carotene, and all-trans-γ-carotene) were quantified after the method validation, while other untargeted carotenoids were tentatively identified by exploiting the identification power of the LC-DAD-MS/MS hyphenation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping of the circulating metabolome reveals α-ketoglutarate as a predictor of morbid obesity-associated non-alcoholic fatty liver disease.

PubMed

Rodríguez-Gallego, E; Guirro, M; Riera-Borrull, M; Hernández-Aguilera, A; Mariné-Casadó, R; Fernández-Arroyo, S; Beltrán-Debón, R; Sabench, F; Hernández, M; del Castillo, D; Menendez, J A; Camps, J; Ras, R; Arola, L; Joven, J

2015-02-01

Obesity severely affects human health, and the accompanying non-alcoholic fatty liver disease (NAFLD) is associated with high morbidity and mortality. Rapid and non-invasive methods to detect this condition may substantially improve clinical care. We used liquid and gas chromatography-quadruple time-of-flight-mass spectrometry (LC/GC-QTOF-MS) analysis in a non-targeted metabolomics approach on the plasma from morbidly obese patients undergoing bariatric surgery to gain a comprehensive measure of metabolite levels. On the basis of these findings, we developed a method (GC-QTOF-MS) for the accurate quantification of plasma α-ketoglutarate to explore its potential as a novel biomarker for the detection of NAFLD. Plasma biochemical differences were observed between patients with and without NAFLD indicating that the accumulation of lipids in hepatocytes decreased β-oxidation energy production, reduced liver function and altered glucose metabolism. The results obtained from the plasma analysis suggest pathophysiological insights that link lipid and glucose disturbances with α-ketoglutarate. Plasma α-ketoglutarate levels are significantly increased in obese patients compared with lean controls. Among obese patients, the measurement of this metabolite differentiates between those with or without NAFLD. Data from the liver were consistent with data from plasma. Clinical utility was assessed, and the results revealed that plasma α-ketoglutarate is a fair-to-good biomarker in patients (n=230). Other common laboratory liver tests used in routine application did not favourably compare. Plasma α-ketoglutarate is superior to common liver function tests in obese patients as a surrogate biomarker of NAFLD. The measurement of this biomarker may potentiate the search for a therapeutic approach, may decrease the need for liver biopsy and may be useful in the assessment of disease progression.

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

PubMed

Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-10-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

PubMed Central

Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-01-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

Metabolomic approach for determination of key volatile compounds related to beef flavor in glutathione-Maillard reaction products.

PubMed

Lee, Sang Mi; Kwon, Goo Young; Kim, Kwang-Ok; Kim, Young-Suk

2011-10-10

The non-targeted analysis, combining gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF/MS) and sensory evaluation, was applied to investigate the relationship between volatile compounds and the sensory attributes of glutathione-Maillard reaction products (GSH-MRPs) prepared under different reaction conditions. Volatile compounds in GSH-MRPs correlating to the sensory attributes were determined using partial least-squares (PLS) regression. Volatile compounds such as 2-methylfuran-3-thiol, 3-sulfanylpentan-2-one, furan-2-ylmethanethiol, 2-propylpyrazine, 1-furan-2-ylpropan-2-one, 1H-pyrrole, 2-methylthiophene, and 2-(furan-2-ylmethyldisulfanylmethyl)furan could be identified as possible key contributors to the beef-related attributes of GSH-MRPs. In this study, we demonstrated that the unbiased non-targeted analysis based on metabolomic approach allows the identification of key volatile compounds related to beef flavor in GSH-MRPs. Copyright © 2011 Elsevier B.V. All rights reserved.

Identifying novel radiotracers for PET imaging of the brain: application of LC-MS/MS to tracer identification.

PubMed

Barth, Vanessa; Need, Anne

2014-12-17

Nuclear medicine imaging biomarker applications are limited by the radiotracers available. Radiotracers enable the measurement of target engagement, or occupancy in relation to plasma exposure. These tracers can also be used as pharmacodynamic biomarkers to demonstrate functional consequences of binding a target. More recently, radiotracers have also been used for patient tailoring in Alzheimer's disease seen with amyloid imaging. Radiotracers for the central nervous system (CNS) are challenging to identify, as they require a unique intersection of multiple properties. Recent advances in tangential technologies, along with the use of iterative learning for the purposes of deriving in silico models, have opened up additional opportunities to identify radiotracers. Mass spectral technologies and in silico modeling have made it possible to measure and predict in vivo characteristics of molecules to indicate potential tracer performance. By analyzing these data alongside other measures, it is possible to delineate guidelines to increase the likelihood of selecting compounds that can perform as radiotracers or serve as the best starting point to develop a radiotracer following additional structural modification. The application of mass spectrometry based technologies is an efficient way to evaluate compounds as tracers in vivo, but more importantly enables the testing of potential tracers that have either no label site or complex labeling chemistry which may deter assessment by traditional means; therefore, use of this technology allows for more rapid iterative learning. The ability to differentially distribute toward target rich tissues versus tissue with no/less target present is a unique defining feature of a tracer. By testing nonlabeled compounds in vivo and analyzing tissue levels by LC-MS/MS, rapid assessment of a compound's ability to differentially distribute in a manner consistent with target expression biology guides the focus of chemistry resources for both designing and labeling tracer candidates. LC-MS/MS has only recently been used for de novo tracer identification; however, this connection of mass spectral technology to imaging has initiated engagement from a wider community that brings diverse backgrounds into the tracer discovery arena.

Two-dimensional turbulent flow chromatography coupled on-line to liquid chromatography-mass spectrometry for solution-based ligand screening against multiple proteins.

PubMed

Zhou, Jian-Liang; An, Jing-Jing; Li, Ping; Li, Hui-Jun; Jiang, Yan; Cheng, Jie-Fei

2009-03-20

We present herein a novel bioseparation/chemical analysis strategy for protein-ligand screening and affinity ranking in compound mixtures, designed to increase screening rates and improve sensitivity and ruggedness in performance. The strategy is carried out by combining on-line two-dimensional turbulent flow chromatography (2D-TFC) with liquid chromatography-mass spectrometry (LC-MS), and accomplished through the following steps: (1) a reversed-phase TFC stage to separate the protein/ligand complex from the unbound free molecules, (2) an on-line dissociation process to release the bound ligands from the complexes, and (3) a second mixed-mode cation-exchange/reversed-phase TFC stage to trap the bound ligands and to remove the proteins and salts, followed by LC-MS analysis for identification and determination of the binding affinities. The technique can implement an ultra-fast isolation of protein/ligand complex with the retention time of a complex peak in about 5s, and on-line prepare the "clean" sample to be directly compatible with the LC-MS analysis. The improvement in performance of this 2D-TFC/LC-MS approach over the conventional approach has been demonstrated by determining affinity-selected ligands of the target proteins acetylcholinesterase and butyrylcholinesterase from a small library with known binding affinities and a steroidal alkaloid library composed of structurally similar compounds. Our results show that 2D-TFC/LC-MS is a generic and efficient tool for high-throughput screening of ligands with low-to-high binding affinities, and structure-activity relationship evaluation.

Multiple reaction monitoring targeted LC-MS analysis of potential cell death marker proteins for increased bioprocess control.

PubMed

Albrecht, Simone; Kaisermayer, Christian; Reinhart, David; Ambrose, Monica; Kunert, Renate; Lindeberg, Anna; Bones, Jonathan

2018-05-01

The monitoring of protein biomarkers for the early prediction of cell stress and death is a valuable tool for process characterization and efficient biomanufacturing control. A representative set of six proteins, namely GPDH, PRDX1, LGALS1, CFL1, TAGLN2 and MDH, which were identified in a previous CHO-K1 cell death model using discovery LC-MS E was translated into a targeted liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM-MS) platform and verified. The universality of the markers was confirmed in a cell growth model for which three Chinese hamster ovary host cell lines (CHO-K1, CHO-S, CHO-DG44) were grown in batch culture in two different types of basal media. LC-MRM-MS was also applied to spent media (n = 39) from four perfusion biomanufacturing series. Stable isotope-labelled peptide analogues and a stable isotope-labelled monoclonal antibody were used for improved protein quantitation and simultaneous monitoring of the workflow reproducibility. Significant increases in protein concentrations were observed for all viability marker proteins upon increased dead cell numbers and allowed for discrimination of spent media with dead cell densities below and above 1 × 10 6  dead cells/mL which highlights the potential of the selected viability marker proteins in bioprocess control. Graphical abstract Overview of the LC-MRM-MS workflow for the determination of proteomic markers in conditioned media from the bioreactor that correlate with CHO cell death.

[Rapid identification of 22 abused drugs and organophosphorus pesticides in blood by LC-MS/MS].

PubMed

Liu, Hong-tao; Ma, An-de

2009-08-01

To develop a method for rapid identification of 22 abused drugs and organophosphorus pesticides in the blood. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple-reaction monitoring mode (MRM) was employed for detecting the drugs and pesticides in the blood. The MRM database and criteria for identification were established, and ethyl acetate was used for extraction of the drugs. After 3 rounds of extractions of the blood sample (1 mL) using 2 mL ethyl acetate, the extract was vortexed for 3 min and centrifuged at 5000 r/min. Each organic phase was combined and evaporated by gentle N2 gas. The residue was re-dissolved in 100 L mobile phase, from which 5 L was taken for LC-MS/MS detection. The detection of the 22 target compounds could be completed within 10 min. The limit of detection of the target compound ranged from 0.03 to 6.00 ng/ml. Satisfactory results were obtained in proficiency testing program organized by China National Accreditation Service for Conformity Assessment. The method we established is rapid, selective and sensitive for detecting the 22 abused drugs and organophosphorus pesticides.

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

NASA Astrophysics Data System (ADS)

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

2018-05-01

In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

Determination of 105 antibiotic, anti-inflammatory, antiparasitic agents and tranquilizers by LC-MS/MS based on an acidic QuEChERS-like extraction.

PubMed

Desmarchelier, Aurélien; Fan, Kaïli; Minh Tien, Mai; Savoy, Marie-Claude; Tarres, Adrienne; Fuger, Denis; Goyon, Alexandre; Bessaire, Thomas; Mottier, Pascal

2018-04-01

A procedure for screening 105 veterinary drugs in foods by liquid chromatography tandem mass-spectrometry (LC-MS/MS) is presented. Its scope encompasses raw materials of animal origin (milk, meat, fish, egg and fat) but also related processed ingredients and finished products commonly used and manufactured by food business operators. Due to the complexity of the matrices considered and to efficiently deal with losses during extraction and matrix effects during MS source ionisation, each sample was analysed twice, that is 'unspiked' and 'spiked at the screening target concentration' using a QuEChERS-like extraction. The entire procedure was validated according to the European Community Reference Laboratories Residues Guidelines. False-negative and false-positive rates were below 5% for all veterinary drugs whatever the food matrix. Effectiveness of the procedure was further demonstrated through participation to five proficiency tests and its ruggedness demonstrated in quality control operations by a second laboratory.

Immobilized magnetic beads-based multi-target affinity selection coupled with HPLC-MS for screening active compounds from traditional Chinese medicine and natural products.

PubMed

Chen, Yaqi; Chen, Zhui; Wang, Yi

2015-01-01

Screening and identifying active compounds from traditional Chinese medicine (TCM) and other natural products plays an important role in drug discovery. Here, we describe a magnetic beads-based multi-target affinity selection-mass spectrometry approach for screening bioactive compounds from natural products. Key steps and parameters including activation of magnetic beads, enzyme/protein immobilization, characterization of functional magnetic beads, screening and identifying active compounds from a complex mixture by LC/MS, are illustrated. The proposed approach is rapid and efficient in screening and identification of bioactive compounds from complex natural products.

Characterization of inhibitory constituents of NO production from Catalpa ovata using LC-MS coupled with a cell-based assay.

PubMed

Park, Sangmin; Shin, Hyeji; Park, Yeeun; Choi, Ilgyu; Park, Byoungduck; Lee, Ki Yong

2018-05-25

An effective screening method for inhibitors of NO production in natural products using LC-QTOF MS/MS coupled with a cell-based assay was proposed. The ethyl acetate fraction of Catalpa ovata exhibited a strong inhibitory effect on NO production in lipopolysaccharide-induced BV2 microglia cells. We attempted to identify the active constituents of C. ovata by using LC-QTOF MS/MS coupled with a cell-based assay. Peaks at approximately 14-15 min on the MS chromatogram were estimated to be the bioactive constituents. A new iridoid compound, 6-O-trans-feruloyl-3β-hydroxy-7-deoxyrehamaglutin A (4), and nine known compounds (1-3, 5-10) were isolated from the ethyl acetate fraction of C. ovata by repeated column chromatography. Compounds 3, 4, 5, 7, and 8 significantly attenuated lipopolysaccharide-stimulated NO production in BV2 cells. Our results indicate that LC-QTOF MS/MS coupled with a cell-based NO production inhibitory assay successfully predicted active compounds without a time-consuming isolation process. Copyright © 2018 Elsevier Inc. All rights reserved.

Stereoselective effects of ibuprofen in adult zebrafish (Danio rerio) using UPLC-TOF/MS-based metabolomics.

PubMed

Song, Yue; Chai, Tingting; Yin, Zhiqiang; Zhang, Xining; Zhang, Wei; Qian, Yongzhong; Qiu, Jing

2018-06-09

Ibuprofen (IBU), as a commonly used non-steroidal anti-inflammatory drug (NSAID) and pharmaceutical and personal care product (PPCP), is frequently prescribed by doctors to relieve pain. It is widely released into environmental water and soil in the form of chiral enantiomers by the urination and defecation of humans or animals and by sewage discharge from wastewater treatment plants. This study focused on the alteration of metabolism in the adult zebrafish (Danio rerio) brain after exposure to R-(-)-/S-(+)-/rac-IBU at 5 μg L -1 for 28 days. A total of 45 potential biomarkers and related pathways, including amino acids and their derivatives, purine and its derivatives, nucleotides and other metabolites, were observed with untargeted metabolomics. To validate the metabolic disorders induced by IBU, 22 amino acids and 3 antioxidant enzymes were selected to be quantitated and determined using targeted metabolomics and enzyme assay. Stereoselective changes were observed in the 45 identified biomarkers from the untargeted metabolomics analysis. The 22 amino acids quantitated in targeted metabolomics and 3 antioxidant enzymes determined in enzyme assay also showed stereoselective changes after R-(-)-/S-(+)-/rac-IBU exposure. Results showed that even at a low concentration of R-(-)-/S-(+)-/rac-IBU, disorders in metabolism and antioxidant defense systems were still induced with stereoselectivity. Our study may enable a better understanding of the risks of chiral PPCPs in aquatic organisms in the environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

General unknown screening procedure for the characterization of human drug metabolites in forensic toxicology: applications and constraints.

PubMed

Sauvage, François-Ludovic; Picard, Nicolas; Saint-Marcoux, Franck; Gaulier, Jean-Michel; Lachâtre, Gérard; Marquet, Pierre

2009-09-01

LC coupled to single (LC-MS) and tandem (LC-MS/MS) mass spectrometry is recognized as the most powerful analytical tools for metabolic studies in drug discovery. In this article, we describe five cases illustrating the utility of screening xenobiotic metabolites in routine analysis of forensic samples using LC-MS/MS. Analyses were performed using a previously published LC-MS/MS general unknown screening (GUS) procedure developed using a hybrid linear IT-tandem mass spectrometer. In each of the cases presented, the presence of metabolites of xenobiotics was suspected after analyzing urine samples. In two cases, the parent drug was also detected and the metabolites were merely useful to confirm drug intake, but in three other cases, metabolite detection was of actual forensic interest. The presented results indicate that: (i) the GUS procedure developed is useful to detect a large variety of drug metabolites, which would have been hardly detected using targeted methods in the context of clinical or forensic toxicology; (ii) metabolite structure can generally be inferred from their "enhanced" product ion scan spectra; and (iii) structure confirmation can be achieved through in vitro metabolic experiments or through the analysis of urine samples from individuals taking the parent drug.

Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

PubMed

Fernandez, Céline; Fransson, Ulrika; Hallgard, Elna; Spégel, Peter; Holm, Cecilia; Krogh, Morten; Wårell, Kristofer; James, Peter; Mulder, Hindrik

2008-01-01

Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level.

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

PubMed Central

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K. Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-01

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. PMID:26467476

Multiplatform plasma metabolic and lipid fingerprinting of breast cancer: A pilot control-case study in Colombian Hispanic women

PubMed Central

Cala, Mónica P.; Aldana, Julian; Medina, Jessica; Sánchez, Julián; Guio, José; Wist, Julien

2018-01-01

Breast cancer (BC) is a highly heterogeneous disease associated with metabolic reprogramming. The shifts in the metabolome caused by BC still lack data from Latin populations of Hispanic origin. In this pilot study, metabolomic and lipidomic approaches were performed to establish a plasma metabolic fingerprint of Colombian Hispanic women with BC. Data from 1H-NMR, GC-MS and LC-MS were combined and compared. Statistics showed discrimination between breast cancer and healthy subjects on all analytical platforms. The differentiating metabolites were involved in glycerolipid, glycerophospholipid, amino acid and fatty acid metabolism. This study demonstrates the usefulness of multiplatform approaches in metabolic/lipid fingerprinting studies to broaden the outlook of possible shifts in metabolism. Our findings propose relevant plasma metabolites that could contribute to a better understanding of underlying metabolic shifts driven by BC in women of Colombian Hispanic origin. Particularly, the understanding of the up-regulation of long chain fatty acyl carnitines and the down-regulation of cyclic phosphatidic acid (cPA). In addition, the mapped metabolic signatures in breast cancer were similar but not identical to those reported for non-Hispanic women, despite racial differences. PMID:29438405

Multiplatform plasma metabolic and lipid fingerprinting of breast cancer: A pilot control-case study in Colombian Hispanic women.

PubMed

Cala, Mónica P; Aldana, Julian; Medina, Jessica; Sánchez, Julián; Guio, José; Wist, Julien; Meesters, Roland J W

2018-01-01

Breast cancer (BC) is a highly heterogeneous disease associated with metabolic reprogramming. The shifts in the metabolome caused by BC still lack data from Latin populations of Hispanic origin. In this pilot study, metabolomic and lipidomic approaches were performed to establish a plasma metabolic fingerprint of Colombian Hispanic women with BC. Data from 1H-NMR, GC-MS and LC-MS were combined and compared. Statistics showed discrimination between breast cancer and healthy subjects on all analytical platforms. The differentiating metabolites were involved in glycerolipid, glycerophospholipid, amino acid and fatty acid metabolism. This study demonstrates the usefulness of multiplatform approaches in metabolic/lipid fingerprinting studies to broaden the outlook of possible shifts in metabolism. Our findings propose relevant plasma metabolites that could contribute to a better understanding of underlying metabolic shifts driven by BC in women of Colombian Hispanic origin. Particularly, the understanding of the up-regulation of long chain fatty acyl carnitines and the down-regulation of cyclic phosphatidic acid (cPA). In addition, the mapped metabolic signatures in breast cancer were similar but not identical to those reported for non-Hispanic women, despite racial differences.

Development of liquid chromatography/mass spectrometry based screening assay for PfTrxR inhibitors using relative quantitation of intact thioredoxin.

PubMed

Munigunti, Ranjith; Calderón, Angela I

2012-09-15

Plasmodium falciparum (Pf) thioredoxin reductase (TrxR) catalyzes the reduction of thioredoxin disulfide (Trx-S(2)) to thioredoxin dithiol (Trx-(SH)(2)) that is essential for antioxidant defense mechanism and DNA synthesis in the parasite and is a validated drug target for new antimalarial agents. In this study, we have developed a liquid chromatography/mass spectrometry (LC/MS)-based functional assay to identify inhibitors of PfTrxR by quantifying the product formed (Trx-(SH)(2)) in the enzymatic reaction. Relative quantitation of the reaction product (intact Trx-(SH)(2)) was carried out using an Agilent 6520 QTOF mass spectrometer equipped with a positive mode electrospray ionization (ESI) source. The calibration curve prepared for Trx-(SH)(2) at concentrations ranging from 1.8 to 116.5 µg/mL was linear (R(2) >0.998). The limit of detection (LOD) and limit of quantification (LOQ) of Trx-(SH)(2) were at 0.45 and 1.8 µg/mL respectively. To validate the developed functional assay we have screened reference compounds 1, 2 and 3 for their PfTrxR inhibitory activity and ten natural compounds (at 10 μM) which were earlier identified as ligands of PfTrxR by a UF-LC/MS based binding assay. The developed LC/MS-based functional assay for identification of inhibitors of PfTrxR is a sensitive and reliable method that is also amendable for high-throughput format. This is the first representation of a relative quantitation of intact Trx-(SH)(2) using LC/MS. Copyright © 2012 John Wiley & Sons, Ltd.

Methodological issues in assessing plasma 25-hydroxyvitamin D concentration in newborn infants.

PubMed

Gallo, Sina; Comeau, Kathryn; Agellon, Sherry; Vanstone, Catherine; Sharma, Atul; Jones, Glenville; L'abbé, Mary; Khamessan, Ali; Weiler, Hope; Rodd, Celia

2014-04-01

Although no gold standard exists, liquid chromatography tandem mass spectrometry (LC-MS/MS) is a precise and accurate method for the analysis of plasma 25-hydroxyvitamin D (25(OH)D). Immunoassays are more readily available and require small volume sampling, ideal for infant testing. The objective was to compare two commercially available immunoassays for measuring circulating 25(OH)D concentration in infant plasma against LC-MS/MS. Capillary blood samples from 103 infants were analyzed for plasma 25(OH)D using an enzyme immunoassay (EIA, Octeia, IDS Ltd.) and radioimmunoassay (RIA, DiaSorin). Plasma 25(OH)D(3), C-3 epimer of 25(OH)D(3) (3-epi-25(OH)D(3)) and 24,25-dihydroxyvitamin D (24,25(OH)(2)D(3)) were measured on the same samples using LC-MS/MS. To establish whether plasma 24,25(OH)(2)D(3) or 3-epi-25(OH)D(3) interferes with these immunoassay results, the zero 25(OH)D calibrator from each assay kit was spiked with increasing amounts of 24,25(OH)(2)D(3) or 3-epi-25(OH)D(3). Classifying infants below the common vitamin D status targets of 50 nmol/L and 75 nmol/L respectively, 58% and 99% fell below using the RIA, 19% and 56% with the EIA and 31% and 76% with LC-MS/MS. Compared to LC-MS/MS, both immunoassays showed poor Bland-Altman limits of agreement for 25(OH)D concentrations (RIA: limits of agreement -27 to +13%; EIA: -12 to +41%), and mountain plots (folded cumulative distribution) depicted significant skew and bias. Spiked 24,25(OH)2D3 concentrations, but not 3-epi-25(OH)D3, appeared as >100% of known values on the EIA but not on the RIA thus, suggesting that the EIA may cross-react with 24,25(OH)(2)D(3) to a greater extent than 3-epi-25(OH)D(3). Two common immunoassays resulted in very different classifications of vitamin D status possibly related to the interference of other vitamin D metabolites. Based on these data, LC-MS/MS assessment of vitamin D status is recommended in young infants (4-6 weeks of age). Copyright © 2014 Elsevier Inc. All rights reserved.

Rapid method for the measurement of circulating thyroid hormones in low volumes of teleost fish plasma by LC-ESI/MS/MS

PubMed Central

Noyes, Pamela D.; Lema, Sean C.; Roberts, Simon C.; Cooper, Ellen M.

2014-01-01

Thyroid hormones are critical regulators of normal development and physiological functioning in all vertebrates. Radioimmunoassay (RIA) approaches have been the method of choice for measuring circulating levels of thyroid hormones in vertebrates. While sensitive, RIA-based approaches only allow for a single analyte measurement per assay, can lack concordance across platforms and laboratories, and can be prone to analytical interferences especially when used with fish plasma. Ongoing advances in liquid chromatography tandem mass spectrometry (LC/MS/MS) have led to substantial decreases in detection limits for thyroid hormones and other biomolecules in complex matrices, including human plasma. Despite these advances, current analytical approaches do not allow for the measurement of native thyroid hormone in teleost fish plasma by mass spectrometry and continue to rely on immunoassay. In this study, we developed a new method that allows for the rapid extraction and simultaneous measurement of total T4 (TT4) and total T3 (TT3) in low volumes (50 μL) of fish plasma by LC/MS/MS. Methods were optimized initially in plasma from rainbow trout (Oncorhynchus mykiss) and applied to plasma from other teleost fishes, including fathead minnows (Pimephales promelas), mummichogs (Fundulus heteroclitus), sockeye salmon (Oncorhynchus nerka), and coho salmon (Oncorhynchus kisutch). Validation of method performance with T4- and T3-spiked rainbow trout plasma at 2 and 4 ng/mL produced mean recoveries ranging from 82 to 95 % and 97 to 105 %, respectively. Recovery of 13C12-T4 internal standard in plasma extractions was: 99±1.8 % in rainbow trout, 85±11 % in fathead minnow, 73±5.0 % in mummichog, 73±1.7 % in sockeye salmon, and 80±8.4 % in coho salmon. While absolute levels of thyroid hormones measured in identical plasma samples by LC/MS/MS and RIA varied depending on the assay used, T4/T3 ratios were generally consistent across both techniques. Less variability was measured among samples subjected to LC/MS/MS suggesting a more precise estimate of thyroid hormone homeostasis in the species targeted. Overall, a sensitive and reproducible method was established that takes advantage of LC/MS/MS techniques to rapidly measure TT4 and TT3 with negligible interferences in low volumes of plasma across a variety of teleost fishes. PMID:24343452

Metabolomic Analysis of the Secretome of Human Embryonic Stem Cells Following Methyl Parathion and Methyl Paraoxon Exposure, Phase 1: Initial Nontargeted LC-MS

DTIC Science & Technology

2014-01-01

and threonine metabolism 6 40 0.006188 0.10 MP H hsa00260 Glycine, serine and threonine metabolism 3 40 0.010283 0.07 MP H hsa00280 Valine, leucine...hsa00770 Pantothenate and CoA biosynthesis 5 24 0.005066 0.07 MP M hsa04142 Lysosome 2 4 0.002426 0.10 MPO M hsa04930 Type II diabetes mellitus 3 5...of MPO and increased after exposure to all three dose levels of MP. The glycine, serine and threonine metabolism pathway is of interest because

Phenolic and microbial-targeted metabolomics to discovering and evaluating wine intake biomarkers in human urine and plasma.

PubMed

Urpi-Sarda, Mireia; Boto-Ordóñez, María; Queipo-Ortuño, María Isabel; Tulipani, Sara; Corella, Dolores; Estruch, Ramon; Tinahones, Francisco J; Andres-Lacueva, Cristina

2015-09-01

The discovery of biomarkers of intake in nutritional epidemiological studies is essential in establishing an association between dietary intake (considering their bioavailability) and diet-related risk factors for diseases. The aim is to study urine and plasma phenolic and microbial profile by targeted metabolomics approach in a wine intervention clinical trial for discovering and evaluating food intake biomarkers. High-risk male volunteers (n = 36) were included in a randomized, crossover intervention clinical trial. After a washout period, subjects received red wine or gin, or dealcoholized red wine over four weeks. Fasting plasma and 24-h urine were collected at baseline and after each intervention period. A targeted metabolomic analysis of 70 host and microbial phenolic metabolites was performed using ultra performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). Metabolites were subjected to stepwise logistic regression to establish prediction models and received operation curves were performed to evaluate biomarkers. Prediction models based mainly on gallic acid metabolites, obtained sensitivity, specificity and area under the curve (AUC) for the training and validation sets of between 91 and 98% for urine and between 74 and 91% for plasma. Resveratrol, ethylgallate and gallic acid metabolite groups in urine samples also resulted in being good predictors of wine intake (AUC>87%). However, lower values for metabolites were obtained in plasma samples. The highest correlations between fasting plasma and urine were obtained for the prediction model score (r = 0.6, P<0.001), followed by gallic acid metabolites (r = 0.5-0.6, P<0.001). This study provides new insights into the discovery of food biomarkers in different biological samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An enhanced targeted identification strategy for the selective identification of flavonoid O-glycosides from Carthamus tinctorius by integrating offline two-dimensional liquid chromatography/linear ion-trap-Orbitrap mass spectrometry, high-resolution diagnostic product ions/neutral loss filtering and liquid chromatography-solid phase extraction-nuclear magnetic resonance.

PubMed

Yao, Chang-Liang; Yang, Wen-Zhi; Si, Wei; Shen, Yao; Zhang, Nai-Xia; Chen, Hua-Li; Pan, Hui-Qin; Yang, Min; Wu, Wan-Ying; Guo, De-An

2017-03-31

Targeted identification of potentially bioactive molecules from herbal medicines is often stymied by the insufficient chromatographic separation, ubiquitous matrix interference, and pervasive isomerism. An enhanced targeted identification strategy is presented and validated by the selective identification of flavonoid O-glycosides (FOGs) from Carthamus tinctorius. It consists of four steps: (i) enhanced separation and detection by offline two-dimensional liquid chromatography/LTQ-Orbitrap MS (offline 2D-LC/LTQ-Orbitrap MS) using collision-induced dissociation (CID) and high-energy C-trap dissociation (HCD); (ii) improved identification of the major aglycones by acid hydrolysis and LC-SPE-NMR; (iii) simplified spectral elucidation by high-resolution diagnostic product ions/neutral loss filtering; and (iv) more convincing structural identification by matching an in-house library. An offline 2D-LC system configuring an Acchrom XAmide column and a BEH Shield RP-18 UPLC ® column enabled much better separation of the easily co-eluting components. Combined use of CID and HCD could produce complementary fragmentation information. The intensity ratios of the aglycone ion species ([Y 0 -H] - /Y 0 - and [Y 0 -2H] - /Y 0 - ) in the HCD-MS 2 spectra were found diagnostic for discriminating the aglycone subtypes and characterizing the glycosylation patterns. Five aglycone structures (kaempferol, 6-hydroxykaempferol, 6-methoxykaempferol, carthamidin, and isocarthamidin) were identified based on the 1 H-NMR data recorded by LC-SPE-NMR. Of the 107 characterized flavonoids, 80 FOGs were first reported from C. tinctorius. Unknown aglycones, pentose, and novel acyl substituents were discovered. A new compound thereof was isolated and fully identified, which could partially validate the MS-oriented identification. This integral strategy can improve the potency, efficiency, and accuracy in the detection of new compounds from medicinal herbs and other natural sources. Copyright © 2017 Elsevier B.V. All rights reserved.

ALLocator: an interactive web platform for the analysis of metabolomic LC-ESI-MS datasets, enabling semi-automated, user-revised compound annotation and mass isotopomer ratio analysis.

PubMed

Kessler, Nikolas; Walter, Frederik; Persicke, Marcus; Albaum, Stefan P; Kalinowski, Jörn; Goesmann, Alexander; Niehaus, Karsten; Nattkemper, Tim W

2014-01-01

Adduct formation, fragmentation events and matrix effects impose special challenges to the identification and quantitation of metabolites in LC-ESI-MS datasets. An important step in compound identification is the deconvolution of mass signals. During this processing step, peaks representing adducts, fragments, and isotopologues of the same analyte are allocated to a distinct group, in order to separate peaks from coeluting compounds. From these peak groups, neutral masses and pseudo spectra are derived and used for metabolite identification via mass decomposition and database matching. Quantitation of metabolites is hampered by matrix effects and nonlinear responses in LC-ESI-MS measurements. A common approach to correct for these effects is the addition of a U-13C-labeled internal standard and the calculation of mass isotopomer ratios for each metabolite. Here we present a new web-platform for the analysis of LC-ESI-MS experiments. ALLocator covers the workflow from raw data processing to metabolite identification and mass isotopomer ratio analysis. The integrated processing pipeline for spectra deconvolution "ALLocatorSD" generates pseudo spectra and automatically identifies peaks emerging from the U-13C-labeled internal standard. Information from the latter improves mass decomposition and annotation of neutral losses. ALLocator provides an interactive and dynamic interface to explore and enhance the results in depth. Pseudo spectra of identified metabolites can be stored in user- and method-specific reference lists that can be applied on succeeding datasets. The potential of the software is exemplified in an experiment, in which abundance fold-changes of metabolites of the l-arginine biosynthesis in C. glutamicum type strain ATCC 13032 and l-arginine producing strain ATCC 21831 are compared. Furthermore, the capability for detection and annotation of uncommon large neutral losses is shown by the identification of (γ-)glutamyl dipeptides in the same strains. ALLocator is available online at: https://allocator.cebitec.uni-bielefeld.de. A login is required, but freely available.

Chemical and technical challenges in the analysis of central carbon metabolites by liquid-chromatography mass spectrometry.

PubMed

Siegel, David; Permentier, Hjalmar; Reijngoud, Dirk-Jan; Bischoff, Rainer

2014-09-01

This review deals with chemical and technical challenges in the analysis of small-molecule metabolites involved in central carbon and energy metabolism via liquid-chromatography mass-spectrometry (LC-MS). The covered analytes belong to the prominent pathways in biochemical carbon oxidation such as glycolysis or the tricarboxylic acid cycle and, for the most part, share unfavorable properties such as a high polarity, chemical instability or metal-affinity. The topic is introduced by selected examples on successful applications of metabolomics in the clinic. In the core part of the paper, the structural features of important analyte classes such as nucleotides, coenzyme A thioesters or carboxylic acids are linked to "problematic hotspots" along the analytical chain (sample preparation and-storage, separation and detection). We discuss these hotspots from a chemical point of view, covering issues such as analyte degradation or interactions with metals and other matrix components. Based on this understanding we propose solutions wherever available. A major notion derived from these considerations is that comprehensive carbon metabolomics inevitably requires multiple, complementary analytical approaches covering different chemical classes of metabolites. Copyright © 2013 Elsevier B.V. All rights reserved.

The Siderophore Metabolome of Azotobacter vinelandii

PubMed Central

Baars, Oliver; Zhang, Xinning

2015-01-01

In this study, we performed a detailed characterization of the siderophore metabolome, or “chelome,” of the agriculturally important and widely studied model organism Azotobacter vinelandii. Using a new high-resolution liquid chromatography-mass spectrometry (LC-MS) approach, we found over 35 metal-binding secondary metabolites, indicative of a vast chelome in A. vinelandii. These include vibrioferrin, a siderophore previously observed only in marine bacteria. Quantitative analyses of siderophore production during diazotrophic growth with different sources and availabilities of Fe showed that, under all tested conditions, vibrioferrin was present at the highest concentration of all siderophores and suggested new roles for vibrioferrin in the soil environment. Bioinformatic searches confirmed the capacity for vibrioferrin production in Azotobacter spp. and other bacteria spanning multiple phyla, habitats, and lifestyles. Moreover, our studies revealed a large number of previously unreported derivatives of all known A. vinelandii siderophores and rationalized their origins based on genomic analyses, with implications for siderophore diversity and evolution. Together, these insights provide clues as to why A. vinelandii harbors multiple siderophore biosynthesis gene clusters. Coupled with the growing evidence for alternative functions of siderophores, the vast chelome in A. vinelandii may be explained by multiple, disparate evolutionary pressures that act on siderophore production. PMID:26452553

Accurate inclusion mass screening: a bridge from unbiased discovery to targeted assay development for biomarker verification.

PubMed

Jaffe, Jacob D; Keshishian, Hasmik; Chang, Betty; Addona, Theresa A; Gillette, Michael A; Carr, Steven A

2008-10-01

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.

Use of metabolomics and lipidomics to evaluate the hypocholestreolemic effect of Proanthocyanidins from grape seed in a pig model.

PubMed

Quifer-Rada, Paola; Choy, Ying Yng; Calvert, Christopher C; Waterhouse, Andrew L; Lamuela-Raventos, Rosa M

2016-10-01

This work aims to evaluate changes in the fecal metabolomic profile due to grape seed extract (GSE) intake by untargeted and targeted analysis using high resolution mass spectrometry in conjunction with multivariate statistics. An intervention study with six crossbred female pigs was performed. The pigs followed a standard diet for 3 days, then they were fed with a supplemented diet containing 1% (w/w) of MegaNatural® Gold grape seed extract for 6 days. Fresh pig fecal samples were collected daily. A combination of untargeted high resolution mass spectrometry, multivariate analysis (PLS-DA), data-dependent MS/MS scan, and accurate mass database matching was used to measure the effect of the treatment on fecal composition. The resultant PLS-DA models showed a good discrimination among classes with great robustness and predictability. A total of 14 metabolites related to the GSE consumption were identified including biliary acid, dicarboxylic fatty acid, cholesterol metabolites, purine metabolites, and eicosanoid metabolites among others. Moreover, targeted metabolomics using GC-MS showed that cholesterol and its metabolites fecal excretion was increased due to the proanthocyanidins from grape seed extract. The results show that oligomeric procyanidins from GSE modifies bile acid and steroid excretion, which could exert a hypocholesterolemic effect. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes.

PubMed

Lanza, Ian R; Zhang, Shucha; Ward, Lawrence E; Karakelides, Helen; Raftery, Daniel; Nair, K Sreekumaran

2010-05-10

Insulin is as a major postprandial hormone with profound effects on carbohydrate, fat, and protein metabolism. In the absence of exogenous insulin, patients with type 1 diabetes exhibit a variety of metabolic abnormalities including hyperglycemia, glycosurea, accelerated ketogenesis, and muscle wasting due to increased proteolysis. We analyzed plasma from type 1 diabetic (T1D) humans during insulin treatment (I+) and acute insulin deprivation (I-) and non-diabetic participants (ND) by (1)H nuclear magnetic resonance spectroscopy and liquid chromatography-tandem mass spectrometry. The aim was to determine if this combination of analytical methods could provide information on metabolic pathways known to be altered by insulin deficiency. Multivariate statistics differentiated proton spectra from I- and I+ based on several derived plasma metabolites that were elevated during insulin deprivation (lactate, acetate, allantoin, ketones). Mass spectrometry revealed significant perturbations in levels of plasma amino acids and amino acid metabolites during insulin deprivation. Further analysis of metabolite levels measured by the two analytical techniques indicates several known metabolic pathways that are perturbed in T1D (I-) (protein synthesis and breakdown, gluconeogenesis, ketogenesis, amino acid oxidation, mitochondrial bioenergetics, and oxidative stress). This work demonstrates the promise of combining multiple analytical methods with advanced statistical methods in quantitative metabolomics research, which we have applied to the clinical situation of acute insulin deprivation in T1D to reflect the numerous metabolic pathways known to be affected by insulin deficiency.

High-throughput metabolic profiling of diverse green Coffea arabica beans identified tryptophan as a universal discrimination factor for immature beans.

PubMed

Setoyama, Daiki; Iwasa, Keiko; Seta, Harumichi; Shimizu, Hiroaki; Fujimura, Yoshinori; Miura, Daisuke; Wariishi, Hiroyuki; Nagai, Chifumi; Nakahara, Koichi

2013-01-01

The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (immature, semi-mature, mature and overripe) of nine different varieties of green Coffea arabica beans hand-harvested from a single experimental field in Hawaii. After developing a high-throughput experimental system for sample preparation and liquid chromatography-mass spectrometry (LC-MS) measurement, we applied metabolic profiling, integrated with chemometric techniques, to explore the relationship between the metabolome and maturity of the sample in a non-biased way. For the multivariate statistical analyses, a partial least square (PLS) regression model was successfully created, which allowed us to accurately predict the maturity of the beans based on the metabolomic information. As a result, tryptophan was identified to be the best contributor to the regression model; the relative MS intensity of tryptophan was higher in immature beans than in those after the semi-mature stages in all arabica varieties investigated, demonstrating a universal discrimination factor for diverse arabica beans. Therefore, typtophan, either alone or together with other metabolites, may be utilized for traders as an assessment standard when purchasing qualified trading green arabica bean products. Furthermore, our results suggest that the tryptophan metabolism may be tightly linked to the development of coffee cherries and/or beans.

LC-MS based analysis of endogenous steroid hormones in human hair.

PubMed

Gao, Wei; Kirschbaum, Clemens; Grass, Juliane; Stalder, Tobias

2016-09-01

The quantification of endogenous steroid hormone concentrations in hair is increasingly used as a method for obtaining retrospective information on long-term integrated hormone exposure. Several different analytical procedures have been employed for hair steroid analysis, with liquid chromatography-mass spectrometry (LC-MS) being recognized as a particularly powerful analytical tool. Several methodological aspects affect the performance of LC-MS systems for hair steroid analysis, including sample preparation and pretreatment, steroid extraction, post-incubation purification, LC methodology, ionization techniques and MS specifications. Here, we critically review the differential value of such protocol variants for hair steroid hormones analysis, focusing on both analytical quality and practical feasibility issues. Our results show that, when methodological challenges are adequately addressed, LC-MS protocols can not only yield excellent sensitivity and specificity but are also characterized by relatively simple sample processing and short run times. This makes LC-MS based hair steroid protocols particularly suitable as a high-quality option for routine application in research contexts requiring the processing of larger numbers of samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a targeted adductomic method for the determination of polycyclic aromatic hydrocarbon DNA adducts using online column-switching liquid chromatography/tandem mass spectrometry.

PubMed

Singh, Rajinder; Teichert, Friederike; Seidel, Albrecht; Roach, Jonathan; Cordell, Rebecca; Cheng, Mai-Kim; Frank, Heinrich; Steward, William P; Manson, Margaret M; Farmer, Peter B

2010-08-30

Human exposure to polycyclic aromatic hydrocarbons (PAHs) from sources such as industrial or urban air pollution, tobacco smoke and cooked food is not confined to a single compound, but instead to mixtures of different PAHs. The interaction of different PAHs may lead to additive, synergistic or antagonistic effects in terms of DNA adduct formation and carcinogenic activity resulting from changes in metabolic activation to reactive intermediates and DNA repair. The development of a targeted DNA adductomic approach using liquid chromatography/tandem mass spectrometry (LC/MS/MS) incorporating software-based peak picking and integration for the assessment of exposure to mixtures of PAHs is described. For method development PAH-modified DNA samples were obtained by reaction of the anti-dihydrodiol epoxide metabolites of benzo[a]pyrene, benzo[b]fluoranthene, dibenzo[a,l]pyrene (DB[a,l]P) and dibenz[a,h]anthracene with calf thymus DNA in vitro and enzymatically hydrolysed to 2'-deoxynucleosides. Positive LC/electrospray ionisation (ESI)-MS/MS collision-induced dissociation product ion spectra data showed that the majority of adducts displayed a common fragmentation for the neutral loss of 116 u (2'-deoxyribose) resulting in a major product ion derived from the adducted base. The exception was the DB[a,l]P dihydrodiol epoxide adduct of 2'-deoxyadenosine which resulted in major product ions derived from the PAH moiety being detected. Specific detection of mixtures of PAH-adducted 2'-deoxynucleosides was achieved using online column-switching LC/MS/MS in conjunction with selected reaction monitoring (SRM) of the [M+H](+) to [M+H-116](+) transition plus product ions derived from the PAH moiety for improved sensitivity of detection and a comparison was made to detection by constant neutral loss scanning. In conclusion, different PAH DNA adducts were detected by employing SRM [M+H-116](+) transitions or constant neutral loss scanning. However, for improved sensitivity of detection optimised SRM transitions relating to the PAH moiety product ions are required for certain PAH DNA adducts for the development of targeted DNA adductomic methods. 2010 John Wiley & Sons, Ltd.

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.

Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptidemore » biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements« less

Strategies Involving Mass Spectrometry Combined with Capillary Electrophoresis in Metabolomics.

PubMed

Rodrigues, Karina Trevisan; Cieslarová, Zuzana; Tavares, Marina Franco Maggi; Simionato, Ana Valéria Colnaghi

2017-01-01

This chapter focuses on the important contribution of CE-MS in metabolomics, describing the nature of CE-MS coupling and the technical improvements that have led to the interfaces used in modern instrumentation. Moreover, it will discourse how the variety of electrolyte compositions and additives, which has conferred CE the exceptional selectivity of its multiple separation modes, has been handled to allow interfacing with MS without compromising ionization efficiency and the spectrometer integrity. Finally, the methodologies of CE-MS in current use for metabolomics will be discussed in detail. To verify the scope of CE-MS in clinical metabolomics, a myriad of representative applications has been compiled.

NMR and MS methods for metabonomics.

PubMed

Dieterle, Frank; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Amberg, Alexander

2011-01-01

Metabonomics, also often referred to as "metabolomics" or "metabolic profiling," is the systematic profiling of metabolites in bio-fluids or tissues of organisms and their temporal changes. In the last decade, metabonomics has become increasingly popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabonomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabonomics, i.e., NMR, LC-MS, UPLC-MS, and GC-MS have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabonomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation, to determining the measurement details of all analytical platforms, and finally, to discussing the corresponding specific steps of data analysis.

Usage of FT-ICR-MS Metabolomics for Characterizing the Chemical Signatures of Barrel-Aged Whisky

PubMed Central

Roullier-Gall, Chloé; Signoret, Julie; Hemmler, Daniel; Witting, Michael A.; Kanawati, Basem; Schäfer, Bernhard; Gougeon, Régis D.; Schmitt-Kopplin, Philippe

2018-01-01

Whisky can be described as a complex matrix integrating the chemical history from the fermented cereals, the wooden barrels, the specific distillery processes, aging, and environmental factors. In this study, using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we analyzed 150 whisky samples from 49 different distilleries, 7 countries, and ranging from 1 day new make spirit to 43 years of maturation with different types of barrel. Chemometrics revealed the unexpected impact of the wood history on the distillate's composition during barrel aging, regardless of the whisky origin. Flavonols, oligolignols, and fatty acids are examples of important chemical signatures for Bourbon casks, whereas a high number of polyphenol glycosides, including for instance quercetin-glucuronide or myricetin-glucoside as potential candidates, and carbohydrates would discriminate Sherry casks. However, the comparison of barrel aged rums and whiskies revealed specific signatures, highlighting the importance of the initial composition of the distillate and the distillery processes. PMID:29520358

Usage of FT-ICR-MS Metabolomics for characterizing the chemical signatures of barrel-aged whisky

NASA Astrophysics Data System (ADS)

Roullier-Gall, Chloé; Signoret, Julie; Hemmler, Daniel; Witting, Michael A.; Kanawati, Basem; Schäfer, Bernhard; Gougeon, Régis D.; Schmitt-Kopplin, Philippe

2018-02-01

Whisky can be described as a complex matrix integrating the chemical history from the fermented cereals, the wooden barrels, the specific distillery processes, ageing and environmental factors. In this study, using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we analysed 150 whisky samples from 49 different distilleries, 7 countries, and ranging from 1 day new make spirit to 43 years of maturation with different types of barrel. Chemometrics revealed the unexpected impact of the wood history on the distillatés composition during barrel ageing, regardless of the whisky origin. Flavonols, oligolignols and fatty acids are examples of important chemical signatures for Bourbon casks, whereas a high number of polyphenol glycosides, including for instance quercetin-glucuronide or myricetin-glucoside as potential candidates, and carbohydrates would discriminate Sherry casks. However, the comparison of barrel aged rums and whiskies revealed specific signatures, highlighting the importance of the initial composition of the distillate and the distillery processes.

Lipidomic analysis of glycerolipid and cholesteryl ester autooxidation products.

PubMed

Kuksis, Arnis; Suomela, Jukka-Pekka; Tarvainen, Marko; Kallio, Heikki

2009-06-01

Thin-layer chromatography (TLC), gas chromatography (GC), and liquid chromatography (LC) in combination with mass spectrometry (MS) have been adopted for the isolation and identification of oxolipids and for determining their functionality. TLC provides a rapid separation and access to most oxolipids as intact molecules and has recently been effectively interfaced with time-of-flight (TOF) MS (TOF-MS). GC with flame ionization (FI) (GC/FI) and electron impact (EI) MS (GC/EI-MS) has been extensively utilized in the analysis of isoprostanes and other low-molecular-weight oxolipids, although these methods require derivatization of the analytes. In contrast, LC with ultraviolet (UV) absorption (LC/UV) or evaporate light scattering detection (ELSD) (LC/ELSD) as well as electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) MS (LC/ESI-MS) or LC/APCI-MS has proven to be well suited for the analysis of intact oxolipids and their conjugates without or with minimal derivatization. Nevertheless, kit-based colorimetric and fluorescent procedures continue to serve as sensitive indicators of the presence of hydroperoxides and aldehydes.

Power of Orbitrap-based LC-high resolution-MS/MS for comprehensive drug testing in urine with or without conjugate cleavage or using dried urine spots after on-spot cleavage in comparison to established LC-MSn or GC-MS procedures.

PubMed

Michely, Julian A; Meyer, Markus R; Maurer, Hans H

2018-01-01

Reliable, sensitive, and comprehensive urine screening procedures by gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS) with low or high resolution (HR) are of high importance for drug testing, adherence monitoring, or detection of toxic compounds. Besides conventional urine sampling, dried urine spots are of increasing interest. In the present study, the power of LC-HR-MS/MS was investigated for comprehensive drug testing in urine with or without conjugate cleavage or using dried urine spots after on-spot cleavage in comparison to established LC-MS n or GC-MS procedures. Authentic human urine samples (n = 103) were split in 4 parts. One aliquot was prepared by precipitation (UP), one by UP with conjugate cleavage (UglucP), one spot on filter paper cards and prepared by on-spot cleavage followed by liquid extraction (DUSglucE), and one worked-up by acid hydrolysis, liquid-liquid extraction, and acetylation for GC-MS analysis. The 3 series of LC-HR-MS/MS results were compared among themselves, to corresponding published LC-MS n data, and to screening results obtained by conventional GC-MS. The reference libraries used for the 3 techniques contained over 4500 spectra of parent compounds and their metabolites. The number of all detected hits (770 drug intakes) was set to 100%. The LC-HR-MS/MS approach detected 80% of the hits after UP, 89% after UglucP, and 77% after DUSglucE, which meant over one-third more hits in comparison to the corresponding published LC-MS n results with ≤49% detected hits. The GC-MS approach identified 56% of all detected hits. In conclusion, LC-HR-MS/MS provided the best screening results after conjugate cleavage and precipitation. Copyright © 2017 John Wiley & Sons, Ltd.

Establishment and comparison of three novel methods for the determination of the photodynamic therapy agent 2-[1-hexyloxyethyl]-2-devinyl pyropheophorbide-a (HPPH) in human serum.

PubMed

Chen, Lin; Xiao, Qingqing; Zhang, Xian; Yang, Jin

2016-03-20

2-[1-Hexyloxyethyl]-2-devinyl pyropheophorbide-a (HPPH) is a second-generation photosensitizer that has been applied in clinical studies of photodynamic therapy for a variety of malignant lesions. Based on the differences in selectivity and labour intensity, three novel methods - fluorescence detection coupled with high performance liquid chromatography (LC-FLD), LC-tandem mass spectrometry (LC-MS/MS) and fluorescence-based microplate reader methods - were developed for the determination of HPPH in human serum, which allowed comparison of fluorescence and MS platform for HPPH quantification. All three methods have been validated and successfully applied to support the clinical pharmacokinetic study of HPPH. The concentrations measured by LC-FLD matched those by LC-MS/MS with a correlation coefficient (r=0.994) and coefficient of determination (r(2)=0.989). Data consistency was also found between the measurements of microplate reader and LC-MS/MS with a correlation coefficient (r=0.999) and coefficient of determination (r(2)=0.998), indicating that fluorescence assay, the low cost alternative with a relatively poorer selectivity, is clearly suitable for the quantification of HPPH. Calibration curves in the methods of LC-FLD and microplate reader were linear (r˃0.998) over the concentration range from 50 to 5000 ng/mL, and linearity was obtained over the concentration range from 5 to 1000 ng/mL in the LC-MS/MS method. Compared with the other two methods, the fluorescence-based microplate reader method with proven high selectivity should be strongly recommended because of obvious advantages such as the lowest labour intensity, the lowest instrument cost, a better sensitivity than LC-FLD and the very rapid determination of large number of samples (24 samples/40 s). Copyright © 2015 Elsevier B.V. All rights reserved.

ICPD-a new peak detection algorithm for LC/MS.

PubMed

Zhang, Jianqiu; Haskins, William

2010-12-01

The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods.

Identification of liver protein targets modified by tienilic acid metabolites using a two-dimensional Western blot-mass spectrometry approach

NASA Astrophysics Data System (ADS)

Methogo, Ruth Menque; Dansette, Patrick M.; Klarskov, Klaus

2007-12-01

A combined approach based on two-dimensional electrophoresis-immuno-blotting and nanoliquid chromatography coupled on-line with electrospray ionization mass spectrometry (nLC-MS/MS) was used to identify proteins modified by a reactive intermediate of tienilic acid (TA). Liver homogenates from rats exposed to TA were fractionated using ultra centrifugation; four fractions were obtained and subjected to 2D electrophoresis. Following transfer to PVDF membranes, modified proteins were visualized after India ink staining, using an anti-serum raised against TA and ECL detection. Immuno-reactive spots were localized on the PVDF membrane by superposition of the ECL image, protein spots of interest were excised, digested on the membrane with trypsin followed by nLC-MS/MS analysis and protein identification. A total of 15 proteins were identified as likely targets modified by a TA reactive metabolite. These include selenium binding protein 2, senescence marker protein SMP-30, adenosine kinase, Acy1 protein, adenosylhomocysteinase, capping protein (actin filament), protein disulfide isomerase, fumarylacetoacetase, arginase chain A, ketohexokinase, proteasome endopeptidase complex, triosephosphate isomerase, superoxide dismutase, dna-type molecular chaperone hsc73 and malate dehydrogenase.

Screening Antioxidants Using LC-MS: A Case Study with Cocoa

PubMed Central

Calderón, Angela I.; Wright, Brian J.; Hurst, W. Jeffrey; van Breemen, Richard B.

2009-01-01

Oxidative stress enhances pathological processes contributing to cancer, cardiovascular disease and neurodegenerative diseases, and dietary antioxidants may counteract these deleterious processes. Since rapid methods to evaluate and compare food products for antioxidant benefits are needed, a new assay based on liquid chromatography-mass spectrometry (LC-MS) was developed for the identification and quantitative analysis of antioxidants in complex natural product samples such as food extracts. This assay is based on the comparison of electrospray LC-MS profiles of sample extracts before and after treatment with reactive oxygen species such as hydrogen peroxide or DPPH (2,2-diphenyl-1-picrylhydrazyl radical). Using this assay, methanolic extracts of cocoa powder were analyzed, and procyanidins were found to be the most potent antioxidant species. These species were identified using LC-MS, LC-MS-MS, accurate mass measurement, and comparison with reference standards. Furthermore, LC-MS was used to determine the levels of these species in cocoa samples. Catechin and epicatechin were the most abundant antioxidants followed by their dimers and trimers. The most potent antioxidants in cocoa were trimers and dimers of catechin and epicatechin, such as procyanidin B2, followed by catechin and epicatechin. This new LC-MS assay facilitates the rapid identification and then the determination of the relative antioxidant activities of individual antioxidant species in complex natural product samples and food products such as cocoa. PMID:19489609

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

PubMed

Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

MicroSPE-nanoLC-ESI-MS/MS Using 10-μm-i.d. Silica-Based Monolithic Columns for Proteomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Quanzhou; Page, Jason S.; Tang, Keqi

2007-01-01

Silica-based monolithic narrow bore capillary columns (25 cm x 10 µm i.d.) with an integrated nanoESI emitter has been developed to provide high quality and robust microSPE-nanoLC-ESI-MS analyses. The integrated nanoESI emitter adds no dead volume to the LC separation, allowing stable electrospray performance to be obtained at flow rates of ~10 nL/min. In an initial application we identified 5510 unique peptides covering 1443 distinct Shewanella oneidensis proteins from a 300 ng tryptic digest sample in a single 4-h LC-MS/MS analysis using a linear ion trap MS (LTQ). We found the use of an integrated monolithic ESI emitter provided enhancedmore » resistance to clogging and good run-to-run reproducibility.« less

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

PubMed Central

Imperlini, Esther; Santorelli, Lucia; Orrù, Stefania; Scolamiero, Emanuela; Ruoppolo, Margherita

2016-01-01

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs. PMID:27403441

Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

DOE PAGES

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...

2015-07-03

Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less

Post-acquisition data processing for the screening of transformation products of different organic contaminants. Two-year monitoring of river water using LC-ESI-QTOF-MS and GCxGC-EI-TOF-MS.

PubMed

López, S Herrera; Ulaszewska, M M; Hernando, M D; Martínez Bueno, M J; Gómez, M J; Fernández-Alba, A R

2014-11-01

This study describes a comprehensive strategy for detecting and elucidating the chemical structures of expected and unexpected transformation products (TPs) from chemicals found in river water and effluent wastewater samples, using liquid chromatography coupled to electrospray ionization quadrupole-time-of-flight mass spectrometer (LC-ESI-QTOF-MS), with post-acquisition data processing and an automated search using an in-house database. The efficacy of the mass defect filtering (MDF) approach to screen metabolites from common biotransformation pathways was tested, and it was shown to be sufficiently sensitive and applicable for detecting metabolites in environmental samples. Four omeprazole metabolites and two venlafaxine metabolites were identified in river water samples. This paper reports the analytical results obtained during 2 years of monitoring, carried out at eight sampling points along the Henares River (Spain). Multiresidue monitoring, for targeted analysis, includes a group of 122 chemicals, amongst which are pharmaceuticals, personal care products, pesticides and PAHs. For this purpose, two analytical methods were used based on direct injection with a LC-ESI-QTOF-MS system and stir bar sorptive extraction (SBSE) with bi-dimensional gas chromatography coupled with a time-of-flight spectrometer (GCxGC-EI-TOF-MS).

Profiling and characterizing skin ceramides using reversed-phase liquid chromatography-quadrupole time-of-flight mass spectrometry.

PubMed

t'Kindt, Ruben; Jorge, Lucie; Dumont, Emmie; Couturon, Pauline; David, Frank; Sandra, Pat; Sandra, Koen

2012-01-03

An LC-MS based method for the profiling and characterization of ceramide species in the upper layer of human skin is described. Ceramide samples, collected by tape stripping of human skin, were analyzed by reversed-phase liquid chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry operated in both positive and negative electrospray ionization mode. All known classes of ceramides could be measured in a repeatable manner. Furthermore, the data set showed several undiscovered ceramides, including a class with four hydroxyl functionalities in its sphingoid base. High-resolution MS/MS fragmentation spectra revealed that each identified ceramide species is composed of several skeletal isomers due to variation in carbon length of the respective sphingoid bases and fatty acyl building blocks. The resulting variety in skeletal isomers has not been previously demonstrated. It is estimated that over 1000 unique ceramide structures could be elucidated in human stratum corneum. Ceramide species with an even and odd number of carbon atoms in both chains were detected in all ceramide classes. Acid hydrolysis of the ceramides, followed by LC-MS analysis of the end-products, confirmed the observed distribution of both sphingoid bases and fatty acyl groups in skin ceramides. The study resulted in an accurate mass retention time library for targeted profiling of skin ceramides. It is furthermore demonstrated that targeted data processing results in an improved repeatability versus untargeted data processing (72.92% versus 62.12% of species display an RSD < 15%). © 2011 American Chemical Society

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Hall, Adam B.; Fornace, Albert J.; Vouros, Paul

2016-10-01

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure.

Enantiomeric separation of metolachlor and its metabolites using LC-MS and CZE

USGS Publications Warehouse

Klein, C. John; Schneider, R.J.; Meyer, M.T.; Aga, D.S.

2006-01-01

The stereoisomers of metolachlor and its two polar metabolites [ethane sulfonic acid (ESA) and oxanilic acid (OXA)] were separated using liquid chromatography-mass spectrometry (LC-MS) and capillary zone electrophoresis (CZE), respectively. The separation of metolachlor enantiomers was achieved using a LC-MS equipped with a chiral stationary phase based on cellulose tris(3,5-dimethylphenyl carbamate) and an atmospheric pressure chemical ionization source operated under positive ion mode. The enantiomers of ESA and OXA were separated using CZE with gamma-cyclodextrin (??-CD) as chiral selector. Various CZE conditions were investigated to achieve the best resolution of the ESA and OXA enantiomers. The optimum background CZE electrolyte was found to consist of borate buffer (pH = 9) containing 20% methanol (v/v) and 2.5% ??-CD (w/v). Maximum resolution of ESA and OXA enantiomers was achieved using a capillary temperature of 15??C and applied voltage of 30 kV. The applicability of the LC-MS and CZE methods was demonstrated successfully on the enantiomeric analysis of metolachlor and its metabolites in samples from a soil and water degradation study that was set up to probe the stereoselectivity of metolachlor biodegradation. These techniques allow the enantiomeric ratios of the target analytes to be followed over time during the degradation process and thus will prove useful in determining the role of chirality in pesticide degradation and metabolite formation. ?? 2005 Elsevier Ltd. All rights reserved.

Quantification of CSF cystatin C using liquid chromatography tandem mass spectrometry.

PubMed

Matsuda, Chikashi; Shiota, Yuri; Sheikh, Abdullah Md; Okazaki, Ryota; Yamada, Kazuo; Yano, Shozo; Minohata, Toshikazu; Matsumoto, Ken-Ichi; Yamaguchi, Shuhei; Nagai, Atsushi

2018-03-01

Cystatin C (CST3), a ubiquitously expressed cysteine protease inhibitor, is implicated in several neurological diseases. Here, we have developed an accurate CST3 measurement system based on liquid chromatography tandem mass spectrometry (LC-MS/MS). LC-MS/MS based measurement for CSF CST3 was validated by determination of assay precision, accuracy and recovery. The values were compared with those measured by immunoassay. Glycosylation of CST3 in CSF was analyzed by Western blotting and lectin blotting. Measuring standard CST3 by LC-MS/MS produced a linear standard curve that correlated with assigned values (r 2 =0.99). Both intra- and inter-assay variation was <10%. Although showed a correlation, the average CST3 concentration measured by LC-MS/MS was significantly higher than that of immunoassay. Western blotting showed the presence of a 25KDa species along with CST3 monomer (14KDa) in CSF. The volume of 25KDa species was decreased by deglycosylation. Lectin blotting revealed a 25KDa glycosylated protein in sialidase-treated CSF, which was decreased by deglycosylation. However, deglycosylation did not alter CST3 concentration measured by immunoassay. Our results suggest that LC-MS/MS-based CST3 measurement is a robust method with higher detection ability. Such method could be useful for the diagnosis and monitoring of neurological diseases. Copyright © 2017 Elsevier B.V. All rights reserved.