Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics

DOE PAGES

Webb-Robertson, Bobbie-Jo M.; Wiberg, Holli K.; Matzke, Melissa M.; ...

2015-04-09

In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yieldedmore » the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. In summary, on the basis of the observations in this review, the goal for imputation in the field of computational proteomics should be to develop new approaches that work generically for this data type and new strategies to guide users in the selection of the best imputation for their dataset and analysis objectives.« less

Evaluation of different multidimensional LC-MS/MS pipelines for iTRAQ-based proteomic analysis of potato tubers in response to cold storage

USDA-ARS?s Scientific Manuscript database

Cold-induced sweetening in potato tubers is a costly problem for food industry. To systematically identify the proteins associated with this process, we employed a comparative proteomics approach using isobaric, stable isotope coded labels to compare the proteomes of potato tubers after 0 and 5 mont...

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

PubMed

Galpert, Deborah; Fernández, Alberto; Herrera, Francisco; Antunes, Agostinho; Molina-Ruiz, Reinaldo; Agüero-Chapin, Guillermin

2018-05-03

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes. The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were alignment-free features related to amino acid composition. The incorporation of alignment-free features in supervised big data models did not significantly improve ortholog detection in yeast proteomes regarding the classification qualities achieved with just alignment-based similarity measures. However, the similarity of their classification performance to that of traditional ortholog detection methods encourages the evaluation of other alignment-free protein pair descriptors in future research.

QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

PubMed

Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

2015-11-03

We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

Mathematical biodescriptors of proteomics maps: background and applications.

PubMed

Basak, Subhash C; Gute, Brian D

2008-05-01

This article reviews recent developments in the formulation and application of biodescriptors to characterize proteomics maps. Such biodescriptors can be derived by applying techniques from discrete mathematics (graph theory, linear algebra and information theory). This review focuses on the development of biodescriptors for proteomics maps derived from 2D gel electrophoresis. Preliminary results demonstrated that such descriptors have a reasonable ability to differentiate between proteomics patterns that result from exposure to closely related individual chemicals and complex mixtures, such as the jet fuel JP-8. Further research is required to evaluate the utility of these proteomics-based biodescriptors for drug discovery and predictive toxicology.

CPTAC Evaluates Long-Term Reproducibility of Quantitative Proteomics Using Breast Cancer Xenografts | Office of Cancer Clinical Proteomics Research

Cancer.gov

Liquid chromatography tandem-mass spectrometry (LC-MS/MS)- based methods such as isobaric tags for relative and absolute quantification (iTRAQ) and tandem mass tags (TMT) have been shown to provide overall better quantification accuracy and reproducibility over other LC-MS/MS techniques. However, large scale projects like the Clinical Proteomic Tumor Analysis Consortium (CPTAC) require comparisons across many genomically characterized clinical specimens in a single study and often exceed the capability of traditional iTRAQ-based quantification.

To label or not to label: applications of quantitative proteomics in neuroscience research.

PubMed

Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

2012-02-01

Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification.

PubMed

Gao, Jing; Zhong, Shaoyun; Zhou, Yanting; He, Han; Peng, Shuying; Zhu, Zhenyun; Liu, Xing; Zheng, Jing; Xu, Bin; Zhou, Hu

2017-06-06

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

Evaluation of comprehensive multidimensional separations using reversed-phase, reversed-phase liquid chromatography/mass spectrometry for shotgun proteomics.

PubMed

Nakamura, Tatsuji; Kuromitsu, Junro; Oda, Yoshiya

2008-03-01

Two-dimensional liquid-chromatographic (LC) separation followed by mass spectrometric (MS) analysis was examined for the identification of peptides in complex mixtures as an alternative to widely used two-dimensional gel electrophoresis followed by MS analysis for use in proteomics. The present method involves the off-line coupling of a narrow-bore, polymer-based, reversed-phase column using an acetonitrile gradient in an alkaline mobile phase in the first dimension with octadecylsilanized silica (ODS)-based nano-LC/MS in the second dimension. After the first separation, successive fractions were acidified and dried off-line, then loaded on the second dimension column. Both columns separate peptides according to hydrophobicity under different pH conditions, but more peptides were identified than with the conventional technique for shotgun proteomics, that is, the combination of a strong cation exchange column with an ODS column, and the system was robust because no salts were included in the mobile phases. The suitability of the method for proteomics measurements was evaluated.

Proteomics insight into the biological safety of transgenic modification of rice as compared with conventional genetic breeding and spontaneous genotypic variation.

PubMed

Gong, Chun Yan; Li, Qi; Yu, Hua Tao; Wang, Zizhang; Wang, Tai

2012-05-04

The potential of unintended effects caused by transgenic events is a key issue in the commercialization of genetically modified (GM) crops. To investigate whether transgenic events cause unintended effects, we used comparative proteomics approaches to evaluate proteome differences in seeds from 2 sets of GM indica rice, herbicide-resistant Bar68-1 carrying bar and insect-resistant 2036-1a carrying cry1Ac/sck, and their respective controls D68 and MH86, as well as indica variety MH63, a parental line for breeding MH86, and japonica variety ZH10. This experimental design allowed for comparing proteome difference caused by transgenes, conventional genetic breeding, and natural genetic variation. Proteomics analysis revealed the maximum numbers of differentially expressed proteins between indica and japonica cultivars, second among indica varieties with relative small difference between MH86 and MH63, and the minimum between GM rice and respective control, thus indicating GM events do not substantially alter proteome profiles as compared with conventional genetic breeding and natural genetic variation. Mass spectrometry analysis revealed 234 proteins differentially expressed in the 6 materials, and these proteins were involved in different cellular and metabolic processes with a prominent skew toward metabolism (31.2%), protein synthesis and destination (25.2%), and defense response (22.4%). In these seed proteomes, proteins implicated in the 3 prominent biological processes showed significantly different composite expression patterns and were major factors differentiating japonica and indica cultivars, as well as indica varieties. Thus, metabolism, protein synthesis and destination, and defense response in seeds are important in differentiating rice cultivars and varieties.

An effect size filter improves the reproducibility in spectral counting-based comparative proteomics.

PubMed

Gregori, Josep; Villarreal, Laura; Sánchez, Alex; Baselga, José; Villanueva, Josep

2013-12-16

The microarray community has shown that the low reproducibility observed in gene expression-based biomarker discovery studies is partially due to relying solely on p-values to get the lists of differentially expressed genes. Their conclusions recommended complementing the p-value cutoff with the use of effect-size criteria. The aim of this work was to evaluate the influence of such an effect-size filter on spectral counting-based comparative proteomic analysis. The results proved that the filter increased the number of true positives and decreased the number of false positives and the false discovery rate of the dataset. These results were confirmed by simulation experiments where the effect size filter was used to evaluate systematically variable fractions of differentially expressed proteins. Our results suggest that relaxing the p-value cut-off followed by a post-test filter based on effect size and signal level thresholds can increase the reproducibility of statistical results obtained in comparative proteomic analysis. Based on our work, we recommend using a filter consisting of a minimum absolute log2 fold change of 0.8 and a minimum signal of 2-4 SpC on the most abundant condition for the general practice of comparative proteomics. The implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of the results obtained among independent laboratories and MS platforms. Quality control analysis of microarray-based gene expression studies pointed out that the low reproducibility observed in the lists of differentially expressed genes could be partially attributed to the fact that these lists are generated relying solely on p-values. Our study has established that the implementation of an effect size post-test filter improves the statistical results of spectral count-based quantitative proteomics. The results proved that the filter increased the number of true positives whereas decreased the false positives and the false discovery rate of the datasets. The results presented here prove that a post-test filter applying a reasonable effect size and signal level thresholds helps to increase the reproducibility of statistical results in comparative proteomic analysis. Furthermore, the implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of results obtained among independent laboratories and MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.

PubMed

Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter

2018-04-17

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

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.

Standardized protocols for quality control of MRM-based plasma proteomic workflows.

PubMed

Percy, Andrew J; Chambers, Andrew G; Smith, Derek S; Borchers, Christoph H

2013-01-04

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

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

Denef, Vincent; Shah, Manesh B; Verberkmoes, Nathan C

The recent surge in microbial genomic sequencing, combined with the development of high-throughput liquid chromatography-mass-spectrometry-based (LC/LC-MS/MS) proteomics, has raised the question of the extent to which genomic information of one strain or environmental sample can be used to profile proteomes of related strains or samples. Even with decreasing sequencing costs, it remains impractical to obtain genomic sequence for every strain or sample analyzed. Here, we evaluate how shotgun proteomics is affected by amino acid divergence between the sample and the genomic database using a probability-based model and a random mutation simulation model constrained by experimental data. To assess the effectsmore » of nonrandom distribution of mutations, we also evaluated identification levels using in silico peptide data from sequenced isolates with average amino acid identities (AAI) varying between 76 and 98%. We compared the predictions to experimental protein identification levels for a sample that was evaluated using a database that included genomic information for the dominant organism and for a closely related variant (95% AAI). The range of models set the boundaries at which half of the proteins in a proteomic experiment can be identified to be 77-92% AAI between orthologs in the sample and database. Consistent with this prediction, experimental data indicated loss of half the identifiable proteins at 90% AAI. Additional analysis indicated a 6.4% reduction of the initial protein coverage per 1% amino acid divergence and total identification loss at 86% AAI. Consequently, shotgun proteomics is capable of cross-strain identifications but avoids most crossspecies false positives.« less

QC-ART: A tool for real-time quality control assessment of mass spectrometry-based proteomics data.

PubMed

Stanfill, Bryan A; Nakayasu, Ernesto S; Bramer, Lisa M; Thompson, Allison M; Ansong, Charles K; Clauss, Therese; Gritsenko, Marina A; Monroe, Matthew E; Moore, Ronald J; Orton, Daniel J; Piehowski, Paul D; Schepmoes, Athena A; Smith, Richard D; Webb-Robertson, Bobbie-Jo; Metz, Thomas O

2018-04-17

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected.  In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration.  To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality.  QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis.  We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

Draft de novo transcriptome assembly and proteome characterization of the electric lobe of Tetronarce californica: a molecular tool for the study of cholinergic neurotransmission in the electric organ.

PubMed

Stavrianakou, Maria; Perez, Ricardo; Wu, Cheng; Sachs, Matthew S; Aramayo, Rodolfo; Harlow, Mark

2017-08-14

The electric organ of Tetronarce californica (an electric ray formerly known as Torpedo californica) is a classic preparation for biochemical studies of cholinergic neurotransmission. To broaden the usefulness of this preparation, we have performed a transcriptome assembly of the presynaptic component of the electric organ (the electric lobe). We combined our assembled transcriptome with a previous transcriptome of the postsynaptic electric organ, to define a MetaProteome containing pre- and post-synaptic components of the electric organ. Sequencing yielded 102 million paired-end 100 bp reads. De novo Trinity assembly was performed at Kmer 25 (default) and Kmers 27, 29, and 31. Trinity, generated around 103,000 transcripts, and 78,000 genes per assembly. Assemblies were evaluated based on the number of bases/transcripts assembled, RSEM-EVAL scores and informational content and completeness. We found that different assemblies scored differently according to the evaluation criteria used, and that while each individual assembly contained unique information, much of the assembly information was shared by all assemblies. To generate the presynaptic transcriptome (electric lobe), while capturing all information, assemblies were first clustered and then combined with postsynaptic transcripts (electric organ) downloaded from NCBI. The completness of the resulting clustered predicted MetaProteome was rigorously evaluated by comparing its information against the predicted proteomes from Homo sapiens, Callorhinchus milli, and the Transporter Classification Database (TCDB). In summary, we obtained a MetaProteome containing 92%, 88.5%, and 66% of the expected set of ultra-conserved sequences (i.e., BUSCOs), expected to be found for Eukaryotes, Metazoa, and Vertebrata, respectively. We cross-annotated the conserved set of proteins shared between the T. californica MetaProteome and the proteomes of H. sapiens and C. milli, using the H. sapiens genome as a reference. This information was used to predict the position in human pathways of the conserved members of the T. californica MetaProteome. We found proteins not detected before in T. californica, corresponding to processes involved in synaptic vesicle biology. Finally, we identified 42 transporter proteins in TCDB that were detected by the T. californica MetaProteome (electric fish) and not selected by a control proteome consisting of the combined proteomes of 12 widely diverse non-electric fishes by Reverse-Blast-Hit Blast. Combined, the information provided here is not only a unique tool for the study of cholinergic neurotransmission, but it is also a starting point for understanding the evolution of early vertebrates.

Proteomics of blood-based therapeutics: a promising tool for quality assurance in transfusion medicine.

PubMed

Thiele, Thomas; Steil, Leif; Völker, Uwe; Greinacher, Andreas

2007-01-01

Blood-based therapeutics are cellular or plasma components derived from human blood. Their production requires appropriate selection and treatment of the donor and processing of cells or plasma proteins. In contrast to clearly defined, chemically synthesized drugs, blood-derived therapeutics are highly complex mixtures of plasma proteins or even more complex cells. Pathogen transmission by the product as well as changes in the integrity of blood constituents resulting in loss of function or immune modulation are currently important issues in transfusion medicine. Protein modifications can occur during various steps of the production process, such as acquisition, enrichment of separate components (e.g. coagulation factors, cell populations), virus inactivation, conservation, and storage. Contemporary proteomic strategies allow a comprehensive assessment of protein modifications with high coverage, offer capabilities for qualitative and even quantitative analysis, and for high-throughput protein identification. Traditionally, proteomics approaches predominantly relied on two-dimensional gel electrophoresis (2-DE). Even if 2-DE is still state of the art, it has inherent limitations that are mainly based on the physicochemical properties of the proteins analyzed; for example, proteins with extremes in molecular mass and hydrophobicity (most membrane proteins) are difficult to assess by 2-DE. These limitations have fostered the development of mass spectrometry centered on non-gel-based separation approaches, which have proven to be highly successful and are thus complementing and even partially replacing 2-DE-based approaches. Although blood constituents have been extensively analyzed by proteomics, this technology has not been widely applied to assess or even improve blood-derived therapeutics, or to monitor the production processes. As proteomic technologies have the capacity to provide comprehensive information about changes occurring during processing and storage of blood products, proteomics can potentially guide improvement of pathogen inactivation procedures and engineering of stem cells, and may also allow a better understanding of factors influencing the immunogenicity of blood-derived therapeutics. An important development in proteomics is the reduction of inter-assay variability. This now allows the screening of samples taken from the same product over time or before and after processing. Optimized preparation procedures and storage conditions will reduce the risk of protein alterations, which in turn may contribute to better recovery, reduced exposure to allogeneic proteins, and increased transfusion safety.

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets.

PubMed

Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo

2018-04-06

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .

Proteomics reveals the effects of sustained weight loss on the human plasma proteome.

PubMed

Geyer, Philipp E; Wewer Albrechtsen, Nicolai J; Tyanova, Stefka; Grassl, Niklas; Iepsen, Eva W; Lundgren, Julie; Madsbad, Sten; Holst, Jens J; Torekov, Signe S; Mann, Matthias

2016-12-22

Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill-defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry-based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual-specific protein levels with wide-ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte-secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of -16% and +37%, respectively (P < 10 -13 ), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten-protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.

PubMed

Ghodasara, P; Sadowski, P; Satake, N; Kopp, S; Mills, P C

2017-12-01

Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Three Commonly-used Diuretics on the Urinary Proteome

PubMed Central

Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

2014-01-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography–tandem mass spectrometry (LC–MS/MS). Based on the criteria of P ⩽ 0.05, a fold change ⩾2, a spectral count ⩾5, and false positive rate (FDR) ⩽1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC–MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. PMID:24508280

A Proteomic View on the Role of Legume Symbiotic Interactions

PubMed Central

Larrainzar, Estíbaliz; Wienkoop, Stefanie

2017-01-01

Legume plants are key elements in sustainable agriculture and represent a significant source of plant-based protein for humans and animal feed worldwide. One specific feature of the family is the ability to establish nitrogen-fixing symbiosis with Rhizobium bacteria. Additionally, like most vascular flowering plants, legumes are able to form a mutualistic endosymbiosis with arbuscular mycorrhizal (AM) fungi. These beneficial associations can enhance the plant resistance to biotic and abiotic stresses. Understanding how symbiotic interactions influence and increase plant stress tolerance are relevant questions toward maintaining crop yield and food safety in the scope of climate change. Proteomics offers numerous tools for the identification of proteins involved in such responses, allowing the study of sub-cellular localization and turnover regulation, as well as the discovery of post-translational modifications (PTMs). The current work reviews the progress made during the last decades in the field of proteomics applied to the study of the legume-Rhizobium and -AM symbioses, and highlights their influence on the plant responses to pathogens and abiotic stresses. We further discuss future perspectives and new experimental approaches that are likely to have a significant impact on the field including peptidomics, mass spectrometric imaging, and quantitative proteomics. PMID:28769967

The Proteomic Response of Arabidopsis thaliana to Cadmium Sulfide Quantum Dots, and Its Correlation with the Transcriptomic Response

PubMed Central

Marmiroli, Marta; Imperiale, Davide; Pagano, Luca; Villani, Marco; Zappettini, Andrea; Marmiroli, Nelson

2015-01-01

A fuller understanding of the interaction between plants and engineered nanomaterials is of topical relevance because the latter are beginning to find applications in agriculture and the food industry. There is a growing need to establish objective safety criteria for their use. The recognition of two independent Arabidopsis thaliana mutants displaying a greater level of tolerance than the wild type plant to exposure to cadmium sulfide quantum dots (CdS QDs) has offered the opportunity to characterize the tolerance response at the physiological, transcriptomic, and proteomic levels. Here, a proteomics-based comparison confirmed the conclusions drawn from an earlier transcriptomic analysis that the two mutants responded to CdS QD exposure differently both to the wild type and to each other. Just over half of the proteomic changes mirrored documented changes at the level of gene transcription, but a substantial number of transcript/gene product pairs were altered in the opposite direction. An interpretation of the discrepancies is given, along with some considerations regarding the use and significance of -omics when monitoring the potential toxicity of ENMs for health and environment. PMID:26732871

Quantitative Shotgun Proteomics Using a Uniform 15N-Labeled Standard to Monitor Proteome Dynamics in Time Course Experiments Reveals New Insights into the Heat Stress Response of Chlamydomonas reinhardtii*

PubMed Central

Mühlhaus, Timo; Weiss, Julia; Hemme, Dorothea; Sommer, Frederik; Schroda, Michael

2011-01-01

Crop-plant-yield safety is jeopardized by temperature stress caused by the global climate change. To take countermeasures by breeding and/or transgenic approaches it is essential to understand the mechanisms underlying plant acclimation to heat stress. To this end proteomics approaches are most promising, as acclimation is largely mediated by proteins. Accordingly, several proteomics studies, mainly based on two-dimensional gel-tandem MS approaches, were conducted in the past. However, results often were inconsistent, presumably attributable to artifacts inherent to the display of complex proteomes via two-dimensional-gels. We describe here a new approach to monitor proteome dynamics in time course experiments. This approach involves full 15N metabolic labeling and mass spectrometry based quantitative shotgun proteomics using a uniform 15N standard over all time points. It comprises a software framework, IOMIQS, that features batch job mediated automated peptide identification by four parallelized search engines, peptide quantification and data assembly for the processing of large numbers of samples. We have applied this approach to monitor proteome dynamics in a heat stress time course using the unicellular green alga Chlamydomonas reinhardtii as model system. We were able to identify 3433 Chlamydomonas proteins, of which 1116 were quantified in at least three of five time points of the time course. Statistical analyses revealed that levels of 38 proteins significantly increased, whereas levels of 206 proteins significantly decreased during heat stress. The increasing proteins comprise 25 (co-)chaperones and 13 proteins involved in chromatin remodeling, signal transduction, apoptosis, photosynthetic light reactions, and yet unknown functions. Proteins decreasing during heat stress were significantly enriched in functional categories that mediate carbon flux from CO2 and external acetate into protein biosynthesis, which also correlated with a rapid, but fully reversible cell cycle arrest after onset of stress. Our approach opens up new perspectives for plant systems biology and provides novel insights into plant stress acclimation. PMID:21610104

Influence of Diet on the Proteome of Drosophila Melanogaster as Assessed by Two-Dimensional Gel Electrophoresis and Capillary Liquid Chromatography–Mass Spectrometry: The Hamburger Effect Revisited

PubMed Central

Culwell, Thomas F.; Thulin, Craig D.; Merrell, Karen J.; Graves, Steven W.

2008-01-01

Proteomic biomarker discovery has been called into question. Diamandis hypothesized that seemingly trivial factors, such as eating a hamburger, may cause sufficient proteomic change as to confound proteomic differences. This has been termed the hamburger effect. Little is known about the variability of complex proteomes in response to the environment. Two methods—two-dimensional gel electrophoresis (2DGE) and capillary liquid chromatography–electrospray ionization time-of-flight mass spectrometry (LCMS)—were used to study the hamburger effect in two cross-sections of the soluble fruit fly proteome. 2DGE measured abundant proteins, whereas LCMS measured small proteins and peptides. Proteomic differences between males and females were first evaluated to assess the discriminatory capability of the methods. Likewise, wild-type and white-eyed flies were analyzed as a further demonstration that genetically based proteomic differences could be observed above the background analytical variation. Then dietary interventions were imposed. Ethanol was added to the diet of some populations without significant proteomic effect. However, after a 24-h fast, proteomic differences were found using LCMS but not 2DGE. Even so, only three of ~1000 molecular species were altered significantly, suggesting that the influence of even an extreme diet change produced only modest proteomic variability, and that much of the fruit fly proteome remains relatively constant in response to diet. These experiments suggest that proteomics can be a viable approach to biomarker discovery. PMID:19137114

Spaceflight induced changes in the human proteome.

PubMed

Kononikhin, Alexey S; Starodubtseva, Natalia L; Pastushkova, Lyudmila Kh; Kashirina, Daria N; Fedorchenko, Kristina Yu; Brhozovsky, Alexander G; Popov, Igor A; Larina, Irina M; Nikolaev, Evgeny N

2017-01-01

Spaceflight is one of the most extreme conditions encountered by humans: Individuals are exposed to radiation, microgravity, hypodynamia, and will experience isolation. A better understanding of the molecular processes induced by these factors may allow us to develop personalized countermeasures to minimize risks to astronauts. Areas covered: This review is a summary of literature searches from PubMed, NASA, Roskosmos and the authors' research experiences and opinions. The review covers the available proteomic data on the effects of spaceflight factors on the human body, including both real space missions and ground-based model experiments. Expert commentary: Overall, the authors believe that the present background, methodology and equipment improvements will enhance spaceflight safety and support accumulation of new knowledge on how organisms adapt to extreme conditions.

Exploitation of molecular profiling techniques for GM food safety assessment.

PubMed

Kuiper, Harry A; Kok, Esther J; Engel, Karl-Heinz

2003-04-01

Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions.

Proteomic analysis of cow, yak, buffalo, goat and camel milk whey proteins: quantitative differential expression patterns.

PubMed

Yang, Yongxin; Bu, Dengpan; Zhao, Xiaowei; Sun, Peng; Wang, Jiaqi; Zhou, Lingyun

2013-04-05

To aid in unraveling diverse genetic and biological unknowns, a proteomic approach was used to analyze the whey proteome in cow, yak, buffalo, goat, and camel milk based on the isobaric tag for relative and absolute quantification (iTRAQ) techniques. This analysis is the first to produce proteomic data for the milk from the above-mentioned animal species: 211 proteins have been identified and 113 proteins have been categorized according to molecular function, cellular components, and biological processes based on gene ontology annotation. The results of principal component analysis showed significant differences in proteomic patterns among goat, camel, cow, buffalo, and yak milk. Furthermore, 177 differentially expressed proteins were submitted to advanced hierarchical clustering. The resulting clustering pattern included three major sample clusters: (1) cow, buffalo, and yak milk; (2) goat, cow, buffalo, and yak milk; and (3) camel milk. Certain proteins were chosen as characterization traits for a given species: whey acidic protein and quinone oxidoreductase for camel milk, biglycan for goat milk, uncharacterized protein (Accession Number: F1MK50 ) for yak milk, clusterin for buffalo milk, and primary amine oxidase for cow milk. These results help reveal the quantitative milk whey proteome pattern for analyzed species. This provides information for evaluating adulteration of specific specie milk and may provide potential directions for application of specific milk protein production based on physiological differences among animal species.

A multi-center study benchmarks software tools for label-free proteome quantification

PubMed Central

Gillet, Ludovic C; Bernhardt, Oliver M.; MacLean, Brendan; Röst, Hannes L.; Tate, Stephen A.; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I.; Aebersold, Ruedi; Tenzer, Stefan

2016-01-01

The consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra), a method that uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test datasets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation windows setups. For consistent evaluation we developed LFQbench, an R-package to calculate metrics of precision and accuracy in label-free quantitative MS, and report the identification performance, robustness and specificity of each software tool. Our reference datasets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. PMID:27701404

A multicenter study benchmarks software tools for label-free proteome quantification.

PubMed

Navarro, Pedro; Kuharev, Jörg; Gillet, Ludovic C; Bernhardt, Oliver M; MacLean, Brendan; Röst, Hannes L; Tate, Stephen A; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I; Aebersold, Ruedi; Tenzer, Stefan

2016-11-01

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation.

PubMed

Megger, Dominik A; Padden, Juliet; Rosowski, Kristin; Uszkoreit, Julian; Bracht, Thilo; Eisenacher, Martin; Gerges, Christian; Neuhaus, Horst; Schumacher, Brigitte; Schlaak, Jörg F; Sitek, Barbara

2017-02-10

The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would lead to an unmanageable number of samples to be analyzed if sample preparation protocols with extensive fractionation methods are applied. Hence, the performance of simple workflows allowing for "one sample, one shot" experiments have been evaluated in this study. In detail, sixteen different protocols implying modifications at the stages of desalting, delipidation, deglycosylation and tryptic digestion have been examined. Each method has been individually evaluated regarding various performance criteria and comparative analyses have been conducted to uncover possible complementarities. Here, the best performance in terms of proteome coverage has been assessed for a combination of acetone precipitation with in-gel digestion. Finally, a mapping of all obtained protein identifications with putative biomarkers for hepatocellular carcinoma (HCC) and cholangiocellular carcinoma (CCC) revealed several proteins easily detectable in bile fluid. These results can build the basis for future studies with large and well-defined patient cohorts in a more disease-related context. Human bile fluid is a proximal body fluid and supposed to be a potential source of disease markers. However, due to its biochemical composition, the proteome analysis of bile fluid still represents a challenging task and is therefore mostly conducted using extensive fractionation procedures. This in turn leads to a high number of mass spectrometric measurements for one biological sample. Considering the fact that in order to overcome the biological variability a high number of biological samples needs to be analyzed in biomarker discovery studies, this leads to the dilemma of an unmanageable number of necessary MS-based analyses. Hence, easy sample preparation protocols are demanded representing a compromise between proteome coverage and simplicity. In the presented study, such protocols have been evaluated regarding various technical criteria (e.g. identification rates, missed cleavages, chromatographic separation) uncovering the strengths and weaknesses of various methods. Furthermore, a cumulative bile proteome list has been generated that extends the current bile proteome catalog by 248 proteins. Finally, a mapping with putative biomarkers for hepatocellular carcinoma (HCC) and cholangiocellular carcinoma (CCC) derived from tissue-based studies, revealed several of these proteins being easily and reproducibly detectable in human bile. Therefore, the presented technical work represents a solid base for future disease-related studies. Copyright © 2016 Elsevier B.V. All rights reserved.

The ProteoRed MIAPE web toolkit: A User-friendly Framework to Connect and Share Proteomics Standards*

PubMed Central

Medina-Aunon, J. Alberto; Martínez-Bartolomé, Salvador; López-García, Miguel A.; Salazar, Emilio; Navajas, Rosana; Jones, Andrew R.; Paradela, Alberto; Albar, Juan P.

2011-01-01

The development of the HUPO-PSI's (Proteomics Standards Initiative) standard data formats and MIAPE (Minimum Information About a Proteomics Experiment) guidelines should improve proteomics data sharing within the scientific community. Proteomics journals have encouraged the use of these standards and guidelines to improve the quality of experimental reporting and ease the evaluation and publication of manuscripts. However, there is an evident lack of bioinformatics tools specifically designed to create and edit standard file formats and reports, or embed them within proteomics workflows. In this article, we describe a new web-based software suite (The ProteoRed MIAPE web toolkit) that performs several complementary roles related to proteomic data standards. First, it can verify that the reports fulfill the minimum information requirements of the corresponding MIAPE modules, highlighting inconsistencies or missing information. Second, the toolkit can convert several XML-based data standards directly into human readable MIAPE reports stored within the ProteoRed MIAPE repository. Finally, it can also perform the reverse operation, allowing users to export from MIAPE reports into XML files for computational processing, data sharing, or public database submission. The toolkit is thus the first application capable of automatically linking the PSI's MIAPE modules with the corresponding XML data exchange standards, enabling bidirectional conversions. This toolkit is freely available at http://www.proteored.org/MIAPE/. PMID:21983993

Effects of three commonly-used diuretics on the urinary proteome.

PubMed

Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

2014-06-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the criteria of P≤0.05, a fold change ≥2, a spectral count ≥5, and false positive rate (FDR) ≤1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC-MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. Copyright © 2014. Production and hosting by Elsevier Ltd.

Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow

PubMed Central

Morisawa, Hiraku; Hirota, Mikako; Toda, Tosifusa

2006-01-01

Background In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies. Results We developed an open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. It supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates. Conclusion Our new open source LIMS is now available as a basic model for proteome informatics, and is accessible for further improvement. We hope that many research scientists working in the field of proteomics will evaluate our LIMS and suggest ways in which it can be improved. PMID:17018156

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

PubMed Central

Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R

2009-01-01

Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk. PMID:19166578

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

Emery, Samantha J; Lacey, Ernest; Haynes, Paul A

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Birth of plant proteomics in India: a new horizon.

PubMed

Narula, Kanika; Pandey, Aarti; Gayali, Saurabh; Chakraborty, Niranjan; Chakraborty, Subhra

2015-09-08

In the post-genomic era, proteomics is acknowledged as the next frontier for biological research. Although India has a long and distinguished tradition in protein research, the initiation of proteomics studies was a new horizon. Protein research witnessed enormous progress in protein separation, high-resolution refinements, biochemical identification of the proteins, protein-protein interaction, and structure-function analysis. Plant proteomics research, in India, began its journey on investigation of the proteome profiling, complexity analysis, protein trafficking, and biochemical modeling. The research article by Bhushan et al. in 2006 marked the birth of the plant proteomics research in India. Since then plant proteomics studies expanded progressively and are now being carried out in various institutions spread across the country. The compilation presented here seeks to trace the history of development in the area during the past decade based on publications till date. In this review, we emphasize on outcomes of the field providing prospects on proteomic pathway analyses. Finally, we discuss the connotation of strategies and the potential that would provide the framework of plant proteome research. The past decades have seen rapidly growing number of sequenced plant genomes and associated genomic resources. To keep pace with this increasing body of data, India is in the provisional phase of proteomics research to develop a comparative hub for plant proteomes and protein families, but it requires a strong impetus from intellectuals, entrepreneurs, and government agencies. Here, we aim to provide an overview of past, present and future of Indian plant proteomics, which would serve as an evaluation platform for those seeking to incorporate proteomics into their research programs. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

ApoptoProteomics, an integrated database for analysis of proteomics data obtained from apoptotic cells.

PubMed

Arntzen, Magnus Ø; Thiede, Bernd

2012-02-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no.

ApoptoProteomics, an Integrated Database for Analysis of Proteomics Data Obtained from Apoptotic Cells*

PubMed Central

Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no. PMID:22067098

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

PubMed

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF+. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations. Copyright © 2016. Published by Elsevier B.V.

JVirGel 2.0: computational prediction of proteomes separated via two-dimensional gel electrophoresis under consideration of membrane and secreted proteins.

PubMed

Hiller, Karsten; Grote, Andreas; Maneck, Matthias; Münch, Richard; Jahn, Dieter

2006-10-01

After the publication of JVirGel 1.0 in 2003 we got many requests and suggestions from the proteomics community to further improve the performance of the software and to add additional useful new features. The integration of the PrediSi algorithm for the prediction of signal peptides for the Sec-dependent protein export into JVirGel 2.0 allows the exclusion of most exported preproteins from calculated proteomic maps and provides the basis for the calculation of Sec-based secretomes. A tool for the identification of transmembrane helices carrying proteins (JCaMelix) and the prediction of the corresponding membrane proteome was added. Finally, in order to directly compare experimental and calculated proteome data, a function to overlay and evaluate predicted and experimental two-dimensional gels was included. JVirGel 2.0 is freely available as precompiled package for the installation on Windows or Linux operating systems. Furthermore, there is a completely platform-independent Java version available for download. Additionally, we provide a Java Server Pages based version of JVirGel 2.0 which can be operated in nearly all web browsers. All versions are accessible at http://www.jvirgel.de

Proteomics with Mass Spectrometry Imaging: Beyond Amyloid Typing.

PubMed

Lavatelli, Francesca; Merlini, Giampaolo

2018-04-01

Detection and typing of amyloid deposits in tissues are two crucial steps in the management of systemic amyloidoses. The presence of amyloid deposits is routinely evaluated through Congo red staining, whereas proteomics is now a mainstay in the identification of the deposited proteins. In article number 1700236, Winter et al. [Proteomics 2017, 17, Issue 22] describe a novel method based on MALDI-MS imaging coupled to ion mobility separation and peptide filtering, to detect the presence of amyloid in histology samples and to identify its composition, while preserving the spatial distribution of proteins in tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In-gel and OFFGEL-based proteomic approach for authentication of meat species from minced meat and meat products.

PubMed

Naveena, Basappa M; Jagadeesh, Deepak S; Kamuni, Veeranna; Muthukumar, Muthupalani; Kulkarni, Vinayak V; Kiran, Mohan; Rapole, Srikanth

2018-02-01

Fraudulent mislabelling of processed meat products on a global scale that cannot be detected using conventional techniques necessitates sensitive, robust and accurate methods of meat authentication to ensure food safety and public health. In the present study, we developed an in-gel (two-dimensional gel electrophoresis, 2DE) and OFFGEL-based proteomic method for authenticating raw and cooked water buffalo (Bubalus bubalis), sheep (Ovis aries) and goat (Caprus hircus) meat and their mixes. The matrix-assisted liquid desorption/ionization time-of-flight mass spectrometric analysis of proteins separated using 2DE or OFFGEL electrophoresis delineated species-specific peptide biomarkers derived from myosin light chain 1 and 2 (MLC1 and MLC2) of buffalo-sheep-goat meat mix in definite proportions at 98:1:1, 99:0.5:0.5 and 99.8:0.1:0.1 that were found stable to resist thermal processing. In-gel and OFFGEL-based proteomic approaches are efficient in authenticating meat mixes spiked at minimum 1.0% and 0.1% levels, respectively, in triple meat mix for both raw and cooked samples. The study demonstrated that authentication of meat from a complex mix of three closely related species requires identification of more than one species-specific peptide due to close similarity between their amino acid sequences. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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

Webb-Robertson, Bobbie-Jo M.; Wiberg, Holli K.; Matzke, Melissa M.

In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yieldedmore » the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. In summary, on the basis of the observations in this review, the goal for imputation in the field of computational proteomics should be to develop new approaches that work generically for this data type and new strategies to guide users in the selection of the best imputation for their dataset and analysis objectives.« less

Characterization of the rat cerebrospinal fluid proteome following acute cerebral ischemia using an aptamer-based proteomic technology.

PubMed

Simats, Alba; García-Berrocoso, Teresa; Ramiro, Laura; Giralt, Dolors; Gill, Natalia; Penalba, Anna; Bustamante, Alejandro; Rosell, Anna; Montaner, Joan

2018-05-21

The limited accessibility to the brain has turned the cerebrospinal fluid (CSF) into a valuable source that may contribute to the complete understanding of the stroke pathophysiology. Here we have described the CSF proteome in the hyper-acute phase of cerebral ischemia by performing an aptamer-based proteomic assay (SOMAscan) in CSF samples collected before and 30 min after male Wistar rats had undergone a 90 min Middle Cerebral Artery Occlusion (MCAO) or sham-surgery. Proteomic results indicated that cerebral ischemia acutely increased the CSF levels of 716 proteins, mostly overrepresented in leukocyte chemotaxis and neuronal death processes. Seven promising candidates were further evaluated in rat plasma and brain (CKB, CaMK2A, CaMK2B, CaMK2D, PDXP, AREG, CMPK). The 3 CaMK2 family-members and CMPK early decreased in the infarcted brain area and, together with AREG, co-localized with neurons. Conversely, CKB levels remained consistent after the insult and specifically matched with astrocytes. Further exploration of these candidates in human plasma revealed the potential of CKB and CMPK to diagnose stroke, while CaMK2B and CMPK resulted feasible biomarkers of functional stroke outcome. Our findings provided insights into the CSF proteome following cerebral ischemia and identified new outstanding proteins that might be further considered as potential biomarkers of stroke.

Evaluation of the salivary proteome as a surrogate tissue for systems biology approaches to understanding appetite.

PubMed

Harden, Charlotte J; Perez-Carrion, Kristine; Babakordi, Zara; Plummer, Sue F; Hepburn, Natalie; Barker, Margo E; Wright, Phillip C; Evans, Caroline A; Corfe, Bernard M

2012-06-06

Current measurement of appetite depends upon tools that are either subjective (visual analogue scales), or invasive (blood). Saliva is increasingly recognised as a valuable resource for biomarker analysis. Proteomics workflows may provide alternative means for the assessment of appetitive response. The study aimed to assess the potential value of the salivary proteome to detect novel biomarkers of appetite using an iTRAQ-based workflow. Diurnal variation of salivary protein concentrations was assessed. A randomised, controlled, crossover study examined the effects on the salivary proteome of isocaloric doses of various long chain fatty acid (LCFA) oil emulsions compared to no treatment (NT). Fasted males provided saliva samples before and following NT or dosing with LCFA emulsions. The oil component of the DHA emulsion contained predominantly docosahexaenoic acid and the oil component of OA contained predominantly oleic acid. Several proteins were present in significantly (p<0.05) different quantities in saliva samples taken following treatments compared to fasting samples. DHA caused alterations in thioredoxin and serpin B4 relative to OA and NT. A further study evaluated energy intake (EI) in response to LCFA in conjunction with subjective appetite scoring. DHA was associated with significantly lower EI relative to NT and OA (p=0.039). The collective data suggest investigation of salivary proteome may be of value in appetitive response. This article is part of a Special Issue entitled: Proteomics: The clinical link. Copyright © 2011 Elsevier B.V. All rights reserved.

Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

PubMed

Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Van Dorssaeler, Alain; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

2016-01-30

Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Omics, microbial modeling, and food safety information infrastructure: a food safety perspective

USDA-ARS?s Scientific Manuscript database

Over the last three decades, advances in a variety of cutting-edge “omics” technologies, including genomics, proteomics, and metabolomics, as well as in molecular and mathematical modeling approaches have provided the ability to more easily determine and interpret the mechanisms underlying pathogene...

Use of Foodomics for Control of Food Processing and Assessing of Food Safety.

PubMed

Josić, D; Peršurić, Ž; Rešetar, D; Martinović, T; Saftić, L; Kraljević Pavelić, S

Food chain, food safety, and food-processing sectors face new challenges due to globalization of food chain and changes in the modern consumer preferences. In addition, gradually increasing microbial resistance, changes in climate, and human errors in food handling remain a pending barrier for the efficient global food safety management. Consequently, a need for development, validation, and implementation of rapid, sensitive, and accurate methods for assessment of food safety often termed as foodomics methods is required. Even though, the growing role of these high-throughput foodomic methods based on genomic, transcriptomic, proteomic, and metabolomic techniques has yet to be completely acknowledged by the regulatory agencies and bodies. The sensitivity and accuracy of these methods are superior to previously used standard analytical procedures and new methods are suitable to address a number of novel requirements posed by the food production sector and global food market. © 2017 Elsevier Inc. All rights reserved.

Changes in the leaf proteome profile of Withania somnifera (L.) Dunal in response to Alternaria alternata infection

PubMed Central

Singh, Varinder; Singh, Baldev; Joshi, Robin; Jaju, Puneet

2017-01-01

Withania somnifera is a high value medicinal plant which is used against large number of ailments. The medicinal properties of the plant attributes to a wide array of important secondary metabolites. The plant is predominantly infected with leaf spot pathogen Alternaria alternata, which leads to substantial biodeterioration of pharmaceutically important metabolites. To develop an effective strategy to combat this disease, proteomics based approach could be useful. Hence, in the present study, three different protein extraction methods tris-buffer based, phenol based and trichloroacetic acid-acetone (TCA-acetone) based method were comparatively evaluated for two-dimensional electrophoresis (2-DE) analysis of W. somnifera. TCA-acetone method was found to be most effective and was further used to identify differentially expressed proteins in response to fungal infection. Thirty-eight differentially expressed proteins were identified by matrix assisted laser desorption/ionization time of flight-mass spectrometry (MALDI TOF/TOF MS/MS). The known proteins were categorized into eight different groups based on their function and maximum proteins belonged to energy and metabolism, cell structure, stress and defense and RNA/DNA categories. Differential expression of some key proteins were also crosschecked at transcriptomic level by using qRT-PCR and were found to be consistent with the 2-DE data. These outcomes enable us to evaluate modifications that take place at the proteomic level during a compatible host pathogen interaction. The comparative proteome analysis conducted in this paper revealed the involvement of many key proteins in the process of pathogenesis and further investigation of these identified proteins could assist in the discovery of new strategies for the development of pathogen resistance in the plant. PMID:28575108

Advancing Clinical Proteomics via Analysis Based on Biological Complexes: A Tale of Five Paradigms.

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2016-09-02

Despite advances in proteomic technologies, idiosyncratic data issues, for example, incomplete coverage and inconsistency, resulting in large data holes, persist. Moreover, because of naïve reliance on statistical testing and its accompanying p values, differential protein signatures identified from such proteomics data have little diagnostic power. Thus, deploying conventional analytics on proteomics data is insufficient for identifying novel drug targets or precise yet sensitive biomarkers. Complex-based analysis is a new analytical approach that has potential to resolve these issues but requires formalization. We categorize complex-based analysis into five method classes or paradigms and propose an even-handed yet comprehensive evaluation rubric based on both simulated and real data. The first four paradigms are well represented in the literature. The fifth and newest paradigm, the network-paired (NP) paradigm, represented by a method called Extremely Small SubNET (ESSNET), dominates in precision-recall and reproducibility, maintains strong performance in small sample sizes, and sensitively detects low-abundance complexes. In contrast, the commonly used over-representation analysis (ORA) and direct-group (DG) test paradigms maintain good overall precision but have severe reproducibility issues. The other two paradigms considered here are the hit-rate and rank-based network analysis paradigms; both of these have good precision-recall and reproducibility, but they do not consider low-abundance complexes. Therefore, given its strong performance, NP/ESSNET may prove to be a useful approach for improving the analytical resolution of proteomics data. Additionally, given its stability, it may also be a powerful new approach toward functional enrichment tests, much like its ORA and DG counterparts.

Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics.

PubMed

Shen, Xiaomeng; Hu, Qiang; Li, Jun; Wang, Jianmin; Qu, Jun

2015-10-02

Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true-positives/negatives are known and span a wide concentration range. It was observed that the EN method correctly reflects the null distribution in a proteomic system and accurately measures false altered proteins discovery rate (FADR). In summary, the EN method provides a straightforward, practical, and accurate alternative to statistics-based approaches for the development and evaluation of proteomic experiments and can be universally adapted to various types of quantitative techniques.

Omics approaches in food safety: fulfilling the promise?

PubMed Central

Bergholz, Teresa M.; Moreno Switt, Andrea I.; Wiedmann, Martin

2014-01-01

Genomics, transcriptomics, and proteomics are rapidly transforming our approaches to detection, prevention and treatment of foodborne pathogens. Microbial genome sequencing in particular has evolved from a research tool into an approach that can be used to characterize foodborne pathogen isolates as part of routine surveillance systems. Genome sequencing efforts will not only improve outbreak detection and source tracking, but will also create large amounts of foodborne pathogen genome sequence data, which will be available for data mining efforts that could facilitate better source attribution and provide new insights into foodborne pathogen biology and transmission. While practical uses and application of metagenomics, transcriptomics, and proteomics data and associated tools are less prominent, these tools are also starting to yield practical food safety solutions. PMID:24572764

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

Dried Blood Spot Proteomics: Surface Extraction of Endogenous Proteins Coupled with Automated Sample Preparation and Mass Spectrometry Analysis

NASA Astrophysics Data System (ADS)

Martin, Nicholas J.; Bunch, Josephine; Cooper, Helen J.

2013-08-01

Dried blood spots offer many advantages as a sample format including ease and safety of transport and handling. To date, the majority of mass spectrometry analyses of dried blood spots have focused on small molecules or hemoglobin. However, dried blood spots are a potentially rich source of protein biomarkers, an area that has been overlooked. To address this issue, we have applied an untargeted bottom-up proteomics approach to the analysis of dried blood spots. We present an automated and integrated method for extraction of endogenous proteins from the surface of dried blood spots and sample preparation via trypsin digestion by use of the Advion Biosciences Triversa Nanomate robotic platform. Liquid chromatography tandem mass spectrometry of the resulting digests enabled identification of 120 proteins from a single dried blood spot. The proteins identified cross a concentration range of four orders of magnitude. The method is evaluated and the results discussed in terms of the proteins identified and their potential use as biomarkers in screening programs.

Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

PubMed Central

Law, Kai P.; Han, Ting-Li; Tong, Chao; Baker, Philip N.

2015-01-01

Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered. PMID:26006232

Proteomic identification of processes and pathways characteristic of osmoregulatory tissues in spiny dogfish shark (Squalus acanthias).

PubMed

Lee, Jinoo; Valkova, Nelly; White, Mark P; Kültz, Dietmar

2006-09-01

We used dogfish shark (Squalus acanthias) as a model for proteome analysis of six different tissues to evaluate tissue-specific protein expression on a global scale and to deduce specific functions and the relatedness of multiple tissues from their proteomes. Proteomes of heart, brain, kidney, intestine, gill, and rectal gland were separated by two-dimensional gel electrophoresis (2DGE), gel images were matched using Delta 2D software and then evaluated for tissue-specific proteins. Sixty-one proteins (4%) were found to be in only a single type of tissue and 535 proteins (36%) were equally abundant in all six tissues. Relatedness between tissues was assessed based on tissue-specific expression patterns of all 1465 consistently resolved protein spots. This analysis revealed that tissues with osmoregulatory function (kidney, intestine, gill, rectal gland) were more similar in their overall proteomes than non-osmoregulatory tissues (heart, brain). Sixty-one proteins were identified by MALDI-TOF/TOF mass spectrometry and biological functions characteristic of osmoregulatory tissues were derived from gene ontology and molecular pathway analysis. Our data demonstrate that the molecular machinery for energy and urea metabolism and the Rho-GTPase/cytoskeleton pathway are enriched in osmoregulatory tissues of sharks. Our work provides a strong rationale for further study of the contribution of these mechanisms to the osmoregulation of marine sharks.

CPTAC Assay Portal: a repository of targeted proteomic assays

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

Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.

2014-06-27

To address these issues, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, MS-based, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data for highly characterized assays. A primary aim of the NCI-supported portal is to bring together clinicians or biologists and analytical chemists to answer hypothesis-driven questions using targeted, MS-based assays. Assay content is easily accessed through queries and filters, enabling investigatorsmore » to find assays to proteins relevant to their areas of interest. Detailed characterization data are available for each assay, enabling researchers to evaluate assay performance prior to launching the assay in their own laboratory.« less

Proteomic Investigations into Hemodialysis Therapy

PubMed Central

Bonomini, Mario; Sirolli, Vittorio; Pieroni, Luisa; Felaco, Paolo; Amoroso, Luigi; Urbani, Andrea

2015-01-01

The retention of a number of solutes that may cause adverse biochemical/biological effects, called uremic toxins, characterizes uremic syndrome. Uremia therapy is based on renal replacement therapy, hemodialysis being the most commonly used modality. The membrane contained in the hemodialyzer represents the ultimate determinant of the success and quality of hemodialysis therapy. Membrane’s performance can be evaluated in terms of removal efficiency for unwanted solutes and excess fluid, and minimization of negative interactions between the membrane material and blood components that define the membrane’s bio(in)compatibility. Given the high concentration of plasma proteins and the complexity of structural functional relationships of this class of molecules, the performance of a membrane is highly influenced by its interaction with the plasma protein repertoire. Proteomic investigations have been increasingly applied to describe the protein uremic milieu, to compare the blood purification efficiency of different dialyzer membranes or different extracorporeal techniques, and to evaluate the adsorption of plasma proteins onto hemodialysis membranes. In this article, we aim to highlight investigations in the hemodialysis setting making use of recent developments in proteomic technologies. Examples are presented of why proteomics may be helpful to nephrology and may possibly affect future directions in renal research. PMID:26690416

Phosphorylation of plastoglobular proteins in Arabidopsis thaliana

PubMed Central

Lohscheider, Jens N.; Friso, Giulia; van Wijk, Klaas J.

2016-01-01

Plastoglobules (PGs) are plastid lipid–protein particles with a small specialized proteome and metabolome. Among the 30 core PG proteins are six proteins of the ancient ABC1 atypical kinase (ABC1K) family and their locations in an Arabidopsis mRNA-based co-expression network suggested central regulatory roles. To identify candidate ABC1K targets and a possible ABC1K hierarchical phosphorylation network within the chloroplast PG proteome, we searched Arabidopsis phosphoproteomics data from publicly available sources. Evaluation of underlying spectra and/or associated information was challenging for a variety of reasons, but supported pSer sites and a few pThr sites in nine PG proteins, including five FIBRILLINS. PG phosphorylation motifs are discussed in the context of possible responsible kinases. The challenges of collection and evaluation of published Arabidopsis phosphorylation data are discussed, illustrating the importance of deposition of all mass spectrometry data in well-organized repositories such as PRIDE and ProteomeXchange. This study provides a starting point for experimental testing of phosho-sites in PG proteins and also suggests that phosphoproteomics studies specifically designed toward the PG proteome and its ABC1K are needed to understand phosphorylation networks in these specialized particles. PMID:26962209

Biochemical Markers of Brain Injury: An Integrated Proteomics-Based Approach

DTIC Science & Technology

2006-02-01

Anthony J Williams, X-C May Lu, Renwu Chen, Zhilin Liao, Rebeca Connors, Kevin K Wang, Ron L Hayes, Frank C Tortella, Jitendra R Dave. High throughput... YANG , A., et al. (2002). Evalu- ation of two-dimensional differential gel electrophoresis for proteomic expression analysis of a model breast cancer cell...apoptosis. J. Biol. Chem. 279, 1030–1039. Kuida K., Zheng T. S., Na S., Kuan C., Yang D., Karasuyama H., Rakic P. and Flavell R. A. (1996) Decreased apoptosis

Proteomics-based network analysis characterizes biological processes and pathways activated by preconditioned mesenchymal stem cells in cardiac repair mechanisms.

PubMed

Di Silvestre, Dario; Brambilla, Francesca; Scardoni, Giovanni; Brunetti, Pietro; Motta, Sara; Matteucci, Marco; Laudanna, Carlo; Recchia, Fabio A; Lionetti, Vincenzo; Mauri, Pierluigi

2017-05-01

We have demonstrated that intramyocardial delivery of human mesenchymal stem cells preconditioned with a hyaluronan mixed ester of butyric and retinoic acid (MSCp + ) is more effective in preventing the decay of regional myocardial contractility in a swine model of myocardial infarction (MI). However, the understanding of the role of MSCp + in proteomic remodeling of cardiac infarcted tissue is not complete. We therefore sought to perform a comprehensive analysis of the proteome of infarct remote (RZ) and border zone (BZ) of pigs treated with MSCp + or unconditioned stem cells. Heart tissues were analyzed by MudPIT and differentially expressed proteins were selected by a label-free approach based on spectral counting. Protein profiles were evaluated by using PPI networks and their topological analysis. The proteomic remodeling was largely prevented in MSCp + group. Extracellular proteins involved in fibrosis were down-regulated, while energetic pathways were globally up-regulated. Cardioprotectant pathways involved in the production of keto acid metabolites were also activated. Additionally, we found that new hub proteins support the cardioprotective phenotype characterizing the left ventricular BZ treated with MSCp + . In fact, the up-regulation of angiogenic proteins NCL and RAC1 can be explained by the increase of capillary density induced by MSCp + . Our results show that angiogenic pathways appear to be uniquely positioned to integrate signaling with energetic pathways involving cardiac repair. Our findings prompt the use of proteomics-based network analysis to optimize new approaches preventing the post-ischemic proteomic remodeling that may underlie the limited self-repair ability of adult heart. Copyright © 2017 Elsevier B.V. All rights reserved.

Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study

PubMed Central

Kistler, Andreas D.; Serra, Andreas L.; Siwy, Justyna; Poster, Diane; Krauer, Fabienne; Torres, Vicente E.; Mrug, Michal; Grantham, Jared J.; Bae, Kyongtae T.; Bost, James E.; Mullen, William; Wüthrich, Rudolf P.; Mischak, Harald; Chapman, Arlene B.

2013-01-01

Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD. PMID:23326375

Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data.

PubMed

Qeli, Ermir; Omasits, Ulrich; Goetze, Sandra; Stekhoven, Daniel J; Frey, Juerg E; Basler, Konrad; Wollscheid, Bernd; Brunner, Erich; Ahrens, Christian H

2014-08-28

The in silico prediction of the best-observable "proteotypic" peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters in combination with positive and negative training sets to identify those peptide properties that most profoundly affect their general detectability. Here we present PeptideRank, an approach that uses learning to rank algorithm for peptide detectability prediction from shotgun proteomics data, and that eliminates the need to select a negative dataset for the training step. A large number of different peptide properties are used to train ranking models in order to predict a ranking of the best-observable peptides within a protein. Empirical evaluation with rank accuracy metrics showed that PeptideRank complements existing prediction algorithms. Our results indicate that the best performance is achieved when it is trained on organism-specific shotgun proteomics data, and that PeptideRank is most accurate for short to medium-sized and abundant proteins, without any loss in prediction accuracy for the important class of membrane proteins. Targeted proteomics approaches have been gaining a lot of momentum and hold immense potential for systems biology studies and clinical proteomics. However, since only very few complete proteomes have been reported to date, for a considerable fraction of a proteome there is no experimental proteomics evidence that would allow to guide the selection of the best-suited proteotypic peptides (PTPs), i.e. peptides that are specific to a given proteoform and that are repeatedly observed in a mass spectrometer. We describe a novel, rank-based approach for the prediction of the best-suited PTPs for targeted proteomics applications. By building on methods developed in the field of information retrieval (e.g. web search engines like Google's PageRank), we circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the experimentalist´s need for selecting e.g. the 5 most promising peptides for targeting a protein of interest. This approach allows to predict PTPs for not yet observed proteins or for organisms without prior experimental proteomics data such as many non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Five years later: the current status of the use of proteomics and transcriptomics in EMF research.

PubMed

Leszczynski, Dariusz; de Pomerai, David; Koczan, Dirk; Stoll, Dieter; Franke, Helmut; Albar, Juan Pablo

2012-08-01

The World Health Organization's and Radiation and Nuclear Safety Authority's "Workshop on Application of Proteomics and Transcriptomics in Electromagnetic Fields Research" was held in Helsinki in the October/November 2005. As a consequence of this meeting, Proteomics journal published in 2006 a special issue "Application of Proteomics and Transcriptomics in EMF Research" (Vol. 6 No. 17; Guest Editor: D. Leszczynski). This Proteomics issue presented the status of research, of the effects of electromagnetic fields (EMF) using proteomics and transcriptomics methods, present in 2005. The current overview/opinion article presents the status of research in this area by reviewing all studies that were published by the end of 2010. The review work was a part of the European Cooperation in the Field of Scientific and Technical Research (COST) Action BM0704 that created a structure in which researchers in the field of EMF and health shared knowledge and information. The review was prepared by the members of the COST Action BM0704 task group on the high-throughput screening techniques and electromagnetic fields (TG-HTST-EMF). © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Emerging proteomics biomarkers and prostate cancer burden in Africa

PubMed Central

Adeola, Henry A.; Blackburn, Jonathan M.; Rebbeck, Timothy R.; Zerbini, Luiz F.

2017-01-01

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers. PMID:28388542

Emerging proteomics biomarkers and prostate cancer burden in Africa.

PubMed

Adeola, Henry A; Blackburn, Jonathan M; Rebbeck, Timothy R; Zerbini, Luiz F

2017-06-06

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

PubMed

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-06-23

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from genome sequences, though there are over lapped proteins. Based on the demonstrated application of data stored in the database for functional analyses, it is suggested that these data will be useful for analyses of biological mechanisms in soybean. Furthermore, coupled with recent advances in information and communication technology, the usefulness of this database would increase in the analyses of biological mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Reproducibility of combinatorial peptide ligand libraries for proteome capture evaluated by selected reaction monitoring.

PubMed

Di Girolamo, Francesco; Righetti, Pier Giorgio; Soste, Martin; Feng, Yuehan; Picotti, Paola

2013-08-26

Systems biology studies require the capability to quantify with high precision proteins spanning a broad range of abundances across multiple samples. However, the broad range of protein expression in cells often precludes the detection of low-abundance proteins. Different sample processing techniques can be applied to increase proteome coverage. Among these, combinatorial (hexa)peptide ligand libraries (CPLLs) bound to solid matrices have been used to specifically capture and detect low-abundance proteins in complex samples. To assess whether CPLL capture can be applied in systems biology studies involving the precise quantitation of proteins across a multitude of samples, we evaluated its performance across the whole range of protein abundances in Saccharomyces cerevisiae. We used selected reaction monitoring assays for a set of target proteins covering a broad abundance range to quantitatively evaluate the precision of the approach and its capability to detect low-abundance proteins. Replicated CPLL-isolates showed an average variability of ~10% in the amount of the isolated proteins. The high reproducibility of the technique was not dependent on the abundance of the protein or the amount of beads used for the capture. However, the protein-to-bead ratio affected the enrichment of specific proteins. We did not observe a normalization effect of CPLL beads on protein abundances. However, CPLLs enriched for and depleted specific sets of proteins and thus changed the abundances of proteins from a whole proteome extract. This allowed the identification of ~400 proteins otherwise undetected in an untreated sample, under the experimental conditions used. CPLL capture is thus a useful tool to increase protein identifications in proteomic experiments, but it should be coupled to the analysis of untreated samples, to maximize proteome coverage. Our data also confirms that CPLL capture is reproducible and can be confidently used in quantitative proteomic experiments. Combinatorial hexapeptide ligand libraries (CPLLs) bound to solid matrices have been proposed to specifically capture and detect low-abundance proteins in complex samples. To assess whether the CPLL capture can be confidently applied in systems biology studies involving the precise quantitation of proteins across a broad range of abundances and a multitude of samples, we evaluated its reproducibility and performance features. Using selected reaction monitoring assays for proteins covering the whole range of abundances we show that the technique is reproducible and compatible with quantitative proteomic studies. However, the protein-to-bead ratio affects the enrichment of specific proteins and CPLLs depleted specific sets of proteins from a whole proteome extract. Our results suggest that CPLL-based analyses should be coupled to the analysis of untreated samples, to maximize proteome coverage. Overall, our data confirms the applicability of CPLLs in systems biology research and guides the correct use of this technique. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterization of human plasma proteome dynamics using deuterium oxide.

PubMed

Wang, Ding; Liem, David A; Lau, Edward; Ng, Dominic C M; Bleakley, Brian J; Cadeiras, Martin; Deng, Mario C; Lam, Maggie P Y; Ping, Peipei

2014-08-01

High-throughput quantification of human protein turnover via in vivo administration of deuterium oxide ((2) H2 O) is a powerful new approach to examine potential disease mechanisms. Its immediate clinical translation is contingent upon characterizations of the safety and hemodynamic effects of in vivo administration of (2) H2 O to human subjects. We recruited ten healthy human subjects with a broad demographic variety to evaluate the safety, feasibility, efficacy, and reproducibility of (2) H2 O intake for studying protein dynamics. We designed a protocol where each subject orally consumed weight-adjusted doses of 70% (2) H2 O daily for 14 days to enrich body water and proteins with deuterium. Plasma proteome dynamics was measured using a high-resolution MS method we recently developed. This protocol was successfully applied in ten human subjects to characterize the endogenous turnover rates of 542 human plasma proteins, the largest such human dataset to-date. Throughout the study, we did not detect physiological effects or signs of discomfort from (2) H2 O consumption. Our investigation supports the utility of a (2) H2 O intake protocol that is safe, accessible, and effective for clinical investigations of large-scale human protein turnover dynamics. This workflow shows promising clinical translational value for examining plasma protein dynamics in human diseases. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of human plasma proteome dynamics using deuterium oxide

PubMed Central

Wang, Ding; Liem, David A; Lau, Edward; Ng, Dominic CM; Bleakley, Brian J; Cadeiras, Martin; Deng, Mario C; Lam, Maggie PY; Ping, Peipei

2016-01-01

Purpose High-throughput quantification of human protein turnover via in vivo administration of deuterium oxide (2H2O) is a powerful new approach to examine potential disease mechanisms. Its immediate clinical translation is contingent upon characterizations of the safety and hemodynamic effects of in vivo administration of 2H2O to human subjects. Experimental design We recruited 10 healthy human subjects with a broad demographic variety to evaluate the safety, feasibility, efficacy, and reproducibility of 2H2O intake for studying protein dynamics. We designed a protocol where each subject orally consumed weight-adjusted doses of 70% 2H2O daily for 14 days to enrich body water and proteins with deuterium. Plasma proteome dynamics was measured using a high-resolution MS method we recently developed. Results This protocol was successfully applied in 10 human subjects to characterize the endogenous turnover rates of 542 human plasma proteins, the largest such human dataset to-date. Throughout the study, we did not detect physiological effects or signs of discomfort from 2H2O consumption. Conclusions and clinical relevance Our investigation supports the utility of a 2H2O intake protocol that is safe, accessible, and effective for clinical investigations of large-scale human protein turnover dynamics. This workflow shows promising clinical translational value for examining plasma protein dynamics in human diseases. PMID:24946186

A large synthetic peptide and phosphopeptide reference library for mass spectrometry-based proteomics.

PubMed

Marx, Harald; Lemeer, Simone; Schliep, Jan Erik; Matheron, Lucrece; Mohammed, Shabaz; Cox, Jürgen; Mann, Matthias; Heck, Albert J R; Kuster, Bernhard

2013-06-01

We present a peptide library and data resource of >100,000 synthetic, unmodified peptides and their phosphorylated counterparts with known sequences and phosphorylation sites. Analysis of the library by mass spectrometry yielded a data set that we used to evaluate the merits of different search engines (Mascot and Andromeda) and fragmentation methods (beam-type collision-induced dissociation (HCD) and electron transfer dissociation (ETD)) for peptide identification. We also compared the sensitivities and accuracies of phosphorylation-site localization tools (Mascot Delta Score, PTM score and phosphoRS), and we characterized the chromatographic behavior of peptides in the library. We found that HCD identified more peptides and phosphopeptides than did ETD, that phosphopeptides generally eluted later from reversed-phase columns and were easier to identify than unmodified peptides and that current computational tools for proteomics can still be substantially improved. These peptides and spectra will facilitate the development, evaluation and improvement of experimental and computational proteomic strategies, such as separation techniques and the prediction of retention times and fragmentation patterns.

Quantitative proteomics-based analysis supports a significant role of GTG proteins in regulation of ABA response in Arabidopsis roots.

PubMed

Alvarez, Sophie; Roy Choudhury, Swarup; Hicks, Leslie M; Pandey, Sona

2013-03-01

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in Arabidopsis thaliana. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and gtg1gtg2 were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in Arabidopsis. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus gtg1gtg2 provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk.

Urinary proteomics in renal pathophysiology: Impact of proteinuria.

PubMed

Sancho-Martínez, Sandra M; Prieto-García, Laura; Blanco-Gozalo, Víctor; Fontecha-Barriuso, Miguel; López-Novoa, José M; López-Hernández, Francisco J

2015-06-01

Urinary differential proteomics is used to study renal pathophysiological mechanisms, find novel markers of biological processes and renal diseases, and stratify patients according to proteomic profiles. The proteomic procedure determines the pathophysiological meaning and clinical relevance of results. Urine samples for differential proteomic studies are usually normalized by protein content, regardless of its pathophysiological characteristics. In the field of nephrology, this approach translates into the comparison of a different fraction of the total daily urine output between proteinuric and nonproteinuric samples. Accordingly, alterations in the level of specific proteins found by this method reflect the relative presence of individual proteins in the urine; but they do not necessarily show alterations in their daily excretion, which is a key parameter for the understanding of the pathophysiological meaning of urinary components. For renal pathophysiology studies and clinical biomarker identification or determination, an alternative proteomic concept providing complementary information is based on sample normalization by daily urine output, which directly informs on changes in the daily excretion of individual proteins. This is clinically important because daily excretion (rather than absolute or relative concentration) is the only self-normalized way to evaluate the real meaning of urinary parameters, which is also independent of urine concentration. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.

PubMed

Di Silvestre, Dario; Bergamaschi, Andrea; Bellini, Edoardo; Mauri, PierLuigi

2018-06-03

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

PubMed

Findeisen, Peter; Neumaier, Michael

2009-01-01

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

Functional proteomic analysis revealed ground-base ion radiations cannot reflect biological effects of space radiations of rice

NASA Astrophysics Data System (ADS)

Wang, Wei; Sun, Yeqing; Zhao, Qian; Han, Lu

2016-07-01

Highly ionizing radiation (HZE) in space is considered as main factor causing biological effects. Radiobiological studies during space flights are unrepeatable due to the variable space radiation environment, ground-base ion radiations are usually performed to simulate of the space biological effect. Spaceflights present a low-dose rate (0.1˜~0.3mGy/day) radiation environment inside aerocrafts while ground-base ion radiations present a much higher dose rate (100˜~500mGy/min). Whether ground-base ion radiation can reflect effects of space radiation is worth of evaluation. In this research, we compared the functional proteomic profiles of rice plants between on-ground simulated HZE particle radiation and spaceflight treatments. Three independent ground-base seed ionizing radiation experiments with different cumulative doses (dose range: 2˜~20000mGy) and different liner energy transfer (LET) values (13.3˜~500keV/μμm) and two independent seed spaceflight experiments onboard Chinese 20th satellite and SZ-6 spacecraft were carried out. Alterations in the proteome were analyzed by two-dimensional difference gel electrophoresis (2-D DIGE) with MALDI-TOF/TOF mass spectrometry identifications. 45 and 59 proteins showed significant (p<0.05) and reproducible quantitative differences in ground-base ion radiation and spaceflight experiments respectively. The functions of ground-base radiation and spaceflight proteins were both involved in a wide range of biological processes. Gene Ontology enrichment analysis further revealed that ground-base radiation responsive proteins were mainly involved in removal of superoxide radicals, defense response to stimulus and photosynthesis, while spaceflight responsive proteins mainly participate in nucleoside metabolic process, protein folding and phosphorylation. The results implied that ground-base radiations cannot truly reflect effects of spaceflight radiations, ground-base radiation was a kind of indirect effect to rice causing oxidation and metabolism stresses, but space radiation was a kind of direct effect leading to macromolecule (DNA and protein) damage and signal pathway disorders. This functional proteomic analysis work might provide a new evaluation method for further on-ground simulated HZE radiation experiments.

In-depth evaluation of software tools for data-independent acquisition based label-free quantification.

PubMed

Kuharev, Jörg; Navarro, Pedro; Distler, Ute; Jahn, Olaf; Tenzer, Stefan

2015-09-01

Label-free quantification (LFQ) based on data-independent acquisition workflows currently experiences increasing popularity. Several software tools have been recently published or are commercially available. The present study focuses on the evaluation of three different software packages (Progenesis, synapter, and ISOQuant) supporting ion mobility enhanced data-independent acquisition data. In order to benchmark the LFQ performance of the different tools, we generated two hybrid proteome samples of defined quantitative composition containing tryptically digested proteomes of three different species (mouse, yeast, Escherichia coli). This model dataset simulates complex biological samples containing large numbers of both unregulated (background) proteins as well as up- and downregulated proteins with exactly known ratios between samples. We determined the number and dynamic range of quantifiable proteins and analyzed the influence of applied algorithms (retention time alignment, clustering, normalization, etc.) on quantification results. Analysis of technical reproducibility revealed median coefficients of variation of reported protein abundances below 5% for MS(E) data for Progenesis and ISOQuant. Regarding accuracy of LFQ, evaluation with synapter and ISOQuant yielded superior results compared to Progenesis. In addition, we discuss reporting formats and user friendliness of the software packages. The data generated in this study have been deposited to the ProteomeXchange Consortium with identifier PXD001240 (http://proteomecentral.proteomexchange.org/dataset/PXD001240). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteome changes in platelets after pathogen inactivation--an interlaboratory consensus.

PubMed

Prudent, Michel; D'Alessandro, Angelo; Cazenave, Jean-Pierre; Devine, Dana V; Gachet, Christian; Greinacher, Andreas; Lion, Niels; Schubert, Peter; Steil, Leif; Thiele, Thomas; Tissot, Jean-Daniel; Völker, Uwe; Zolla, Lello

2014-04-01

Pathogen inactivation (PI) of platelet concentrates (PCs) reduces the proliferation/replication of a large range of bacteria, viruses, and parasites as well as residual leucocytes. Pathogen-inactivated PCs were evaluated in various clinical trials showing their efficacy and safety. Today, there is some debate over the hemostatic activity of treated PCs as the overall survival of PI platelets seems to be somewhat reduced, and in vitro measurements have identified some alterations in platelet function. Although the specific lesions resulting from PI of PCs are still not fully understood, proteomic studies have revealed potential damages at the protein level. This review merges the key findings of the proteomic analyses of PCs treated by the Mirasol Pathogen Reduction Technology, the Intercept Blood System, and the Theraflex UV-C system, respectively, and discusses the potential impact on the biological functions of platelets. The complementarities of the applied proteomic approaches allow the coverage of a wide range of proteins and provide a comprehensive overview of PI-mediated protein damage. It emerges that there is a relatively weak impact of PI on the overall proteome of platelets. However, some data show that the different PI treatments lead to an acceleration of platelet storage lesions, which is in agreement with the current model of platelet storage lesion in pathogen-inactivated PCs. Overall, the impact of the PI treatment on the proteome appears to be different among the PI systems. Mirasol impacts adhesion and platelet shape change, whereas Intercept seems to impact proteins of intracellular platelet activation pathways. Theraflex influences platelet shape change and aggregation, but the data reported to date are limited. This information provides the basis to understand the impact of different PI on the molecular mechanisms of platelet function. Moreover, these data may serve as basis for future developments of PI technologies for PCs. Further studies should address the impact of both the PI and the storage duration on platelets in PCs because PI may enable the extension of the shelf life of PCs by reducing the bacterial contamination risk. Copyright © 2014 Elsevier Inc. All rights reserved.

Progress and challenges for abiotic stress proteomics of crop plants.

PubMed

Barkla, Bronwyn J; Vera-Estrella, Rosario; Pantoja, Omar

2013-06-01

Plants are continually challenged to recognize and respond to adverse changes in their environment to avoid detrimental effects on growth and development. Understanding the mechanisms that crop plants employ to resist and tolerate abiotic stress is of considerable interest for designing agriculture breeding strategies to ensure sustainable productivity. The application of proteomics technologies to advance our knowledge in crop plant abiotic stress tolerance has increased dramatically in the past few years as evidenced by the large amount of publications in this area. This is attributed to advances in various technology platforms associated with MS-based techniques as well as the accessibility of proteomics units to a wider plant research community. This review summarizes the work which has been reported for major crop plants and evaluates the findings in context of the approaches that are widely employed with the aim to encourage broadening the strategies used to increase coverage of the proteome. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

PubMed

de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

2017-12-01

An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Molecular responses of genetically modified maize to abiotic stresses as determined through proteomic and metabolomic analyses

PubMed Central

Benevenuto, Rafael Fonseca; Agapito-Tenfen, Sarah Zanon; Vilperte, Vinicius; Wikmark, Odd-Gunnar; van Rensburg, Peet Jansen; Nodari, Rubens Onofre

2017-01-01

Some genetically modified (GM) plants have transgenes that confer tolerance to abiotic stressors. Meanwhile, other transgenes may interact with abiotic stressors, causing pleiotropic effects that will affect the plant physiology. Thus, physiological alteration might have an impact on the product safety. However, routine risk assessment (RA) analyses do not evaluate the response of GM plants exposed to different environmental conditions. Therefore, we here present a proteome profile of herbicide-tolerant maize, including the levels of phytohormones and related compounds, compared to its near-isogenic non-GM variety under drought and herbicide stresses. Twenty differentially abundant proteins were detected between GM and non-GM hybrids under different water deficiency conditions and herbicide sprays. Pathway enrichment analysis showed that most of these proteins are assigned to energetic/carbohydrate metabolic processes. Among phytohormones and related compounds, different levels of ABA, CA, JA, MeJA and SA were detected in the maize varieties and stress conditions analysed. In pathway and proteome analyses, environment was found to be the major source of variation followed by the genetic transformation factor. Nonetheless, differences were detected in the levels of JA, MeJA and CA and in the abundance of 11 proteins when comparing the GM plant and its non-GM near-isogenic variety under the same environmental conditions. Thus, these findings do support molecular studies in GM plants Risk Assessment analyses. PMID:28245233

Impact of mesenchymal stem cells' secretome on glioblastoma pathophysiology.

PubMed

Vieira de Castro, Joana; Gomes, Eduardo D; Granja, Sara; Anjo, Sandra I; Baltazar, Fátima; Manadas, Bruno; Salgado, António J; Costa, Bruno M

2017-10-02

Glioblastoma (GBM) is a highly aggressive primary brain cancer, for which curative therapies are not available. An emerging therapeutic approach suggested to have potential to target malignant gliomas has been based on the use of multipotent mesenchymal stem cells (MSCs), either unmodified or engineered to deliver anticancer therapeutic agents, as these cells present an intrinsic capacity to migrate towards malignant tumors. Nevertheless, it is still controversial whether this innate tropism of MSCs towards the tumor area is associated with cancer promotion or suppression. Considering that one of the major mechanisms by which MSCs interact with and modulate tumor cells is via secreted factors, we studied how the secretome of MSCs modulates critical hallmark features of GBM cells. The effect of conditioned media (CM) from human umbilical cord perivascular cells (HUCPVCs, a MSC population present in the Wharton's jelly of the umbilical cord) on GBM cell viability, migration, proliferation and sensitivity to temozolomide treatment of U251 and SNB-19 GBM cells was evaluated. The in vivo chicken chorioallantoic membrane (CAM) assay was used to evaluate the effect of HUCPVCs CM on tumor growth and angiogenesis. The secretome of HUCPVCs was characterized by proteomic analyses. We found that both tested GBM cell lines exposed to HUCPVCs CM presented significantly higher cellular viability, proliferation and migration. In contrast, resistance of GBM cells to temozolomide chemotherapy was not significantly affected by HUCPVCs CM. In the in vivo CAM assay, CM from HUCPVCs promoted U251 and SNB-19 tumor cells growth. Proteomic analysis to characterize the secretome of HUCPVCs identified several proteins involved in promotion of cell survival, proliferation and migration, revealing novel putative molecular mediators for the effects observed in GBM cells exposed to HUCPVCs CM. These findings provide novel insights to better understand the interplay between GBM cells and MSCs, raising awareness to potential safety issues regarding the use of MSCs as stem-cell based therapies for GBM.

Computational clustering for viral reference proteomes

PubMed Central

Chen, Chuming; Huang, Hongzhan; Mazumder, Raja; Natale, Darren A.; McGarvey, Peter B.; Zhang, Jian; Polson, Shawn W.; Wang, Yuqi; Wu, Cathy H.

2016-01-01

Motivation: The enormous number of redundant sequenced genomes has hindered efforts to analyze and functionally annotate proteins. As the taxonomy of viruses is not uniformly defined, viral proteomes pose special challenges in this regard. Grouping viruses based on the similarity of their proteins at proteome scale can normalize against potential taxonomic nomenclature anomalies. Results: We present Viral Reference Proteomes (Viral RPs), which are computed from complete virus proteomes within UniProtKB. Viral RPs based on 95, 75, 55, 35 and 15% co-membership in proteome similarity based clusters are provided. Comparison of our computational Viral RPs with UniProt’s curator-selected Reference Proteomes indicates that the two sets are consistent and complementary. Furthermore, each Viral RP represents a cluster of virus proteomes that was consistent with virus or host taxonomy. We provide BLASTP search and FTP download of Viral RP protein sequences, and a browser to facilitate the visualization of Viral RPs. Availability and implementation: http://proteininformationresource.org/rps/viruses/ Contact: chenc@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153712

PROTEOMICS in aquaculture: applications and trends.

PubMed

Rodrigues, Pedro M; Silva, Tomé S; Dias, Jorge; Jessen, Flemming

2012-07-19

Over the last forty years global aquaculture presented a growth rate of 6.9% per annum with an amazing production of 52.5 million tonnes in 2008, and a contribution of 43% of aquatic animal food for human consumption. In order to meet the world's health requirements of fish protein, a continuous growth in production is still expected for decades to come. Aquaculture is, though, a very competitive market, and a global awareness regarding the use of scientific knowledge and emerging technologies to obtain a better farmed organism through a sustainable production has enhanced the importance of proteomics in seafood biology research. Proteomics, as a powerful comparative tool, has therefore been increasingly used over the last decade to address different questions in aquaculture, regarding welfare, nutrition, health, quality, and safety. In this paper we will give an overview of these biological questions and the role of proteomics in their investigation, outlining the advantages, disadvantages and future challenges. A brief description of the proteomics technical approaches will be presented. Special focus will be on the latest trends related to the aquaculture production of fish with defined nutritional, health or quality properties for functional foods and the integration of proteomics techniques in addressing this challenging issue. Copyright © 2012 Elsevier B.V. All rights reserved.

Integrated Proteomic Approaches for Understanding Toxicity of Environmental Chemicals

EPA Science Inventory

To apply quantitative proteomic analysis to the evaluation of toxicity of environmental chemicals, we have developed an integrated proteomic technology platform. This platform has been applied to the analysis of the toxic effects and pathways of many important environmental chemi...

Role of Proteomics in the Development of Personalized Medicine.

PubMed

Jain, Kewal K

2016-01-01

Advances in proteomic technologies have made import contribution to the development of personalized medicine by facilitating detection of protein biomarkers, proteomics-based molecular diagnostics, as well as protein biochips and pharmacoproteomics. Application of nanobiotechnology in proteomics, nanoproteomics, has further enhanced applications in personalized medicine. Proteomics-based molecular diagnostics will have an important role in the diagnosis of certain conditions and understanding the pathomechanism of disease. Proteomics will be a good bridge between diagnostics and therapeutics; the integration of these will be important for advancing personalized medicine. Use of proteomic biomarkers and combination of pharmacoproteomics with pharmacogenomics will enable stratification of clinical trials and improve monitoring of patients for development of personalized therapies. Proteomics is an important component of several interacting technologies used for development of personalized medicine, which is depicted graphically. Finally, cancer is a good example of applications of proteomic technologies for personalized management of cancer. © 2016 Elsevier Inc. All rights reserved.

Assay for Arf GTP-binding Proteins | NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute's Laboratory of Cellular and Molecular Biology is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize an antibody-based proteomics assay.

Saccharomyces boulardii probiotic-associated fungemia: questioning the safety of this preventive probiotic's use.

PubMed

Martin, Isabella W; Tonner, Rita; Trivedi, Julie; Miller, Heather; Lee, Richard; Liang, Xinglun; Rotello, Leo; Isenbergh, Elena; Anderson, Jennifer; Perl, Trish; Zhang, Sean X

2017-03-01

We report a case of fungemia in an immunocompetent patient after administration of probiotic containing Saccharomyces boulardii. We demonstrated the strain relatedness of the yeast from the probiotic capsule and the yeast causing fungal infection using genomic and proteomic typing methods. Our study questions the safety of this preventative biotherapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Proteomic analysis of a decellularized human vocal fold mucosa scaffold using 2D electrophoresis and high-resolution mass spectrometry.

PubMed

Welham, Nathan V; Chang, Zhen; Smith, Lloyd M; Frey, Brian L

2013-01-01

Natural biologic scaffolds for tissue engineering are commonly generated by decellularization of tissues and organs. Despite some preclinical and clinical success, in vivo scaffold remodeling and functional outcomes remain variable, presumably due to the influence of unidentified bioactive molecules on the scaffold-host interaction. Here, we used 2D electrophoresis and high-resolution mass spectrometry-based proteomic analyses to evaluate decellularization effectiveness and identify potentially bioactive protein remnants in a human vocal fold mucosa model. We noted proteome, phosphoproteome and O-glycoproteome depletion post-decellularization, and identified >200 unique protein species within the decellularized scaffold. Gene ontology-based enrichment analysis revealed a dominant set of functionally-related ontology terms associated with extracellular matrix assembly, organization, morphology and patterning, consistent with preservation of a tissue-specific niche for later cell seeding and infiltration. We further identified a subset of ontology terms associated with bioactive (some of which are antigenic) cellular proteins, despite histological and immunohistochemical data indicating complete decellularization. These findings demonstrate the value of mass spectrometry-based proteomics in identifying agents potentially responsible for variation in host response to engineered tissues derived from decellularized scaffolds. This work has implications for the manufacturing of biologic scaffolds from any tissue or organ, as well as for prediction and monitoring of the scaffold-host interaction in vivo. Copyright © 2012 Elsevier Ltd. All rights reserved.

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Estimation of the proteomic cancer co-expression sub networks by using association estimators.

PubMed

Erdoğan, Cihat; Kurt, Zeyneb; Diri, Banu

2017-01-01

In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators' performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists.

Estimation of the proteomic cancer co-expression sub networks by using association estimators

PubMed Central

Kurt, Zeyneb; Diri, Banu

2017-01-01

In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study. As the gold standard to measure the association estimators’ performance, a multi-layer data integration platform on gene-disease associations (DisGeNET) and the Molecular Signatures Database (MSigDB) was used. Fisher's exact test was used to evaluate the performance of the association estimators by comparing the created co-expression networks with the disease-associated pathways. It was observed that the MI based estimators provided more successful results than the Pearson and Spearman correlation approaches, which are used in the estimation of biological networks in the weighted correlation network analysis (WGCNA) package. In correlation-based methods, the best average success rate for five cancer types was 60%, while in MI-based methods the average success ratio was 71% for James-Stein Shrinkage (Shrink) and 64% for Schurmann-Grassberger (SG) association estimator, respectively. Moreover, the hub genes and the inferred sub networks are presented for the consideration of researchers and experimentalists. PMID:29145449

Characterization of proteomic and metabolomic responses to dietary factors and supplements.

PubMed

Astle, John; Ferguson, Jonathan T; German, J Bruce; Harrigan, George G; Kelleher, Neil L; Kodadek, Thomas; Parks, Bryan A; Roth, Michael J; Singletary, Keith W; Wenger, Craig D; Mahady, Gail B

2007-12-01

Over the past decade there has been a renewed interest in research and development of both dietary and nutritional supplements. Significant advancements have been made in the scientific assessment of the quality, safety, and efficacy of these products because of the strong interest in and financial support of these projects. As research in both fields continues to advance, opportunities to use new and innovative research technologies and methodologies, such as proteomics and metabolomics, are critical for the future progress of the science. The purpose of the symposium was to begin the process of communicating new innovative proteomic and metabolomic methodologies that may be applied by researchers in both the nutrition and the natural product communities. This symposium highlighted 2 proteomic approaches, protein fingerprinting in complex mixtures with peptoid microarrays and top-down mass spectrometry for annotation of gene products. Likewise, an overview of the methodologies used in metabolomic profiling of natural products was presented, and an illustration of an integrated metabolomics approach in nutrition research was highlighted.

Mass spectrometry based proteomics: existing capabilities and future directions

PubMed Central

Angel, Thomas E.; Aryal, Uma K.; Hengel, Shawna M.; Baker, Erin S.; Kelly, Ryan T.; Robinson, Errol W.; Smith, Richard D.

2012-01-01

Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics is increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health. PMID:22498958

Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability.

PubMed

Alvarez, Sophie; Roy Choudhury, Swarup; Pandey, Sona

2014-03-07

Wheat is one of the most highly cultivated cereals in the world. Like other cultivated crops, wheat production is significantly affected by abiotic stresses such as drought. Multiple wheat varieties suitable for different geographical regions of the world have been developed that are adapted to different environmental conditions; however, the molecular basis of such adaptations remains unknown in most cases. We have compared the quantitative proteomics profile of the roots of two different wheat varieties, Nesser (drought-tolerant) and Opata (drought-sensitive), in the absence and presence of abscisic acid (ABA, as a proxy for drought). A labeling LC-based quantitative proteomics approach using iTRAQ was applied to elucidate the changes in protein abundance levels. Quantitative differences in protein levels were analyzed for the evaluation of inherent differences between the two varieties as well as the overall and variety-specific effect of ABA on the root proteome. This study reveals the most elaborate ABA-responsive root proteome identified to date in wheat. A large number of proteins exhibited inherently different expression levels between Nesser and Opata. Additionally, significantly higher numbers of proteins were ABA-responsive in Nesser roots compared with Opata roots. Furthermore, several proteins showed variety-specific regulation by ABA, suggesting their role in drought adaptation.

Proteomic profiling of white muscle from freshwater catfish Rita rita.

PubMed

Mohanty, Bimal Prasanna; Mitra, Tandrima; Banerjee, Sudeshna; Bhattacharjee, Soma; Mahanty, Arabinda; Ganguly, Satabdi; Purohit, Gopal Krishna; Karunakaran, Dhanasekar; Mohanty, Sasmita

2015-06-01

Muscle tissues contribute 34-48 % of the total body mass in fish. Proteomic analysis enables better understanding of the skeletal muscle physiology and metabolism. A proteome map reflects the general fingerprinting of the fish species and has the potential to identify novel proteins which could serve as biomarkers for many aspects of aquaculture including fish physiology and growth, flesh quality, food safety and aquatic environmental monitoring. The freshwater catfish Rita rita of the family Bagridae inhabiting the tropical rivers and estuaries is an important food fish with high nutritive value and is also considered a species of choice in riverine pollution monitoring. Omics information that could enhance utility of this species in molecular research is meager. Therefore, in the present study, proteomic analysis of Rita rita muscle has been carried out and functional genomics data have been generated. A reference muscle proteome has been developed, and 23 protein spots, representing 18 proteins, have been identified by MALDI-TOF/TOF-MS and LC-MS/MS. Besides, transcript information on a battery of heat shock proteins (Hsps) has been generated. The functional genomics information generated could act as the baseline data for further molecular research on this species.

Evaluation of Proteomic Search Engines for the Analysis of Histone Modifications

PubMed Central

2015-01-01

Identification of histone post-translational modifications (PTMs) is challenging for proteomics search engines. Including many histone PTMs in one search increases the number of candidate peptides dramatically, leading to low search speed and fewer identified spectra. To evaluate database search engines on identifying histone PTMs, we present a method in which one kind of modification is searched each time, for example, unmodified, individually modified, and multimodified, each search result is filtered with false discovery rate less than 1%, and the identifications of multiple search engines are combined to obtain confident results. We apply this method for eight search engines on histone data sets. We find that two search engines, pFind and Mascot, identify most of the confident results at a reasonable speed, so we recommend using them to identify histone modifications. During the evaluation, we also find some important aspects for the analysis of histone modifications. Our evaluation of different search engines on identifying histone modifications will hopefully help those who are hoping to enter the histone proteomics field. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001118. PMID:25167464

Evaluation of proteomic search engines for the analysis of histone modifications.

PubMed

Yuan, Zuo-Fei; Lin, Shu; Molden, Rosalynn C; Garcia, Benjamin A

2014-10-03

Identification of histone post-translational modifications (PTMs) is challenging for proteomics search engines. Including many histone PTMs in one search increases the number of candidate peptides dramatically, leading to low search speed and fewer identified spectra. To evaluate database search engines on identifying histone PTMs, we present a method in which one kind of modification is searched each time, for example, unmodified, individually modified, and multimodified, each search result is filtered with false discovery rate less than 1%, and the identifications of multiple search engines are combined to obtain confident results. We apply this method for eight search engines on histone data sets. We find that two search engines, pFind and Mascot, identify most of the confident results at a reasonable speed, so we recommend using them to identify histone modifications. During the evaluation, we also find some important aspects for the analysis of histone modifications. Our evaluation of different search engines on identifying histone modifications will hopefully help those who are hoping to enter the histone proteomics field. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001118.

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

Liquid Chromatography-Mass Spectrometry-based Quantitative Proteomics

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

Xie, Fang; Liu, Tao; Qian, Weijun

2011-07-22

Liquid chromatography-mass spectrometry (LC-MS)-based quantitative proteomics has become increasingly applied for a broad range of biological applications due to growing capabilities for broad proteome coverage and good accuracy in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations, and highlight their potential applications.

Comparative study of label and label-free techniques using shotgun proteomics for relative protein quantification.

PubMed

Sjödin, Marcus O D; Wetterhall, Magnus; Kultima, Kim; Artemenko, Konstantin

2013-06-01

The analytical performance of three different strategies, iTRAQ (isobaric tag for relative and absolute quantification), dimethyl labeling (DML) and label free (LF) for relative protein quantification using shotgun proteomics have been evaluated. The methods have been explored using samples containing (i) Bovine proteins in known ratios and (ii) Bovine proteins in known ratios spiked into Escherichia coli. The latter case mimics the actual conditions in a typical biological sample with a few differentially expressed proteins and a bulk of proteins with unchanged ratios. Additionally, the evaluation was performed on both QStar and LTQ-FTICR mass spectrometers. LF LTQ-FTICR was found to have the highest proteome coverage while the highest accuracy based on the artificially regulated proteins was found for DML LTQ-FTICR (54%). A varying linearity (k: 0.55-1.16, r(2): 0.61-0.96) was shown for all methods within selected dynamic ranges. All methods were found to consistently underestimate Bovine protein ratios when matrix proteins were added. However, LF LTQ-FTICR was more tolerant toward a compression effect. A single peptide was demonstrated to be sufficient for a reliable quantification using iTRAQ. A ranking system utilizing several parameters important for quantitative proteomics demonstrated that the overall performance of the five different methods was; DML LTQ-FTICR>iTRAQ QStar>LF LTQ-FTICR>DML QStar>LF QStar. Copyright © 2013 Elsevier B.V. All rights reserved.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

PubMed

Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong

2015-01-01

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Probing the Proteome on Earth and Beyond

NASA Astrophysics Data System (ADS)

Ostrom, P.

2008-12-01

Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.

Salt stress-induced changes in antioxidative defense system and proteome profiles of salt-tolerant and sensitive Frankia strains.

PubMed

Srivastava, Amrita; Singh, Anumeha; Singh, Satya S; Mishra, Arun K

2017-04-16

An appreciation of comparative microbial survival is most easily done while evaluating their adaptive strategies during stress. In the present experiment, antioxidative and whole cell proteome variations based on spectrophotometric analysis and SDS-PAGE and 2-dimensional gel electrophoresis have been analysed among salt-tolerant and salt-sensitive Frankia strains. This is the first report of proteomic basis underlying salt tolerance in these newly isolated Frankia strains from Hippophae salicifolia D. Don. Salt-tolerant strain HsIi10 shows higher increment in the contents of superoxide dismutase, catalase and ascorbate peroxidase as compared to salt-sensitive strain HsIi8. Differential 2-DGE profile has revealed differential profiles for salt-tolerant and salt-sensitive strains. Proteomic confirmation of salt tolerance in the strains with inbuilt efficiency of thriving in nitrogen-deficient locales is a definite advantage for these microbes. This would be equally beneficial for improvement of soil nitrogen status. Efficient protein regulation in HsIi10 suggests further exploration for its potential use as biofertilizer in saline soils.

The need for agriculture phenotyping: "moving from genotype to phenotype".

PubMed

Boggess, Mark V; Lippolis, John D; Hurkman, William J; Fagerquist, Clifton K; Briggs, Steve P; Gomes, Aldrin V; Righetti, Pier Giorgio; Bala, Kumar

2013-11-20

Increase in the world population has called for the increased demand for agricultural productivity. Traditional methods to augment crop and animal production are facing exacerbating pressures in keeping up with population growth. This challenge has in turn led to the transformational change in the use of biotechnology tools to meet increased productivity for both plant and animal systems. Although many challenges exist, the use of proteomic techniques to understand agricultural problems is steadily increasing. This review discusses the impact of genomics, proteomics, metabolomics and phenotypes on plant, animal and bacterial systems to achieve global food security and safety and we highlight examples of intra and extra mural research work that is currently being done to increase agricultural productivity. This review focuses on the global demand for increased agricultural productivity arising from population growth and how we can address this challenge using biotechnology. With a population well above seven billion humans, in a very unbalanced nutritional state (20% overweight, 20% risking starvation) drastic measures have to be taken at the political, infrastructure and scientific levels. While we cannot influence politics, it is our duty as scientists to see what can be done to feed humanity. Hence we highlight the transformational change in the use of biotechnology tools over traditional methods to increase agricultural productivity (plant and animal). Specifically, this review deals at length on how a three-pronged attack, namely combined genomics, proteomics and metabolomics, can help to ensure global food security and safety. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human.

PubMed

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-04-13

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish.

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human

PubMed Central

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-01-01

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish. PMID:27071722

Find Pairs: The Module for Protein Quantification of the PeakQuant Software Suite

PubMed Central

Eisenacher, Martin; Kohl, Michael; Wiese, Sebastian; Hebeler, Romano; Meyer, Helmut E.

2012-01-01

Abstract Accurate quantification of proteins is one of the major tasks in current proteomics research. To address this issue, a wide range of stable isotope labeling techniques have been developed, allowing one to quantitatively study thousands of proteins by means of mass spectrometry. In this article, the FindPairs module of the PeakQuant software suite is detailed. It facilitates the automatic determination of protein abundance ratios based on the automated analysis of stable isotope-coded mass spectrometric data. Furthermore, it implements statistical methods to determine outliers due to biological as well as technical variance of proteome data obtained in replicate experiments. This provides an important means to evaluate the significance in obtained protein expression data. For demonstrating the high applicability of FindPairs, we focused on the quantitative analysis of proteome data acquired in 14N/15N labeling experiments. We further provide a comprehensive overview of the features of the FindPairs software, and compare these with existing quantification packages. The software presented here supports a wide range of proteomics applications, allowing one to quantitatively assess data derived from different stable isotope labeling approaches, such as 14N/15N labeling, SILAC, and iTRAQ. The software is publicly available at http://www.medizinisches-proteom-center.de/software and free for academic use. PMID:22909347

Shotgun proteomics of plant plasma membrane and microdomain proteins using nano-LC-MS/MS.

PubMed

Takahashi, Daisuke; Li, Bin; Nakayama, Takato; Kawamura, Yukio; Uemura, Matsuo

2014-01-01

Shotgun proteomics allows the comprehensive analysis of proteins extracted from plant cells, subcellular organelles, and membranes. Previously, two-dimensional gel electrophoresis-based proteomics was used for mass spectrometric analysis of plasma membrane proteins. In order to get comprehensive proteome profiles of the plasma membrane including highly hydrophobic proteins with a number of transmembrane domains, a mass spectrometry-based shotgun proteomics method using nano-LC-MS/MS for proteins from the plasma membrane proteins and plasma membrane microdomain fraction is described. The results obtained are easily applicable to label-free protein semiquantification.

A proteomic study to identify soya allergens--the human response to transgenic versus non-transgenic soya samples.

PubMed

Batista, Rita; Martins, Isabel; Jeno, Paul; Ricardo, Cândido Pinto; Oliveira, Maria Margarida

2007-01-01

In spite of being among the main foods responsible for allergic reactions worldwide, soybean (Glycine max)-derived products continue to be increasingly widespread in a variety of food products due to their well-documented health benefits. Soybean also continues to be one of the elected target crops for genetic modification. The aim of this study was to characterize the soya proteome and, specifically, IgE-reactive proteins as well as to compare the IgE response in soya-allergic individuals to genetically modified Roundup Ready soya versus its non-transgenic control. We performed two-dimensional gel electrophoresis of protein extracts from a 5% genetically modified Roundup Ready flour sample and its non-transgenic control followed by Western blotting with plasma from 5 soya-sensitive individuals. We used peptide tandem mass spectrometry to identify soya proteins (55 protein matches), specifically IgE-binding ones, and to evaluate differences between transgenic and non-transgenic samples. We identified 2 new potential soybean allergens--one is maturation associated and seems to be part of the late embryogenesis abundant proteins group and the other is a cysteine proteinase inhibitor. None of the individuals tested reacted differentially to the transgenic versus non-transgenic samples under study. Soybean endogenous allergen expression does not seem to be altered after genetic modification. Proteomics should be considered a powerful tool for functional characterization of plants and for food safety assessment. Copyright (c) 2007 S. Karger AG, Basel.

Differential Proteomic Analysis of Lactic Acid Bacteria-Escherichia coli O157:H7 Interaction and Its Contribution to Bioprotection Strategies in Meat.

PubMed

Orihuel, Alejandra; Terán, Lucrecia; Renaut, Jenny; Vignolo, Graciela M; De Almeida, André M; Saavedra, María L; Fadda, Silvina

2018-01-01

Human infection by Enterohemorrhagic Escherichia (E.) coli (EHEC) occurs through the ingestion of contaminated foods such as milk, vegetable products, water-based drinks, and particularly minced meats. Indeed EHEC is a pathogen that threatens public health and meat industry. The potential of different Lactic Acid Bacteria (LAB) strains to control EHEC in a meat-based medium was evaluated by using a simple and rapid method and by analyzing the growth kinetics of co-cultures (LAB-EHEC) in a meat-based medium. The activity of LAB toward EHEC in co-cultures showed variable inhibitory effect. Although, LAB were able to control EHEC, neither the produced acid nor bacteriocins were responsible of the inhibition. The bacteriocinogenic Enteroccus (Ent.) mundtii CRL35 presented one of the highest inhibition activities. A proteomic approach was used to evaluate bacterial interaction and antagonistic mechanisms between Ent. mundtii and EHEC. Physiological observations, such as growth kinetics, acidification ability and EHEC inhibitory potential were supported by the proteomic results, demonstrating significant differences in protein expression in LAB: (i) due to the presence of the pathogen and (ii) according to the growth phase analyzed. Most of the identified proteins belonged to carbohydrate/amino acid metabolism, energy production, transcription/translation, and cell division. These results contribute to the knowledge of competition strategies used by Ent. mundtii during its co-culture with EHEC setting new perspectives for the use of LAB to control this pathogen in meat.

The Challenge of Human Spermatozoa Proteome: A Systematic Review.

PubMed

Gilany, Kambiz; Minai-Tehrani, Arash; Amini, Mehdi; Agharezaee, Niloofar; Arjmand, Babak

2017-01-01

Currently, there are 20,197 human protein-coding genes in the most expertly curated database (UniProtKB/Swiss-Pro). Big efforts have been made by the international consortium, the Chromosome-Centric Human Proteome Project (C-HPP) and independent researchers, to map human proteome. In brief, anno 2017 the human proteome was outlined. The male factor contributes to 50% of infertility in couples. However, there are limited human spermatozoa proteomic studies. Firstly, the development of the mapping of the human spermatozoa was analyzed. The human spermatozoa have been used as a model for missing proteins. It has been shown that human spermatozoa are excellent sources for finding missing proteins. Y chromosome proteome mapping is led by Iran. However, it seems that it is extremely challenging to map the human spermatozoa Y chromosome proteins based on current mass spectrometry-based proteomics technology. Post-translation modifications (PTMs) of human spermatozoa proteome are the most unexplored area and currently the exact role of PTMs in male infertility is unknown. Additionally, the clinical human spermatozoa proteomic analysis, anno 2017 was done in this study.

EBprot: Statistical analysis of labeling-based quantitative proteomics data.

PubMed

Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon

2015-08-01

Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

Machine learning applications in proteomics research: how the past can boost the future.

PubMed

Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Ramon, Jan; Laukens, Kris; Valkenborg, Dirk; Barsnes, Harald; Martens, Lennart

2014-03-01

Machine learning is a subdiscipline within artificial intelligence that focuses on algorithms that allow computers to learn solving a (complex) problem from existing data. This ability can be used to generate a solution to a particularly intractable problem, given that enough data are available to train and subsequently evaluate an algorithm on. Since MS-based proteomics has no shortage of complex problems, and since publicly available data are becoming available in ever growing amounts, machine learning is fast becoming a very popular tool in the field. We here therefore present an overview of the different applications of machine learning in proteomics that together cover nearly the entire wet- and dry-lab workflow, and that address key bottlenecks in experiment planning and design, as well as in data processing and analysis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clinical potential of proteomics in the diagnosis of ovarian cancer.

PubMed

Ardekani, Ali M; Liotta, Lance A; Petricoin, Emanuel F

2002-07-01

The need for specific and sensitive markers of ovarian cancer is critical. Finding a sensitive and specific test for its detection has an important public health impact. Currently, there are no effective screening options available for patients with ovarian cancer. CA-125, the most widely used biomarker for ovarian cancer, does not have a high positive predictive value and it is only effective when used in combination with other diagnostic tests. However, pathologic changes taking place within the ovary may be reflected in biomarker patterns in the serum. Combination of mass spectra generated by new proteomic technologies, such as surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) and artificial-intelligence-based informatic algorithms, have been used to discover a small set of key protein values and discriminate normal from ovarian cancer patients. Serum proteomic pattern analysis might be applied ultimately in medical screening clinics, as a supplement to the diagnostic work-up and evaluation.

Building ProteomeTools based on a complete synthetic human proteome

PubMed Central

Zolg, Daniel P.; Wilhelm, Mathias; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Delanghe, Bernard; Bailey, Derek J.; Gessulat, Siegfried; Ehrlich, Hans-Christian; Weininger, Maximilian; Yu, Peng; Schlegl, Judith; Kramer, Karl; Schmidt, Tobias; Kusebauch, Ulrike; Deutsch, Eric W.; Aebersold, Ruedi; Moritz, Robert L.; Wenschuh, Holger; Moehring, Thomas; Aiche, Stephan; Huhmer, Andreas; Reimer, Ulf; Kuster, Bernhard

2018-01-01

The ProteomeTools project builds molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we report the generation and multimodal LC-MS/MS analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products and exemplify the utility of this data. The resource will be extended to >1 million peptides and all data will be shared with the community via ProteomicsDB and proteomeXchange. PMID:28135259

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

Comparative and network-based proteomic analysis of low dose ethanol- and lipopolysaccharide-induced macrophages.

PubMed

Kamal, Abu Hena M; Fessler, Michael B; Chowdhury, Saiful M

2018-01-01

Macrophages are specialized phagocytes that play an essential role in inflammation, immunity, and tissue repair. Profiling the global proteomic response of macrophages to microbial molecules such as bacterial lipopolysaccharide is key to understanding fundamental mechanisms of inflammatory disease. Ethanol is a widely abused substance that has complex effects on inflammation. Reports have indicated that ethanol can activate or inhibit the lipopolysaccharide receptor, Toll-like Receptor 4, in different settings, with important consequences for liver and neurologic inflammation, but the underlying mechanisms are poorly understood. To profile the sequential effect of low dose ethanol and lipopolysaccharide on macrophages, a gel-free proteomic technique was applied to RAW 264.7 macrophages. Five hundred four differentially expressed proteins were identified and quantified with high confidence using ≥ 5 peptide spectral matches. Among these, 319 proteins were shared across all treatment conditions, and 69 proteins were exclusively identified in ethanol-treated or lipopolysaccharide-stimulated cells. The interactive impact of ethanol and lipopolysaccharide on the macrophage proteome was evaluated using bioinformatics tools, enabling identification of differentially responsive proteins, protein interaction networks, disease- and function-based networks, canonical pathways, and upstream regulators. Five candidate protein coding genes (PGM2, ISYNA1, PARP1, and PSAP) were further validated by qRT-PCR that mostly related to glucose metabolism and fatty acid synthesis pathways. Taken together, this study describes for the first time at a systems level the interaction between ethanol and lipopolysaccharide in the proteomic programming of macrophages, and offers new mechanistic insights into the biology that may underlie the impact of ethanol on infectious and inflammatory disease in humans.

Mass spectrometry-based proteomics for translational research: a technical overview.

PubMed

Paulo, Joao A; Kadiyala, Vivek; Banks, Peter A; Steen, Hanno; Conwell, Darwin L

2012-03-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.

Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

PubMed Central

Paulo, Joao A.; Kadiyala, Vivek; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease. PMID:22461744

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2010-06-01

SELDI-TOF-MS. Additional proteomic profiling studies using NMR- and MS-based metabonomics have been completed, and LC/MS based protein profiling using...Flight mass spectrometry (SELDI-TOF-MS). Changes in proteomic profiles will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr...performed using NMR- and MS-based metabonomics at Miami University, in the laboratory of Dr. Michael Kennedy. Initial spectra and profiles obtained show

Integrating cell biology and proteomic approaches in plants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of representative studies combining proteomic and cell biology methods for various purposes. Integrating cell biology approaches with proteomic ones allow validation and better interpretation of proteomic data. Moreover, cell biology methods remarkably extend the knowledge provided by proteomic studies and might be fundamental for the functional complementation of proteomic data. This review article summarizes current literature linking proteomics with cell biology. Copyright © 2017 Elsevier B.V. All rights reserved.

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

PubMed

Bereman, Michael S

2015-03-01

With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Environmental proteomics: a paradigm shift in characterizing microbial activities at the molecular level.

PubMed

Keller, Martin; Hettich, Robert

2009-03-01

The increase in sequencing capacity led to a new wave of metagenomic projects, enabling and setting the prerequisite for the application of environmental proteomics technologies. This review describes the current status of environmental proteomics. It describes sample preparation as well as the two major technologies applied within this field: two-dimensional electrophoresis-based environmental proteomics and liquid chromatography-mass spectrometry-based environmental proteomics. It also highlights current publications and describes major scientific findings. The review closes with a discussion of critical improvements in the area of integrating experimental mass spectrometry technologies with bioinformatics as well as improved sample handling.

Transcriptome and proteomic analysis of mango (Mangifera indica Linn) fruits.

PubMed

Wu, Hong-xia; Jia, Hui-min; Ma, Xiao-wei; Wang, Song-biao; Yao, Quan-sheng; Xu, Wen-tian; Zhou, Yi-gang; Gao, Zhong-shan; Zhan, Ru-lin

2014-06-13

Here we used Illumina RNA-seq technology for transcriptome sequencing of a mixed fruit sample from 'Zill' mango (Mangifera indica Linn) fruit pericarp and pulp during the development and ripening stages. RNA-seq generated 68,419,722 sequence reads that were assembled into 54,207 transcripts with a mean length of 858bp, including 26,413 clusters and 27,794 singletons. A total of 42,515(78.43%) transcripts were annotated using public protein databases, with a cut-off E-value above 10(-5), of which 35,198 and 14,619 transcripts were assigned to gene ontology terms and clusters of orthologous groups respectively. Functional annotation against the Kyoto Encyclopedia of Genes and Genomes database identified 23,741(43.79%) transcripts which were mapped to 128 pathways. These pathways revealed many previously unknown transcripts. We also applied mass spectrometry-based transcriptome data to characterize the proteome of ripe fruit. LC-MS/MS analysis of the mango fruit proteome was using tandem mass spectrometry (MS/MS) in an LTQ Orbitrap Velos (Thermo) coupled online to the HPLC. This approach enabled the identification of 7536 peptides that matched 2754 proteins. Our study provides a comprehensive sequence for a systemic view of transcriptome during mango fruit development and the most comprehensive fruit proteome to date, which are useful for further genomics research and proteomic studies. Our study provides a comprehensive sequence for a systemic view of both the transcriptome and proteome of mango fruit, and a valuable reference for further research on gene expression and protein identification. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

PubMed

Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

PubMed

Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

2016-11-04

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Combined comparative and chemical proteomics on the mechanisms of levo-tetrahydropalmatine-induced antinociception in the formalin test.

PubMed

Wang, Chen; Zhou, Jiangrui; Wang, Shuowen; Ye, Mingliang; Jiang, Chunlei; Fan, Guorong; Zou, Hanfa

2010-06-04

This study investigated the mechanisms involved in the antinociceptive action induced by levo-tetrahydropalmatine (l-THP) in the formalin test by combined comparative and chemical proteomics. Rats were pretreated with l-THP by the oral route (40 mg/kg) 1 h before formalin injection. The antinociceptive effect of l-THP was shown in the first and second phases of the formalin test. To address the mechanisms by which l-THP inhibits formalin-induced nociception in rats, the combined comparative and chemical proteomics were applied. A novel high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS was applied to simultaneously evaluate the deregulated proteins involved in the response of l-THP treatment in formalin-induced pain rats. Thousands of proteins were identified, among which 17 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (Neurabin-1 and Calcium-dependent secretion activator 1) were randomly selected, and their expression levels were further confirmed by Western Blots. The results matched well with those of proteomics. In the present study, we also described the development and application of l-THP immobilized beads to bind the targets. Following incubation with cellular lysates, the proteome interacting with the fixed l-THP was identified. The results of comparative and chemical proteomics were quite complementary. Although the precise roles of these identified moleculars in l-THP-induced antinociception need further study, the combined results indicated that proteins associated with signal transduction, vesicular trafficking and neurotransmitter release, energy metabolism, and ion transport play important roles in l-THP-induced antinociception in the formalin test.

Recent advances in mass spectrometry-based proteomics of gastric cancer.

PubMed

Kang, Changwon; Lee, Yejin; Lee, J Eugene

2016-10-07

The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

Exploring novel paths towards protein signatures of chronic pain.

PubMed

Gomez-Varela, David; Schmidt, Manuela

2016-01-01

Pain is a major symptom of many medical conditions and the worldwide number one reason for people to seek medical assistance. It affects the quality of life of patients and poses a heavy financial burden on society with high costs of treatment and lost productivity. Furthermore, the treatment of chronic pain presents a big challenge as pain therapeutics often lack efficacy and exhibit minimal safety profiles. The latter can be largely attributed to the fact that current therapies target molecules with key physiological functions throughout the body. In light of these difficulties, the identification of proteins specifically involved in chronic pain states is of paramount importance for designing selective interventions. Several profiling efforts have been employed with the aim to dissect the molecular underpinnings of chronic pain, both on the level of the transcriptome and proteome. However, generated results are often inconsistent and non-overlapping, which is largely due to inherent technical constraints. A potential solution may be offered by emerging strategies capable of performing standardized and reproducible proteome analysis, such as data-independent acquisition-mass spectrometry (DIA-MS). We have recently demonstrated the applicability of DIA-MS to interrogate chronic pain-related proteome alterations in mice. Based on our results, we aim to provide an overview on DIA-MS and its potential to contribute to the comprehensive characterization of molecular signatures underlying pain pathologies. © The Author(s) 2016.

The Functional Human C-Terminome

PubMed Central

Hedden, Michael; Lyon, Kenneth F.; Brooks, Steven B.; David, Roxanne P.; Limtong, Justin; Newsome, Jacklyn M.; Novakovic, Nemanja; Rajasekaran, Sanguthevar; Thapar, Vishal; Williams, Sean R.; Schiller, Martin R.

2016-01-01

All translated proteins end with a carboxylic acid commonly called the C-terminus. Many short functional sequences (minimotifs) are located on or immediately proximal to the C-terminus. However, information about the function of protein C-termini has not been consolidated into a single source. Here, we built a new “C-terminome” database and web system focused on human proteins. Approximately 3,600 C-termini in the human proteome have a minimotif with an established molecular function. To help evaluate the function of the remaining C-termini in the human proteome, we inferred minimotifs identified by experimentation in rodent cells, predicted minimotifs based upon consensus sequence matches, and predicted novel highly repetitive sequences in C-termini. Predictions can be ranked by enrichment scores or Gene Evolutionary Rate Profiling (GERP) scores, a measurement of evolutionary constraint. By searching for new anchored sequences on the last 10 amino acids of proteins in the human proteome with lengths between 3–10 residues and up to 5 degenerate positions in the consensus sequences, we have identified new consensus sequences that predict instances in the majority of human genes. All of this information is consolidated into a database that can be accessed through a C-terminome web system with search and browse functions for minimotifs and human proteins. A known consensus sequence-based predicted function is assigned to nearly half the proteins in the human proteome. Weblink: http://cterminome.bio-toolkit.com. PMID:27050421

Liquid Chromatography Mass Spectrometry-Based Proteomics: Biological and Technological Aspects

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

Karpievitch, Yuliya V.; Polpitiya, Ashoka D.; Anderson, Gordon A.

2010-12-01

Mass spectrometry-based proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. Though recent years have seen a tremendous improvement in instrument performance and the computational tools used, significant challenges remain, and there are many opportunities for statisticians to make important contributions. In the most widely used "bottom-up" approach to proteomics, complex mixtures of proteins are first subjected to enzymatic cleavage, the resulting peptide products are separated based on chemical or physical properties and analyzed using a mass spectrometer. The two fundamental challenges in the analysis of bottom-up MS-based proteomics are: (1) Identifying themore » proteins that are present in a sample, and (2) Quantifying the abundance levels of the identified proteins. Both of these challenges require knowledge of the biological and technological context that gives rise to observed data, as well as the application of sound statistical principles for estimation and inference. We present an overview of bottom-up proteomics and outline the key statistical issues that arise in protein identification and quantification.« less

[The application of metabonomics in modern studies of Chinese materia medica].

PubMed

Chen, Hai-Bin; Zhou, Hong-Guang; Yu, Xiao-Yi

2012-06-01

Metabonomics, a newly developing subject secondary to genomics, transcriptomics, and proteomics, is an important constituent part of systems biology. It is believed to be the final direction of the systems biology. It can be directly applied to understand the physiological and biochemical states by its "metabolome profile" as a whole. Therefore, it can provide a huge amount of information different from those originating from other "omics". In the modernization of Chinese materia medica research, the application of metabonomics methods and technologies has a broad potential for future development. Especially it is of important theoretical significance and application value in holistic efficacies evaluation, active ingredients studies, and safety research of Chinese materia medica.

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Mass spectrometry-based proteomic exploration of the human immune system: focus on the inflammasome, global protein secretion, and T cells.

PubMed

Nyman, Tuula A; Lorey, Martina B; Cypryk, Wojciech; Matikainen, Sampsa

2017-05-01

The immune system is our defense system against microbial infections and tissue injury, and understanding how it works in detail is essential for developing drugs for different diseases. Mass spectrometry-based proteomics can provide in-depth information on the molecular mechanisms involved in immune responses. Areas covered: Summarized are the key immunology findings obtained with MS-based proteomics in the past five years, with a focus on inflammasome activation, global protein secretion, mucosal immunology, immunopeptidome and T cells. Special focus is on extracellular vesicle-mediated protein secretion and its role in immune responses. Expert commentary: Proteomics is an essential part of modern omics-scale immunology research. To date, MS-based proteomics has been used in immunology to study protein expression levels, their subcellular localization, secretion, post-translational modifications, and interactions in immune cells upon activation by different stimuli. These studies have made major contributions to understanding the molecular mechanisms involved in innate and adaptive immune responses. New developments in proteomics offer constantly novel possibilities for exploring the immune system. Examples of these techniques include mass cytometry and different MS-based imaging approaches which can be widely used in immunology.

Proteomics in Heart Failure: Top-down or Bottom-up?

PubMed Central

Gregorich, Zachery R.; Chang, Ying-Hua; Ge, Ying

2014-01-01

Summary The pathophysiology of heart failure (HF) is diverse, owing to multiple etiologies and aberrations in a number of cellular processes. Therefore, it is essential to understand how defects in the molecular pathways that mediate cellular responses to internal and external stressors function as a system to drive the HF phenotype. Mass spectrometry (MS)-based proteomics strategies have great potential for advancing our understanding of disease mechanisms at the systems level because proteins are the effector molecules for all cell functions and, thus, are directly responsible for determining cell phenotype. Two MS-based proteomics strategies exist: peptide-based bottom-up and protein-based top-down proteomics—each with its own unique strengths and weaknesses for interrogating the proteome. In this review, we will discuss the advantages and disadvantages of bottom-up and top-down MS for protein identification, quantification, and the analysis of post-translational modifications, as well as highlight how both of these strategies have contributed to our understanding of the molecular and cellular mechanisms underlying HF. Additionally, the challenges associated with both proteomics approaches will be discussed and insights will be offered regarding the future of MS-based proteomics in HF research. PMID:24619480

SILAC-Based Quantitative Proteomic Analysis of Human Lung Cell Response to Copper Oxide Nanoparticles

PubMed Central

Edelmann, Mariola J.; Shack, Leslie A.; Naske, Caitlin D.; Walters, Keisha B.; Nanduri, Bindu

2014-01-01

Copper (II) oxide (CuO) nanoparticles (NP) are widely used in industry and medicine. In our study we evaluated the response of BEAS-2B human lung cells to CuO NP, using Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics and phosphoproteomics. Pathway modeling of the protein differential expression showed that CuO NP affect proteins relevant in cellular function and maintenance, protein synthesis, cell death and survival, cell cycle and cell morphology. Some of the signaling pathways represented by BEAS-2B proteins responsive to the NP included mTOR signaling, protein ubiquitination pathway, actin cytoskeleton signaling and epithelial adherens junction signaling. Follow-up experiments showed that CuO NP altered actin cytoskeleton, protein phosphorylation and protein ubiquitination level. PMID:25470785

Protein extraction and gel-based separation methods to analyze responses to pathogens in carnation (Dianthus caryophyllus L).

PubMed

Ardila, Harold Duban; Fernández, Raquel González; Higuera, Blanca Ligia; Redondo, Inmaculada; Martínez, Sixta Tulia

2014-01-01

We are currently using a 2-DE-based proteomics approach to study plant responses to pathogenic fungi by using the carnation (Dianthus caryophyllus L)-Fusarium oxysporum f. sp. dianthi pathosystem. It is clear that the protocols for the first stages of a standard proteomics workflow must be optimized to each biological system and objectives of the research. The optimization procedure for the extraction and separation of proteins by 1-DE and 2-DE in the indicated system is reported. This strategy can be extrapolated to other plant-pathogen interaction systems in order to perform an evaluation of the changes in the host protein profile caused by the pathogen and to identify proteins which, at early stages, are involved or implicated in the plant defense response.

Timing of transcriptomic and proteomic changes in the bovine placentome after parturition

USDA-ARS?s Scientific Manuscript database

Proper post-partum reproductive performance is important for reproductive efficiency in beef cows, and dystocia decreases post-partum fertility. Crossbred beef cows (n = 1676) were evaluated for lifetime performance based on degree of dystocia at presentation of the first calf. Cows that experience...

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes. PMID:23806018

NCI Launches Proteomics Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

In a paper recently published by the journal Nature Methods, Investigators from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (NCI-CPTAC) announced the launch of a proteomics Assay Portal for multiple reaction monitoring-mass spectrometry (MRM-MS) assays.  This community web-based repository for well-characterized quantitative proteomic assays currently consists of 456 unique peptide assays to 282 unique proteins and ser

Combination of Bottom-up 2D-LC-MS and Semi-top-down GelFree-LC-MS Enhances Coverage of Proteome and Low Molecular Weight Short Open Reading Frame Encoded Peptides of the Archaeon Methanosarcina mazei.

PubMed

Cassidy, Liam; Prasse, Daniela; Linke, Dennis; Schmitz, Ruth A; Tholey, Andreas

2016-10-07

The recent discovery of an increasing number of small open reading frames (sORF) creates the need for suitable analytical technologies for the comprehensive identification of the corresponding gene products. For biological and functional studies the knowledge of the entire set of proteins and sORF gene products is essential. Consequently in the present study we evaluated analytical approaches that will allow for simultaneous analysis of widest parts of the proteome together with the predicted sORF. We performed a full proteome analysis of the methane producing archaeon Methanosarcina mazei strain Gö1 cytosolic proteome using a high/low pH reversed phase LC-MS bottom-up approach. The second analytical approach was based on semi-top-down strategy, encompassing a separation at intact protein level using a GelFree system, followed by digestion and LC-MS analysis. A high overlap in identified proteins was found for both approaches yielding the most comprehensive coverage of the cytosolic proteome of this organism achieved so far. The application of the second approach in combination with an adjustment of the search criteria for database searches further led to a significant increase of sORF peptide identifications, finally allowing to detect and identify 28 sORF gene products.

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778

Proteomic profiling of eccrine sweat reveals its potential as a diagnostic biofluid for active tuberculosis.

PubMed

Adewole, Olanisun Olufemi; Erhabor, Greg Efosa; Adewole, Temitayo Oluwatoyin; Ojo, Abiodun Oluwasesan; Oshokoya, Harriet; Wolfe, Lisa M; Prenni, Jessica E

2016-05-01

Excessive sweating is a common symptom of the disease and an unexplored biofluid for TB diagnosis; we conducted a proof-of-concept study to identify potential diagnostic biomarkers of active TB in eccrine sweat. We performed a global proteomic profile of eccrine sweat sampled from patients with active pulmonary TB, other lung diseases (non-TB disease), and healthy controls. A comparison of proteomics between Active-TB, Non-TB, and Healthy Controls was done in search for potential biomarkers of active TB. Sweat specimens were pooled from 32 active TB patients, 27 patients with non-TB diseases, and 24 apparently healthy controls, all were negative for HIV. Over 100 unique proteins were identified in the eccrine sweat of all three groups. Twenty-six proteins were exclusively detected in the sweat of patients with active TB while the remaining detected proteins overlapped between three groups. Gene ontology evaluation indicated that the proteins detected uniquely in sweat of active TB patients were involved in immune response and auxiliary protein transport. Gene products for cellular components (e.g. ribosomes) were detected only in active TB patients. Data are available via ProteomeXchange with identifier PXD003224. Proteomics of sweat from active TB patients is a viable approach for biomarker identification, which could be used to develop a nonsputum-based test for detection of active TB. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

Informed-Proteomics: open-source software package for top-down proteomics

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

Park, Jungkap; Piehowski, Paul D.; Wilkins, Christopher

Top-down proteomics involves the analysis of intact proteins. This approach is very attractive as it allows for analyzing proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms, proteolytic processing or their combinations collectively called proteoforms. Moreover, the quality of the top-down LC-MS/MS datasets is rapidly increasing due to advances in the liquid chromatography and mass spectrometry instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compare to the more conventional bottom-up data. To take full advantage of the increasing quality of the top-down LC-MS/MS datasets there is an urgent needmore » to develop algorithms and software tools for confident proteoform identification and quantification. In this study we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.« less

An orthology-based analysis of pathogenic protozoa impacting global health: an improved comparative genomics approach with prokaryotes and model eukaryote orthologs.

PubMed

Cuadrat, Rafael R C; da Serra Cruz, Sérgio Manuel; Tschoeke, Diogo Antônio; Silva, Edno; Tosta, Frederico; Jucá, Henrique; Jardim, Rodrigo; Campos, Maria Luiza M; Mattoso, Marta; Dávila, Alberto M R

2014-08-01

A key focus in 21(st) century integrative biology and drug discovery for neglected tropical and other diseases has been the use of BLAST-based computational methods for identification of orthologous groups in pathogenic organisms to discern orthologs, with a view to evaluate similarities and differences among species, and thus allow the transfer of annotation from known/curated proteins to new/non-annotated ones. We used here a profile-based sensitive methodology to identify distant homologs, coupled to the NCBI's COG (Unicellular orthologs) and KOG (Eukaryote orthologs), permitting us to perform comparative genomics analyses on five protozoan genomes. OrthoSearch was used in five protozoan proteomes showing that 3901 and 7473 orthologs can be identified by comparison with COG and KOG proteomes, respectively. The core protozoa proteome inferred was 418 Protozoa-COG orthologous groups and 704 Protozoa-KOG orthologous groups: (i) 31.58% (132/418) belongs to the category J (translation, ribosomal structure, and biogenesis), and 9.81% (41/418) to the category O (post-translational modification, protein turnover, chaperones) using COG; (ii) 21.45% (151/704) belongs to the categories J, and 13.92% (98/704) to the O using KOG. The phylogenomic analysis showed four well-supported clades for Eukarya, discriminating Multicellular [(i) human, fly, plant and worm] and Unicellular [(ii) yeast, (iii) fungi, and (iv) protozoa] species. These encouraging results attest to the usefulness of the profile-based methodology for comparative genomics to accelerate semi-automatic re-annotation, especially of the protozoan proteomes. This approach may also lend itself for applications in global health, for example, in the case of novel drug target discovery against pathogenic organisms previously considered difficult to research with traditional drug discovery tools.

An Orthology-Based Analysis of Pathogenic Protozoa Impacting Global Health: An Improved Comparative Genomics Approach with Prokaryotes and Model Eukaryote Orthologs

PubMed Central

Cuadrat, Rafael R. C.; da Serra Cruz, Sérgio Manuel; Tschoeke, Diogo Antônio; Silva, Edno; Tosta, Frederico; Jucá, Henrique; Jardim, Rodrigo; Campos, Maria Luiza M.; Mattoso, Marta

2014-01-01

Abstract A key focus in 21st century integrative biology and drug discovery for neglected tropical and other diseases has been the use of BLAST-based computational methods for identification of orthologous groups in pathogenic organisms to discern orthologs, with a view to evaluate similarities and differences among species, and thus allow the transfer of annotation from known/curated proteins to new/non-annotated ones. We used here a profile-based sensitive methodology to identify distant homologs, coupled to the NCBI's COG (Unicellular orthologs) and KOG (Eukaryote orthologs), permitting us to perform comparative genomics analyses on five protozoan genomes. OrthoSearch was used in five protozoan proteomes showing that 3901 and 7473 orthologs can be identified by comparison with COG and KOG proteomes, respectively. The core protozoa proteome inferred was 418 Protozoa-COG orthologous groups and 704 Protozoa-KOG orthologous groups: (i) 31.58% (132/418) belongs to the category J (translation, ribosomal structure, and biogenesis), and 9.81% (41/418) to the category O (post-translational modification, protein turnover, chaperones) using COG; (ii) 21.45% (151/704) belongs to the categories J, and 13.92% (98/704) to the O using KOG. The phylogenomic analysis showed four well-supported clades for Eukarya, discriminating Multicellular [(i) human, fly, plant and worm] and Unicellular [(ii) yeast, (iii) fungi, and (iv) protozoa] species. These encouraging results attest to the usefulness of the profile-based methodology for comparative genomics to accelerate semi-automatic re-annotation, especially of the protozoan proteomes. This approach may also lend itself for applications in global health, for example, in the case of novel drug target discovery against pathogenic organisms previously considered difficult to research with traditional drug discovery tools. PMID:24960463

Comparative and network-based proteomic analysis of low dose ethanol- and lipopolysaccharide-induced macrophages

PubMed Central

Kamal, Abu Hena M.; Fessler, Michael B.

2018-01-01

Macrophages are specialized phagocytes that play an essential role in inflammation, immunity, and tissue repair. Profiling the global proteomic response of macrophages to microbial molecules such as bacterial lipopolysaccharide is key to understanding fundamental mechanisms of inflammatory disease. Ethanol is a widely abused substance that has complex effects on inflammation. Reports have indicated that ethanol can activate or inhibit the lipopolysaccharide receptor, Toll-like Receptor 4, in different settings, with important consequences for liver and neurologic inflammation, but the underlying mechanisms are poorly understood. To profile the sequential effect of low dose ethanol and lipopolysaccharide on macrophages, a gel-free proteomic technique was applied to RAW 264.7 macrophages. Five hundred four differentially expressed proteins were identified and quantified with high confidence using ≥ 5 peptide spectral matches. Among these, 319 proteins were shared across all treatment conditions, and 69 proteins were exclusively identified in ethanol-treated or lipopolysaccharide-stimulated cells. The interactive impact of ethanol and lipopolysaccharide on the macrophage proteome was evaluated using bioinformatics tools, enabling identification of differentially responsive proteins, protein interaction networks, disease- and function-based networks, canonical pathways, and upstream regulators. Five candidate protein coding genes (PGM2, ISYNA1, PARP1, and PSAP) were further validated by qRT-PCR that mostly related to glucose metabolism and fatty acid synthesis pathways. Taken together, this study describes for the first time at a systems level the interaction between ethanol and lipopolysaccharide in the proteomic programming of macrophages, and offers new mechanistic insights into the biology that may underlie the impact of ethanol on infectious and inflammatory disease in humans. PMID:29481576

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance*

PubMed Central

Paulovich, Amanda G.; Billheimer, Dean; Ham, Amy-Joan L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Tabb, David L.; Wang, Pei; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Clauser, Karl R.; Kinsinger, Christopher R.; Schilling, Birgit; Tegeler, Tony J.; Variyath, Asokan Mulayath; Wang, Mu; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fenyo, David; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Mesri, Mehdi; Neubert, Thomas A.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Stein, Stephen E.; Tempst, Paul; Liebler, Daniel C.

2010-01-01

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments. PMID:19858499

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Evaluation of three high abundance protein depletion kits for umbilical cord serum proteomics

PubMed Central

2011-01-01

Background High abundance protein depletion is a major challenge in the study of serum/plasma proteomics. Prior to this study, most commercially available kits for depletion of highly abundant proteins had only been tested and evaluated in adult serum/plasma, while the depletion efficiency on umbilical cord serum/plasma had not been clarified. Structural differences between some adult and fetal proteins (such as albumin) make it likely that depletion approaches for adult and umbilical cord serum/plasma will be variable. Therefore, the primary purposes of the present study are to investigate the efficiencies of several commonly-used commercial kits during high abundance protein depletion from umbilical cord serum and to determine which kit yields the most effective and reproducible results for further proteomics research on umbilical cord serum. Results The immunoaffinity based kits (PROTIA-Sigma and 5185-Agilent) displayed higher depletion efficiency than the immobilized dye based kit (PROTBA-Sigma) in umbilical cord serum samples. Both the PROTIA-Sigma and 5185-Agilent kit maintained high depletion efficiency when used three consecutive times. Depletion by the PROTIA-Sigma Kit improved 2DE gel quality by reducing smeared bands produced by the presence of high abundance proteins and increasing the intensity of other protein spots. During image analysis using the identical detection parameters, 411 ± 18 spots were detected in crude serum gels, while 757 ± 43 spots were detected in depleted serum gels. Eight spots unique to depleted serum gels were identified by MALDI- TOF/TOF MS, seven of which were low abundance proteins. Conclusions The immunoaffinity based kits exceeded the immobilized dye based kit in high abundance protein depletion of umbilical cord serum samples and dramatically improved 2DE gel quality for detection of trace biomarkers. PMID:21554704

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676

Virtual Labs in proteomics: new E-learning tools.

PubMed

Ray, Sandipan; Koshy, Nicole Rachel; Reddy, Panga Jaipal; Srivastava, Sanjeeva

2012-05-17

Web-based educational resources have gained enormous popularity recently and are increasingly becoming a part of modern educational systems. Virtual Labs are E-learning platforms where learners can gain the experience of practical experimentation without any direct physical involvement on real bench work. They use computerized simulations, models, videos, animations and other instructional technologies to create interactive content. Proteomics being one of the most rapidly growing fields of the biological sciences is now an important part of college and university curriculums. Consequently, many E-learning programs have started incorporating the theoretical and practical aspects of different proteomic techniques as an element of their course work in the form of Video Lectures and Virtual Labs. To this end, recently we have developed a Virtual Proteomics Lab at the Indian Institute of Technology Bombay, which demonstrates different proteomics techniques, including basic and advanced gel and MS-based protein separation and identification techniques, bioinformatics tools and molecular docking methods, and their applications in different biological samples. This Tutorial will discuss the prominent Virtual Labs featuring proteomics content, including the Virtual Proteomics Lab of IIT-Bombay, and E-resources available for proteomics study that are striving to make proteomic techniques and concepts available and accessible to the student and research community. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 14). Details can be found at: http://www.proteomicstutorials.org/. Copyright © 2012 Elsevier B.V. All rights reserved.

An overview of stress response proteomes in Listeria monocytogenes

USDA-ARS?s Scientific Manuscript database

Listeria monocytogenes adapts to diverse stress conditions including cold, osmotic, heat, acid, and alkali stresses encountered during food processing and preservation which is a serious food safety threat. In this review, we have presented the major findings on this bacterium’s stress response prot...

Development and application of automated systems for plasmid-based functional proteomics to improve syntheitc biology of engineered industrial microbes for high level expression of proteases for biofertilizer production

USDA-ARS?s Scientific Manuscript database

In addition to microarray technology, which provides a robust method to study protein function in a rapid, economical, and proteome-wide fashion, plasmid-based functional proteomics is an important technology for rapidly obtaining large quantities of protein and determining protein function across a...

Evaluation of Rice Resistance to Southern Rice Black-Streaked Dwarf Virus and Rice Ragged Stunt Virus through Combined Field Tests, Quantitative Real-Time PCR, and Proteome Analysis.

PubMed

Wang, Zhenchao; Yu, Lu; Jin, Linhong; Wang, Wenli; Zhao, Qi; Ran, Longlu; Li, Xiangyang; Chen, Zhuo; Guo, Rong; Wei, Yongtian; Yang, Zhongcheng; Liu, Enlong; Hu, Deyu; Song, Baoan

2017-02-22

Diseases caused by southern rice black-streaked dwarf virus (SRBSDV) and rice ragged stunt virus (RRSV) considerably decrease grain yield. Therefore, determining rice cultivars with high resistance to SRBSDV and RRSV is necessary. In this study, rice cultivars with high resistance to SRBSDV and RRSV were evaluated through field trials in Shidian and Mangshi county, Yunnan province, China. SYBR Green I-based quantitative real-time polymerase chain reaction (qRT-PCR) analysis was used to quantitatively detect virus gene expression levels in different rice varieties. The following parameters were applied to evaluate rice resistance: acre yield (A.Y.), incidence of infected plants (I.I.P.), virus load (V.L.), disease index (D.I.), and insect quantity (I.Q.) per 100 clusters. Zhongzheyou1 (Z1) and Liangyou2186 (L2186) were considered the most suitable varieties with integrated higher A.Y., lower I.I.P., V.L., D.I. and I.Q. In order to investigate the mechanism of rice resistance, comparative label-free shotgun liquid chromatography tandem-mass spectrometry (LC-MS/MS) proteomic approaches were applied to comprehensively describe the proteomics of rice varieties' SRBSDV tolerance. Systemic acquired resistance (SAR)-related proteins in Z1 and L2186 may result in the superior resistance of these varieties compared with Fengyouxiangzhan (FYXZ).

Placental Proteomics: A Shortcut to Biological Insight

PubMed Central

Robinson, John M.; Vandré, Dale D.; Ackerman, William E.

2012-01-01

Proteomics analysis of biological samples has the potential to identify novel protein expression patterns and/or changes in protein expression patterns in different developmental or disease states. An important component of successful proteomics research, at least in its present form, is to reduce the complexity of the sample if it is derived from cells or tissues. One method to simplify complex tissues is to focus on a specific, highly purified sub-proteome. Using this approach we have developed methods to prepare highly enriched fractions of the apical plasma membrane of the syncytiotrophoblast. Through proteomics analysis of this fraction we have identified over five hundred proteins several of which were previously not known to reside in the syncytiotrophoblast. Herein, we focus on two of these, dysferlin and myoferlin. These proteins, largely known from studies of skeletal muscle, may not have been found in the human placenta were it not for discovery-based proteomics analysis. This new knowledge, acquired through a discovery-driven approach, can now be applied for the generation of hypothesis-based experimentation. Thus discovery-based and hypothesis-based research are complimentary approaches that when coupled together can hasten scientific discoveries. PMID:19070895

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative mass spectrometry-based proteomic targeted assays. Targeted proteomic assays eliminate issues that are commonly observed using conventional protein detection systems.

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

Current advances in esophageal cancer proteomics.

PubMed

Uemura, Norihisa; Kondo, Tadashi

2015-06-01

We review the current status of proteomics for esophageal cancer (EC) from a clinician's viewpoint. The ultimate goal of cancer proteomics is the improvement of clinical outcome. The proteome as a functional translation of the genome is a straightforward representation of genomic mechanisms that trigger carcinogenesis. Cancer proteomics has identified the mechanisms of carcinogenesis and tumor progression, detected biomarker candidates for early diagnosis, and provided novel therapeutic targets for personalized treatments. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We discuss the major histological differences between EC types, i.e., esophageal squamous cell carcinoma and adenocarcinoma, and evaluate the clinical significance of published proteomics studies, including promising diagnostic biomarkers and novel therapeutic targets, which should be further validated prior to launching clinical trials. Multi-disciplinary collaborations between basic scientists, clinicians, and pathologists should be established for inter-institutional validation. In conclusion, EC proteomics has provided significant results, which after thorough validation, should lead to the development of novel clinical tools and improvement of the clinical outcome for esophageal cancer patients. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

Screening of entomopathogenic Metarhizium anisopliae isolates and proteomic analysis of secretion synthesized in response to cowpea weevil (Callosobruchus maculatus) exoskeleton.

PubMed

Murad, André M; Laumann, Raul A; Lima, Thaina de A; Sarmento, Rubia B C; Noronha, Eliane F; Rocha, Thales L; Valadares-Inglis, Maria C; Franco, Octávio L

2006-01-01

Cowpea crops are severely attacked by Callosobruchus maculatus, a Coleopteran that at the larval stage penetrates into stored seeds and feeds on cotyledons. Cowpea weevil control could be based in utilization of bacteria and fungi to reduce pest development. Entomopathogenic fungi, such as Metarhizium anisopliae, are able to control insect-pests and are widely applied in biological control. This report evaluated ten M. anisopliae isolates according to their virulence, correlating chitinolytic, proteolytic and alpha-amylolytic activities, as well proteomic analysis by two dimensional gels of fungal secretions in response to an induced medium containing C. maculatus shells, indicating novel biotechnological tools capable of improving cowpea crop resistance.

Targeted Proteomics Predicts a Sustained Complete-Response after Transarterial Chemoembolization and Clinical Outcomes in Patients with Hepatocellular Carcinoma: A Prospective Cohort Study.

PubMed

Yu, Su Jong; Kim, Hyunsoo; Min, Hophil; Sohn, Areum; Cho, Young Youn; Yoo, Jeong-Ju; Lee, Dong Hyeon; Cho, Eun Ju; Lee, Jeong-Hoon; Gim, Jungsoo; Park, Taesung; Kim, Yoon Jun; Kim, Chung Yong; Yoon, Jung-Hwan; Kim, Youngsoo

2017-03-03

This study was aimed to identify blood-based biomarkers to predict a sustained complete response (CR) after transarterial chemoembolization (TACE) using targeted proteomics. Consecutive patients with HCC who had undergone TACE were prospectively enrolled (training (n = 100) and validation set (n = 80)). Serum samples were obtained before and 6 months after TACE. Treatment responses were evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST). In the training set, the MRM-MS assay identified five marker candidate proteins (LRG1, APCS, BCHE, C7, and FCN3). When this five-marker panel was combined with the best-performing clinical variables (tumor number, baseline PIVKA, and baseline AFP), the resulting ensemble model had the highest area under the receiver operating curve (AUROC) value in predicting a sustained CR after TACE in the training and validation sets (0.881 and 0.813, respectively). Furthermore, the ensemble model was an independent predictor of rapid progression (hazard ratio (HR), 2.889; 95% confidence interval (CI), 1.612-5.178; P value < 0.001) and overall an unfavorable survival rate (HR, 1.985; 95% CI, 1.024-3.848; P value = 0.042) in the entire population by multivariate analysis. Targeted proteomics-based ensemble model can predict clinical outcomes after TACE. Therefore, this model can aid in determining the best candidates for TACE and the need for adjuvant therapy.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells.

PubMed

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001.

Deep coverage of the beer proteome.

PubMed

Grochalová, Martina; Konečná, Hana; Stejskal, Karel; Potěšil, David; Fridrichová, Danuše; Srbová, Eva; Ornerová, Kateřina; Zdráhal, Zbyněk

2017-06-06

We adopted an approach based on peptide immobilized pH gradient-isoelectric focusing (IPG-IEF) separation, coupled with LC-MS/MS, in order to maximize coverage of the beer proteome. A lager beer brewed using traditional Czech technology was degassed, desalted and digested. Tryptic peptides were separated by isoelectric focusing on an immobilized pH gradient strip and, after separation, the gel strip was divided into seven equally sized parts. Peptides extracted from gel fractions were analyzed by LC-MS/MS. This approach resulted in a three-fold increase in the number of proteins identified (over 1700) when compared to analysis of unfractionated beer processed by a filter-aided sample preparation (FASP). Over 1900 protein groups (PGs) in total were identified by both approaches. The study significantly extends knowledge about the beer proteome and demonstrates its complexity. Detailed knowledge of the protein content, especially gluten proteins, will enhance the evaluation of potential health risks related to beer consumption (coeliac disease) and will contribute to improving beer quality. Copyright © 2017 Elsevier B.V. All rights reserved.

A proteomic chronology of gene expression through the cell cycle in human myeloid leukemia cells

PubMed Central

Ly, Tony; Ahmad, Yasmeen; Shlien, Adam; Soroka, Dominique; Mills, Allie; Emanuele, Michael J; Stratton, Michael R; Lamond, Angus I

2014-01-01

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). DOI: http://dx.doi.org/10.7554/eLife.01630.001 PMID:24596151

Affordable proteomics: the two-hybrid systems.

PubMed

Gillespie, Marc

2003-06-01

Numerous proteomic methodologies exist, but most require a heavy investment in expertise and technology. This puts these approaches out of reach for many laboratories and small companies, rarely allowing proteomics to be used as a pilot approach for biomarker or target identification. Two proteomic approaches, 2D gel electrophoresis and the two-hybrid systems, are currently available to most researchers. The two-hybrid systems, though accommodating to large-scale experiments, were originally designed as practical screens, that by comparison to current proteomics tools were small-scale, affordable and technically feasible. The screens rapidly generated data, identifying protein interactions that were previously uncharacterized. The foundation for a two-hybrid proteomic investigation can be purchased as separate kits from a number of companies. The true power of the technique lies not in its affordability, but rather in its portability. The two-hybrid system puts proteomics back into laboratories where the output of the screens can be evaluated by researchers with experience in the particular fields of basic research, cancer biology, toxicology or drug development.

Efficient Site-Specific Labeling of Proteins via Cysteines

PubMed Central

Kim, Younggyu; Ho, Sam O.; Gassman, Natalie R.; Korlann, You; Landorf, Elizabeth V.; Collart, Frank R.; Weiss, Shimon

2011-01-01

Methods for chemical modifications of proteins have been crucial for the advancement of proteomics. In particular, site-specific covalent labeling of proteins with fluorophores and other moieties has permitted the development of a multitude of assays for proteome analysis. A common approach for such a modification is solvent-accessible cysteine labeling using thiol-reactive dyes. Cysteine is very attractive for site-specific conjugation due to its relative rarity throughout the proteome and the ease of its introduction into a specific site along the protein's amino acid chain. This is achieved by site-directed mutagenesis, most often without perturbing the protein's function. Bottlenecks in this reaction, however, include the maintenance of reactive thiol groups without oxidation before the reaction, and the effective removal of unreacted molecules prior to fluorescence studies. Here, we describe an efficient, specific, and rapid procedure for cysteine labeling starting from well-reduced proteins in the solid state. The efficacy and specificity of the improved procedure are estimated using a variety of single-cysteine proteins and thiol-reactive dyes. Based on UV/vis absorbance spectra, coupling efficiencies are typically in the range 70–90%, and specificities are better than ~95%. The labeled proteins are evaluated using fluorescence assays, proving that the covalent modification does not alter their function. In addition to maleimide-based conjugation, this improved procedure may be used for other thiol-reactive conjugations such as haloacetyl, alkyl halide, and disulfide interchange derivatives. This facile and rapid procedure is well suited for high throughput proteome analysis. PMID:18275130

Efficient site-specific labeling of proteins via cysteines.

PubMed

Kim, Younggyu; Ho, Sam O; Gassman, Natalie R; Korlann, You; Landorf, Elizabeth V; Collart, Frank R; Weiss, Shimon

2008-03-01

Methods for chemical modifications of proteins have been crucial for the advancement of proteomics. In particular, site-specific covalent labeling of proteins with fluorophores and other moieties has permitted the development of a multitude of assays for proteome analysis. A common approach for such a modification is solvent-accessible cysteine labeling using thiol-reactive dyes. Cysteine is very attractive for site-specific conjugation due to its relative rarity throughout the proteome and the ease of its introduction into a specific site along the protein's amino acid chain. This is achieved by site-directed mutagenesis, most often without perturbing the protein's function. Bottlenecks in this reaction, however, include the maintenance of reactive thiol groups without oxidation before the reaction, and the effective removal of unreacted molecules prior to fluorescence studies. Here, we describe an efficient, specific, and rapid procedure for cysteine labeling starting from well-reduced proteins in the solid state. The efficacy and specificity of the improved procedure are estimated using a variety of single-cysteine proteins and thiol-reactive dyes. Based on UV/vis absorbance spectra, coupling efficiencies are typically in the range 70-90%, and specificities are better than approximately 95%. The labeled proteins are evaluated using fluorescence assays, proving that the covalent modification does not alter their function. In addition to maleimide-based conjugation, this improved procedure may be used for other thiol-reactive conjugations such as haloacetyl, alkyl halide, and disulfide interchange derivatives. This facile and rapid procedure is well suited for high throughput proteome analysis.

Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

PubMed

Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

2015-08-01

We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

Quantitative proteomics analysis using 2D-PAGE to investigate the effects of cigarette smoke and aerosol of a prototypic modified risk tobacco product on the lung proteome in C57BL/6 mice.

PubMed

Elamin, Ashraf; Titz, Bjoern; Dijon, Sophie; Merg, Celine; Geertz, Marcel; Schneider, Thomas; Martin, Florian; Schlage, Walter K; Frentzel, Stefan; Talamo, Fabio; Phillips, Blaine; Veljkovic, Emilija; Ivanov, Nikolai V; Vanscheeuwijck, Patrick; Peitsch, Manuel C; Hoeng, Julia

2016-08-11

Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations. Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Application of metagenomics technologies for antimicrobial resistance and food safety research and beyond

USDA-ARS?s Scientific Manuscript database

Current developments in the field of metagenomics in biological sciences have demonstrated the need and potential usefulness of taxonomical and functional analyses of meta-omics data generated by genomics, transcriptomics, proteomics, and metabolomics. This review will provide a general overview of...

The online Tabloid Proteome: an annotated database of protein associations

PubMed Central

Turan, Demet; Tavernier, Jan

2018-01-01

Abstract A complete knowledge of the proteome can only be attained by determining the associations between proteins, along with the nature of these associations (e.g. physical contact in protein–protein interactions, participation in complex formation or different roles in the same pathway). Despite extensive efforts in elucidating direct protein interactions, our knowledge on the complete spectrum of protein associations remains limited. We therefore developed a new approach that detects protein associations from identifications obtained after re-processing of large-scale, public mass spectrometry-based proteomics data. Our approach infers protein association based on the co-occurrence of proteins across many different proteomics experiments, and provides information that is almost completely complementary to traditional direct protein interaction studies. We here present a web interface to query and explore the associations derived from this method, called the online Tabloid Proteome. The online Tabloid Proteome also integrates biological knowledge from several existing resources to annotate our derived protein associations. The online Tabloid Proteome is freely available through a user-friendly web interface, which provides intuitive navigation and data exploration options for the user at http://iomics.ugent.be/tabloidproteome. PMID:29040688

[Techniques for rapid production of monoclonal antibodies for use with antibody technology].

PubMed

Kamada, Haruhiko

2012-01-01

A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.

Screening Novel Molecular Targets of Metformin in Breast Cancer by Proteomic Approach

PubMed Central

Al-Zaidan, Lobna; El Ruz, Rasha Abu; Malki, Ahmed M.

2017-01-01

Metformin is a commonly prescribed antihyperglycemic drug, and has been investigated in vivo and in vitro for its effect to improve the comorbidity of diabetes and various types of cancers. Several studies investigated the therapeutic mechanisms of metformin on cancer cells, but the exact mechanism of metformin’s effect on the proteomic pathways of cancer cells is yet to be further investigated. The main objective of our research line is to discover safe and alternative therapeutic options for breast cancer, we aimed in this study to design a novel “bottom up proteomics workflow” in which proteins were first broken into peptides to reveal their identity, then the proteomes were precisely evaluated using spectrometry analysis. In our study, metformin suppressed cell proliferation and induced apoptosis in human breast carcinoma cell line MCF-7 with minimal toxicity to normal breast epithelial cells MCF-10. Metformin induced apoptosis by arresting cells in G1 phase as evaluated by flow cytometric analysis. Moreover, The G1 phase arrest for the MCF-7 has been confirmed by increased expression levels of p21 and reduction in cyclin D1 level. Additionally, metformin increased the expression levels of p53, Bax, Bad while it reduced expression levels of Akt, Bcl-2, and Mdm2. The study employed a serviceable strategy that investigates metformin-dependent changes in the proteome using a literature-derived network. The protein extracts of the treated and untreated cell lines were analyzed employing proteomic approaches; the findings conveyed a proposed mechanism of the effectual tactics of metformin on breast cancer cells. Metformin proposed an antibreast cancer effect through the examination of the proteomic pathways upon the MCF-7 and MCF-10A exposure to the drug. Our findings proposed prolific proteomic changes that revealed the therapeutic mechanisms of metformin on breast cancer cells upon their exposure. In conclusion, the reported proteomic pathways lead to increase the understanding of breast cancer prognosis and permit future studies to examine the effect of metformin on the proteomic pathways against other types of cancers. Finally, it suggests the possibility to develop further therapeutic generations of metformin with increased anticancer effect through targeting specific proteomes. PMID:29085821

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

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

Compositional and proteomic analyses of genetically modified broccoli (Brassica oleracea var. italica) harboring an agrobacterial gene.

PubMed

Liu, Mao-Sen; Ko, Miau-Hwa; Li, Hui-Chun; Tsai, Shwu-Jene; Lai, Ying-Mi; Chang, You-Ming; Wu, Min-Tze; Chen, Long-Fang O

2014-08-28

Previously, we showed improved shelf life for agrobacterial isopentenyltransferase (ipt) transgenic broccoli (Brassica oleracea var. italica), with yield comparable to commercial varieties, because of the protection mechanism offered by molecular chaperones and stress-related proteins. Here, we used proximate analysis to examine macronutrients, chemical and mineral constituents as well as anti-nutrient and protein changes of ipt-transgenic broccoli and corresponding controls. We also preliminarily assessed safety in mice. Most aspects were comparable between ipt-transgenic broccoli and controls, except for a significant increase in carbohydrate level and a decrease in magnesium content in ipt-transgenic lines 101, 102 and 103, as compared with non-transgenic controls. In addition, the anti-nutrient glucosinolate content was increased and crude fat content decreased in inbred control 104 and transgenic lines as compared with the parental control, "Green King". Gel-based proteomics detected more than 50 protein spots specifically found in ipt-transgenic broccoli at harvest and after cooking; one-third of these proteins showed homology to potential allergens that also play an important role in plant defense against stresses and senescence. Mice fed levels of ipt-transgenic broccoli mimicking the 120 g/day of broccoli eaten by a 60-kg human adult showed normal growth and immune function. In conclusion, the compositional and proteomic changes attributed to the transgenic ipt gene did not affect the growth and immune response of mice under the feeding regimes examined.

Compositional and Proteomic Analyses of Genetically Modified Broccoli (Brassica oleracea var. italica) Harboring an Agrobacterial Gene

PubMed Central

Liu, Mao-Sen; Ko, Miau-Hwa; Li, Hui-Chun; Tsai, Shwu-Jene; Lai, Ying-Mi; Chang, You-Ming; Wu, Min-Tze; Chen, Long-Fang O.

2014-01-01

Previously, we showed improved shelf life for agrobacterial isopentenyltransferase (ipt) transgenic broccoli (Brassica oleracea var. italica), with yield comparable to commercial varieties, because of the protection mechanism offered by molecular chaperones and stress-related proteins. Here, we used proximate analysis to examine macronutrients, chemical and mineral constituents as well as anti-nutrient and protein changes of ipt-transgenic broccoli and corresponding controls. We also preliminarily assessed safety in mice. Most aspects were comparable between ipt-transgenic broccoli and controls, except for a significant increase in carbohydrate level and a decrease in magnesium content in ipt-transgenic lines 101, 102 and 103, as compared with non-transgenic controls. In addition, the anti-nutrient glucosinolate content was increased and crude fat content decreased in inbred control 104 and transgenic lines as compared with the parental control, “Green King”. Gel-based proteomics detected more than 50 protein spots specifically found in ipt-transgenic broccoli at harvest and after cooking; one-third of these proteins showed homology to potential allergens that also play an important role in plant defense against stresses and senescence. Mice fed levels of ipt-transgenic broccoli mimicking the 120 g/day of broccoli eaten by a 60-kg human adult showed normal growth and immune function. In conclusion, the compositional and proteomic changes attributed to the transgenic ipt gene did not affect the growth and immune response of mice under the feeding regimes examined. PMID:25170807

Synthesis and Evaluation of a Novel Adenosine-Ribose Probe for Global-Scale Profiling of Nucleoside and Nucleotide-Binding Proteins

PubMed Central

Mahajan, Shikha; Manetsch, Roman; Merkler, David J.; Stevens Jr., Stanley M.

2015-01-01

Proteomics is a powerful approach used for investigating the complex molecular mechanisms of disease pathogenesis and progression. An important challenge in modern protein profiling approaches involves targeting of specific protein activities in order to identify altered molecular processes associated with disease pathophysiology. Adenosine-binding proteins represent an important subset of the proteome where aberrant expression or activity changes of these proteins have been implicated in numerous human diseases. Herein, we describe an affinity-based approach for the enrichment of adenosine-binding proteins from a complex cell proteome. A novel N 6-biotinylated-8-azido-adenosine probe (AdoR probe) was synthesized, which contains a reactive group that forms a covalent bond with the target proteins, as well as a biotin tag for affinity enrichment using avidin chromatography. Probe specificity was confirmed with protein standards prior to further evaluation in a complex protein mixture consisting of a lysate derived from mouse neuroblastoma N18TG2 cells. Protein identification and relative quantitation using mass spectrometry allowed for the identification of small variations in abundance of nucleoside- and nucleotide-binding proteins in these samples where a significant enrichment of AdoR-binding proteins in the labeled proteome from the neuroblastoma cells was observed. The results from this study demonstrate the utility of this method to enrich for nucleoside- and nucleotide-binding proteins in a complex protein mixture, pointing towards a unique set of proteins that can be examined in the context of further understanding mechanisms of disease, or fundamental biological processes in general. PMID:25671571

Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification.

PubMed

Chebouba, Lokmane; Boughaci, Dalila; Guziolowski, Carito

2018-06-04

The use of data issued from high throughput technologies in drug target problems is widely widespread during the last decades. This study proposes a meta-heuristic framework using stochastic local search (SLS) combined with random forest (RF) where the aim is to specify the most important genes and proteins leading to the best classification of Acute Myeloid Leukemia (AML) patients. First we use a stochastic local search meta-heuristic as a feature selection technique to select the most significant proteins to be used in the classification task step. Then we apply RF to classify new patients into their corresponding classes. The evaluation technique is to run the RF classifier on the training data to get a model. Then, we apply this model on the test data to find the appropriate class. We use as metrics the balanced accuracy (BAC) and the area under the receiver operating characteristic curve (AUROC) to measure the performance of our model. The proposed method is evaluated on the dataset issued from DREAM 9 challenge. The comparison is done with a pure random forest (without feature selection), and with the two best ranked results of the DREAM 9 challenge. We used three types of data: only clinical data, only proteomics data, and finally clinical and proteomics data combined. The numerical results show that the highest scores are obtained when using clinical data alone, and the lowest is obtained when using proteomics data alone. Further, our method succeeds in finding promising results compared to the methods presented in the DREAM challenge.

We Are Not Alone: The iMOP Initiative and Its Roles in a Biology- and Disease-Driven Human Proteome Project.

PubMed

Tholey, Andreas; Taylor, Nicolas L; Heazlewood, Joshua L; Bendixen, Emøke

2017-12-01

Mapping of the human proteome has advanced significantly in recent years and will provide a knowledge base to accelerate our understanding of how proteins and protein networks can affect human health and disease. However, providing solutions to human health challenges will likely fail if insights are exclusively based on studies of human samples and human proteomes. In recent years, it has become evident that human health depends on an integrated understanding of the many species that make human life possible. These include the commensal microorganisms that are essential to human life, pathogens, and food species as well as the classic model organisms that enable studies of biological mechanisms. The Human Proteome Organization (HUPO) initiative on multiorganism proteomes (iMOP) works to support proteome research undertaken on nonhuman species that remain widely under-studied compared with the progress in human proteome research. This perspective argues the need for further research on multiple species that impact human life. We also present an update on recent progress in model organisms, microbiota, and food species, address the emerging problem of antibiotics resistance, and outline how iMOP activities could lead to a more inclusive approach for the human proteome project (HPP) to better support proteome research aimed at improving human health and furthering knowledge on human biology.

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics.

PubMed

Timms, John F; Hale, Oliver J; Cramer, Rainer

2016-06-01

The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry (MS). Studies using advanced MS have resulted in new insights into cell biology and the etiology of diseases as well as its use in clinical applications. This review discusses recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It also discusses the issues around translating the research findings to the clinic and provides an outline of where the field is moving. Expert commentary: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

Coatomer subunit beta 2 (COPB2), identified by label-free quantitative proteomics, regulates cell proliferation and apoptosis in human prostate carcinoma cells.

PubMed

Mi, Yuanyuan; Sun, Chuanyu; Wei, Bingbing; Sun, Feiyu; Guo, Yijun; Hu, Qingfeng; Ding, Weihong; Zhu, Lijie; Xia, Guowei

2018-01-01

Label-free quantitative proteomics has broad applications in the identification of differentially expressed proteins. Here, we applied this method to identify differentially expressed proteins (such as coatomer subunit beta 2 [COPB2]) and evaluated the functions and molecular mechanisms of these proteins in prostate cancer (PCA) cell proliferation. Proteins extracted from surgically resected PCA tissues and adjacent tissues of 3 patients were analyzed by label-free quantitative proteomics. The target protein was confirmed by bioinformatics and GEO dataset analyses. To investigate the role of the target protein in PCA, we used lentivirus-mediated small-interfering RNA (siRNA) to knockdown protein expression in the prostate carcinoma cell line, CWR22RV1 cells and assessed gene and protein expression by reverse transcription quantitative polymerase chain reaction and western blotting. CCK8 and colony formation assays were conducted to evaluate cell proliferation. Cell cycle distributions and apoptosis were assayed by flow cytometry. We selected the differentiation-related protein COPB2 as our target protein based on the results of label-free quantitative proteomics. High expression of COPB2 was found in PCA tissue and was related to poor overall survival based on a public dataset. Cell proliferation was significantly inhibited in COPB2-knockdown CWR22RV1 cells, as demonstrated by CCK8 and colony formation assays. Additionally, the apoptosis rate and percentage of cells in the G 1 phase were increased in COPB2-knockdown cells compared with those in control cells. CDK2, CDK4, and cyclin D1 were downregulated, whereas p21 Waf1/Cip1 and p27 Kip1 were upregulated, affecting the cell cycle signaling pathway. COPB2 significantly promoted CWR22RV1 cell proliferation through the cell cycle signaling pathway. Thus, silencing of COPB2 may have therapeutic applications in PCA. Copyright © 2017 Elsevier Inc. All rights reserved.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Proteomics in India: A Report on a Brainstorming Meeting at Hyderabad, India

PubMed Central

Chatterjee, Bhaswati; Makarov, Alexander; Clemmer, David E.; Steen, Hanno; Steen, Judith; Saffell-Clemmer, Wendy; Moghekar, Abhay R.; Mohan Rao, Chintalagiri; Bradshaw, Ralph A.; Thakur, Suman S.

2016-01-01

The Centre for Cellular and Molecular Biology, Hyderabad, India, was host for an international forum, or “brainstorming meeting,” on proteomics held in November 2014, which provided the opportunity to showcase proteomic science in India and to allow discussions between Indian scientists and students and several international visitors. This provided an amalgamation of speakers and participants whose interests lay mainly in developing and using mass-spectrometry-based proteomics to advance their research work. A week-long workshop with hands-on training in proteomic methodology followed the meeting. PMID:27114450

The state of proteome profiling in the fungal genus Aspergillus.

PubMed

Kim, Yonghyun; Nandakumar, M P; Marten, Mark R

2008-03-01

Aspergilli are an important genus of filamentous fungi that contribute to a multibillion dollar industry. Since many fungal genome sequencing were recently completed, it would be advantageous to profile their proteome to better understand the fungal cell factory. Here, we review proteomic data generated for the Aspergilli in recent years. Thus far, a combined total of 28 cell surface, 102 secreted and 139 intracellular proteins have been identified based on 10 different studies on Aspergillus proteomics. A summary proteome map highlighting identified proteins in major metabolic pathway is presented.

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

PubMed

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

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

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.

2016-05-03

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of thismore » protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical). IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.« less

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

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

Li, Zhou; Adams, Rachel M; Chourey, Karuna

2012-01-01

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification. Isobaricmore » chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. Based on the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.« less

Methodologies and Perspectives of Proteomics Applied to Filamentous Fungi: From Sample Preparation to Secretome Analysis

PubMed Central

Bianco, Linda; Perrotta, Gaetano

2015-01-01

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation. PMID:25775160

Methodologies and perspectives of proteomics applied to filamentous fungi: from sample preparation to secretome analysis.

PubMed

Bianco, Linda; Perrotta, Gaetano

2015-03-12

Filamentous fungi possess the extraordinary ability to digest complex biomasses and mineralize numerous xenobiotics, as consequence of their aptitude to sensing the environment and regulating their intra and extra cellular proteins, producing drastic changes in proteome and secretome composition. Recent advancement in proteomic technologies offers an exciting opportunity to reveal the fluctuations of fungal proteins and enzymes, responsible for their metabolic adaptation to a large variety of environmental conditions. Here, an overview of the most commonly used proteomic strategies will be provided; this paper will range from sample preparation to gel-free and gel-based proteomics, discussing pros and cons of each mentioned state-of-the-art technique. The main focus will be kept on filamentous fungi. Due to the biotechnological relevance of lignocellulose degrading fungi, special attention will be finally given to their extracellular proteome, or secretome. Secreted proteins and enzymes will be discussed in relation to their involvement in bio-based processes, such as biomass deconstruction and mycoremediation.

First systematic plant proteomics workshop in Botany Department, University of Delhi: transferring proteomics knowledge to next-generation researchers and students.

PubMed

Deswal, Renu; Abat, Jasmeet Kaur; Sehrawat, Ankita; Gupta, Ravi; Kashyap, Prakriti; Sharma, Shruti; Sharma, Bhavana; Chaurasia, Satya Prakash; Chanu, Sougrakpam Yaiphabi; Masi, Antonio; Agrawal, Ganesh Kumar; Sarkar, Abhijit; Agrawal, Raj; Dunn, Michael J; Renaut, Jenny; Rakwal, Randeep

2014-07-01

International Plant Proteomics Organization (INPPO) outlined ten initiatives to promote plant proteomics in each and every country. With greater emphasis in developing countries, one of those was to "organize workshops at national and international levels to train manpower and exchange information". This third INPPO highlights covers the workshop organized for the very first time in a developing country, India, at the Department of Botany in University of Delhi on December 26-30, 2013 titled - "1(st) Plant Proteomics Workshop / Training Program" under the umbrella of INPPO India-Nepal chapter. Selected 20 participants received on-hand training mainly on gel-based proteomics approach along with manual booklet and parallel lectures on this and associated topics. In house, as well as invited experts drawn from other Universities and Institutes (national and international), delivered talks on different aspects of gel-based and gel-free proteomics. Importance of gel-free proteomics approach, translational proteomics, and INPPO roles were presented and interactively discussed by a group of three invited speakers Drs. Ganesh Kumar Agrawal (Nepal), Randeep Rakwal (Japan), and Antonio Masi (Italy). Given the output of this systematic workshop, it was proposed and thereafter decided to be organized every alternate year; the next workshop will be held in 2015. Furthermore, possibilities on providing advanced training to those students / researchers / teachers with basic knowledge in proteomics theory and experiments at national and international levels were discussed. INPPO is committed to generating next-generation trained manpower in proteomics, and it would only happen by the firm determination of scientists to come forward and do it. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The strategy, organization, and progress of the HUPO Human Proteome Project.

PubMed

Omenn, Gilbert S

2014-04-04

The Human Proteome Project is a major, comprehensive initiative of the Human Proteome Organization. This global collaborative effort aims to identify and characterize at least one protein product and many PTM, SAP, and splice variant isoforms from the 20,300 human protein-coding genes. The deliverables are an extensive parts list and an array of technology platforms, reagents, spectral libraries, and linked knowledge bases that advance the field and facilitate the use of proteomics by a much wider community of life scientists. Such enablement will help address the Grand Challenge of using proteomics to bridge major gaps between evidence of genomic variation and diverse phenotypes. The HUPO Human Proteome Project (HPP) has made an outstanding launch, including a special issue of the Journal of Proteome Research on the Chromosome-centric HPP with a total of 48 articles. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes? © 2013.

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

PubMed Central

Hajduk, Joanna; Klupczynska, Agnieszka; Dereziński, Paweł; Matysiak, Jan; Kokot, Piotr; Nowak, Dorota M.; Gajęcka, Marzena; Nowak-Markwitz, Ewa; Kokot, Zenon J.

2015-01-01

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases. PMID:26694367

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate the feasibility and power of the proposed DCA-based profile biomarker diagnosis in achieving high sensitivity and conquering the data reproducibility issue in serum proteomics. Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction. In particular, our profile biomarker diagnosis can be generalized to other omics data for derivative component analysis (DCA)'s nature of generic data analysis.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. PMID:20586475

Characterization of the human aqueous humour proteome: A comparison of the genders.

PubMed

Perumal, Natarajan; Manicam, Caroline; Steinicke, Matthias; Funke, Sebastian; Pfeiffer, Norbert; Grus, Franz H

2017-01-01

Aqueous humour (AH) is an important biologic fluid that maintains normal intraocular pressure and contains proteins that regulate the homeostasis of ocular tissues. Any alterations in the protein compositions are correlated to the pathogenesis of various ocular disorders. In recent years, gender-based medicine has emerged as an important research focus considering the prevalence of certain diseases, which are higher in a particular sex. Nevertheless, the inter-gender variations in the AH proteome are unknown. Therefore, this study endeavoured to characterize the AH proteome to assess the differences between genders. Thirty AH samples of patients who underwent cataract surgery were categorized according to their gender. Label-free quantitative discovery mass spectrometry-based proteomics strategy was employed to characterize the AH proteome. A total of 147 proteins were identified with a false discovery rate of less than 1% and only the top 10 major AH proteins make up almost 90% of the total identified proteins. A large number of proteins identified were correlated to defence, immune and inflammatory mechanisms, and response to wounding. Four proteins were found to be differentially abundant between the genders, comprising SERPINF1, SERPINA3, SERPING1 and PTGDS. The findings emerging from our study provide the first insight into the gender-based proteome differences in the AH and also highlight the importance in considering potential sex-dependent changes in the proteome of ocular pathologies in future studies employing the AH.

Label-free protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes.

PubMed

Wang, Guanghui; Wu, Wells W; Zeng, Weihua; Chou, Chung-Lin; Shen, Rong-Fong

2006-05-01

A critical step in protein biomarker discovery is the ability to contrast proteomes, a process referred generally as quantitative proteomics. While stable-isotope labeling (e.g., ICAT, 18O- or 15N-labeling, or AQUA) remains the core technology used in mass spectrometry-based proteomic quantification, increasing efforts have been directed to the label-free approach that relies on direct comparison of peptide peak areas between LC-MS runs. This latter approach is attractive to investigators for its simplicity as well as cost effectiveness. In the present study, the reproducibility and linearity of using a label-free approach to highly complex proteomes were evaluated. Various amounts of proteins from different proteomes were subjected to repeated LC-MS analyses using an ion trap or Fourier transform mass spectrometer. Highly reproducible data were obtained between replicated runs, as evidenced by nearly ideal Pearson's correlation coefficients (for ion's peak areas or retention time) and average peak area ratios. In general, more than 50% and nearly 90% of the peptide ion ratios deviated less than 10% and 20%, respectively, from the average in duplicate runs. In addition, the multiplicity ratios of the amounts of proteins used correlated nicely with the observed averaged ratios of peak areas calculated from detected peptides. Furthermore, the removal of abundant proteins from the samples led to an improvement in reproducibility and linearity. A computer program has been written to automate the processing of data sets from experiments with groups of multiple samples for statistical analysis. Algorithms for outlier-resistant mean estimation and for adjusting statistical significance threshold in multiplicity of testing were incorporated to minimize the rate of false positives. The program was applied to quantify changes in proteomes of parental and p53-deficient HCT-116 human cells and found to yield reproducible results. Overall, this study demonstrates an alternative approach that allows global quantification of differentially expressed proteins in complex proteomes. The utility of this method to biomarker discovery is likely to synergize with future improvements in the detecting sensitivity of mass spectrometers.

Comparative evaluation of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) and high-pH reversed phase (Hp-RP) chromatography in profiling of rat kidney proteome.

PubMed

Hao, Piliang; Ren, Yan; Dutta, Bamaprasad; Sze, Siu Kwan

2013-04-26

ERLIC and high-pH RP (Hp-RP) have been reported to be promising alternatives to strong cation exchange (SCX) in proteome fractionation. Here we compared the performance of ERLIC, concatenated ERLIC and concatenated Hp-RP in proteome profiling. The protein identification is comparable in these three strategies, but significantly more unique peptides are identified by the two concatenation methods, resulting in a significant increase of the average protein sequence coverage. The pooling of fractions from spaced intervals results in more uniform distribution of peptides in each fraction compared with the chromatogram-based pooling of adjacent fractions. ERLIC fractionates peptides according to their pI and GRAVY values. These properties remains but becomes less remarkable in concatenated ERLIC. In contrast, the average pI and GRAVY values of the peptides are comparable in each fraction in concatenated Hp-RP. ERLIC performs the best in identifying peptides with pI>9 among the three strategies, while concatenated Hp-RP is good at identifying peptides with pI<4. These advantages are useful when either basic or acidic peptides/proteins are analytical targets. The power of ERLIC in identification of basic peptides seems to be due to their efficient separation from acidic peptides. This study facilitates the choice of proper fractionation strategies based on specific objectives. For in-depth proteomic analysis of a cell, tissue and plasma, multidimensional liquid chromatography (MDLC) is still necessary to reduce sample complexity for improving analytical dynamic range and proteome coverage. This work conducts a direct comparison of three promising first-dimensional proteome fractionation methods. They are comparable in identifying proteins, but concatenated ERLIC and concatenated Hp-RP identify significantly more unique peptides than ERLIC. ERLIC is good at analyzing basic peptides, while concatenated Hp-RP performs the best in analyzing acidic peptides with pI<4. This will facilitate the choice of the proper peptide fractionation strategy based on a specific need. A combination of different fractionation strategies can be used to increase the sequence coverage and number of protein identification due to the complementary effect between different methods. Copyright © 2013 Elsevier B.V. All rights reserved.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

PubMed Central

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V.; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J.; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wiśniewski, Jacek R.; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. PMID:17090601

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

The International Proteomics Tutorial Programme (IPTP): a teaching tool box for the proteomics community.

PubMed

James, Peter

2011-09-01

The most critical functions of the various proteomics organisations are the training of young scientists and the dissemination of information to the general scientific community. The education committees of the Human Proteome Organisation (HUPO) and the European Proteomics Association (EuPA) together with their national counterparts are therefore launching the International Proteomics Tutorial Programme to meet these needs. The programme is being led by Peter James (Sweden), Thierry Rabilloud (France) and Kazuyuki Nakamura (Japan). It involves collaboration between the leading proteomics journals: Journal of Proteome Research, Journal of Proteomics, Molecular and Cellular Proteomics, and Proteomics. The overall level is aimed at Masters/PhD level students who are starting out their research and who would benefit from a solid grounding in the techniques used in modern protein-based research. The tutorial program will cover core techniques and basics as an introduction to scientists new to the field. At a later stage the programme may be expanded with a series of more advanced topics focussing on the application of proteomics techniques to biological problem solving. The entire series of articles and slides will be made freely available for teaching use at the Journals and Organisations homepages and at a special website, www.proteomicstutorials.org. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Explore, Visualize, and Analyze Functional Cancer Proteomic Data Using the Cancer Proteome Atlas. | Office of Cancer Genomics

Cancer.gov

Reverse-phase protein arrays (RPPA) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and to develop novel cancer therapies. To facilitate community-based investigation of the large-scale protein expression data generated by this platform, we have developed a user-friendly, open-access bioinformatic resource, The Cancer Proteome Atlas (TCPA, http://tcpaportal.org), which contains two separate web applications.

Top-down proteomics for the analysis of proteolytic events - Methods, applications and perspectives.

PubMed

Tholey, Andreas; Becker, Alexander

2017-11-01

Mass spectrometry based proteomics is an indispensable tool for almost all research areas relevant for the understanding of proteolytic processing, ranging from the identification of substrates, products and cleavage sites up to the analysis of structural features influencing protease activity. The majority of methods for these studies are based on bottom-up proteomics performing analysis at peptide level. As this approach is characterized by a number of pitfalls, e.g. loss of molecular information, there is an ongoing effort to establish top-down proteomics, performing separation and MS analysis both at intact protein level. We briefly introduce major approaches of bottom-up proteomics used in the field of protease research and highlight the shortcomings of these methods. We then discuss the present state-of-the-art of top-down proteomics. Together with the discussion of known challenges we show the potential of this approach and present a number of successful applications of top-down proteomics in protease research. This article is part of a Special Issue entitled: Proteolysis as a Regulatory Event in Pathophysiology edited by Stefan Rose-John. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

PubMed Central

Hartler, Jürgen; Thallinger, Gerhard G; Stocker, Gernot; Sturn, Alexander; Burkard, Thomas R; Körner, Erik; Rader, Robert; Schmidt, Andreas; Mechtler, Karl; Trajanoski, Zlatko

2007-01-01

Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community. PMID:17567892

The Escherichia coli O157:H7 cattle immuno-proteome includes outer membrane protein A (OmpA), a modulator of adherence to bovine recto-anal junction squamous epithelial (RSE) cells

PubMed Central

Kudva, Indira T.; Krastins, Bryan; Torres, Alfredo G.; Griffin, Robert W.; Sheng, Haiqing; Sarracino, David A.; Hovde, Carolyn J.; Calderwood, Stephen B.; John, Manohar

2015-01-01

SUMMARY Building on previous studies, we defined the repertoire of proteins comprising the immuno-proteome of E. coli O157:H7 (O157) cultured in DMEM supplemented with norepinephrine (NE; O157 immuno-proteome), a β-adrenergic hormone that regulates E. coli O157 gene expression in the gastrointestinal tract, using a variation of a novel proteomics-based platform proteome mining tool for antigen discovery, called Proteomics-based Expression Library Screening (PELS; Kudva et al., 2006). The E. coli O157 immuno-proteome (O157-IP) comprised 91 proteins, and included those identified previously using PELS, and also proteins comprising DMEM- and bovine rumen fluid- proteomes. Outer membrane protein A (OmpA), a common component of the above proteomes, and reportedly a contributor to E. coli O157 adherence to cultured Hep-2 epithelial cells, was interestingly found to be a modulator rather than a contributor to E. coli O157 adherence to bovine recto-anal junction squamous epithelial (RSE) cells. Our results point to a role for yet to be identified members of the O157-IP in E. coli O157 adherence to RSE-cells, and additionally implicate a possible role for the OmpA regulator, TdcA, in the expression of such adhesins. Our observations have implications for development of efficacious vaccines for preventing E. coli O157 colonization of the bovine gastrointestinal tract. PMID:25643951

A complete mass spectrometric map for the analysis of the yeast proteome and its application to quantitative trait analysis

PubMed Central

Picotti, Paola; Clement-Ziza, Mathieu; Lam, Henry; Campbell, David S.; Schmidt, Alexander; Deutsch, Eric W.; Röst, Hannes; Sun, Zhi; Rinner, Oliver; Reiter, Lukas; Shen, Qin; Michaelson, Jacob J.; Frei, Andreas; Alberti, Simon; Kusebauch, Ulrike; Wollscheid, Bernd; Moritz, Robert; Beyer, Andreas; Aebersold, Ruedi

2013-01-01

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways. PMID:23334424

A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics

PubMed Central

Chang, Ying-Hua; Gregorich, Zachery R.; Chen, Albert J.; Hwang, Leekyoung; Guner, Huseyin; Yu, Deyang; Zhang, Jianyi; Ge, Ying

2015-01-01

Tissue proteomics is increasingly recognized for its role in biomarker discovery and disease mechanism investigation. However, protein solubility remains a significant challenge in mass spectrometry (MS)-based tissue proteomics. Conventional surfactants such as sodium dodecyl sulfate (SDS), the preferred surfactant for protein solubilization, are not compatible with MS. Herein, we have screened a library of surfactant-like compounds and discovered an MS-compatible degradable surfactant (MaSDeS) for tissue proteomics that solubilizes all categories of proteins with performance comparable to SDS. The use of MaSDeS in the tissue extraction significantly improves the total number of protein identifications from commonly used tissues, including tissue from the heart, liver, and lung. Notably, MaSDeS significantly enriches membrane proteins, which are often under-represented in proteomics studies. The acid degradable nature of MaSDeS makes it amenable for high-throughput mass spectrometry-based proteomics. In addition, the thermostability of MaSDeS allows for its use in experiments requiring high temperature to facilitate protein extraction and solubilization. Furthermore, we have shown that MaSDeS outperforms the other MS-compatible surfactants in terms of overall protein solubility and the total number of identified proteins in tissue proteomics. Thus, the use of MaSDeS will greatly advance tissue proteomics and realize its potential in basic biomedical and clinical research. MaSDeS could be utilized in a variety of proteomics studies as well as general biochemical and biological experiments that employ surfactants for protein solubilization. PMID:25589168

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

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

Tabb, David L.; Wang, Xia; Carr, Steven A.

2016-03-04

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilarmore » workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation. From these assessments we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61-93% of the time. When comparing across different instruments and quantitative technologies, differential genes were reproduced by other data sets from 67-99% of the time. Projecting gene differences to biological pathways and networks increased the similarities. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.« less

A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting.

PubMed

Wiśniewski, Jacek R; Mann, Matthias

2016-07-01

Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system.

Proteomics in India: A Report on a Brainstorming Meeting at Hyderabad, India.

PubMed

Chatterjee, Bhaswati; Makarov, Alexander; Clemmer, David E; Steen, Hanno; Steen, Judith; Saffell-Clemmer, Wendy; Moghekar, Abhay R; Mohan Rao, Chintalagiri; Bradshaw, Ralph A; Thakur, Suman S

2016-07-01

The Centre for Cellular and Molecular Biology, Hyderabad, India, was host for an international forum, or "brainstorming meeting," on proteomics held in November 2014, which provided the opportunity to showcase proteomic science in India and to allow discussions between Indian scientists and students and several international visitors. This provided an amalgamation of speakers and participants whose interests lay mainly in developing and using mass-spectrometry-based proteomics to advance their research work. A week-long workshop with hands-on training in proteomic methodology followed the meeting. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Forensic proteomics for the evaluation of the post-mortem decay in bones.

PubMed

Procopio, Noemi; Williams, Anna; Chamberlain, Andrew T; Buckley, Michael

2018-04-15

Current methods for evaluation the of post-mortem interval (PMI) of skeletal remains suffer from poor accuracy due to the great number of variables that affect the diagenetic process and to the lack of specific guidelines to address this issue. During decomposition, proteins can undergo cumulative decay over the time, resulting in a decrease in the range and abundance of proteins present (i.e., the proteome) in different tissues as well as in an increase of post-translational modifications occurring in these proteins. In this study, we investigate the applicability of bone proteomic analyses to simulated forensic contexts, looking for specific biomarkers that may help the estimation of PMI, as well as evaluate a previously discovered marker for the estimation of biological age. We noticed a reduction of particular plasma and muscle proteins with increasing PMIs, as well as an increased deamidation of biglycan, a protein with a role in modulating bone growth and mineralization. We also corroborated our previous results regarding the use of fetuin-A as a potential biomarker for the estimation of age-at-death, demonstrating the applicability and the great potential that proteomics may have towards forensic sciences. The estimation of the post-mortem interval has a key role in forensic investigations, however nowadays it still suffers from poor reliability, especially when body tissues are heavily decomposed. Here we propose for the first time the application of bone proteomics to the estimation of the time elapsed since death and found several new potential biomarkers to address this, demonstrating the applicability of proteomic analyses to forensic sciences. Copyright © 2018. Published by Elsevier B.V.

Comparative Proteomic Analyses of Human Adipose Extracellular Matrices Decellularized Using Alternative Procedures.

PubMed

Thomas-Porch, Caasy; Li, Jie; Zanata, Fabiana; Martin, Elizabeth C; Pashos, Nicholas; Genemaras, Kaylynn; Poche, J Nicholas; Totaro, Nicholas P; Bratton, Melyssa R; Gaupp, Dina; Frazier, Trivia; Wu, Xiying; Ferreira, Lydia Masako; Tian, Weidong; Wang, Guangdi; Bunnell, Bruce A; Flynn, Lauren; Hayes, Daniel; Gimble, Jeffrey M

2018-04-25

Decellularized human adipose tissue has potential clinical utility as a processed biological scaffold for soft tissue cosmesis, grafting and reconstruction. Adipose tissue decellularization has been accomplished using enzymatic-, detergent-, and/or solvent-based methods. To examine the hypothesis that distinct decellularization processes may yield scaffolds with differing compositions, the current study employed mass spectrometry to compare the proteomes of human adipose-derived matrices generated through three independent methods combining enzymatic-, detergent-, and/or solvent-based steps. In addition to protein content, bioscaffolds were evaluated for DNA depletion, ECM composition, and physical structure using optical density, histochemical staining, and scanning electron microscopy (SEM). Mass spectrometry (MS) based proteomic analyses identified 25 proteins (having at least two peptide sequences detected) in the scaffolds generated with an enzymatic approach, 143 with the detergent approach, and 102 with the solvent approach, as compared to 155 detected in unprocessed native human fat. Immunohistochemical detection confirmed the presence of the structural proteins actin, collagen type VI, fibrillin, laminin, and vimentin. Subsequent in vivo analysis of the predominantly enzymatic- and detergent-based decellularized scaffolds following subcutaneous implantation in GFP + transgenic mice demonstrated that the matrices generated with both approaches supported the ingrowth of host-derived adipocyte progenitors and vasculature in a time dependent manner. Together, these results determine that decellularization methods influence the protein composition of adipose tissue-derived bioscaffolds. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

PubMed

Giménez, Estela; Gay, Marina; Vilaseca, Marta

2017-01-30

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

Microbial profiling, neural network and semantic web: an integrated information system for human pathogen risk management, prevention and surveillance in food safety

USDA-ARS?s Scientific Manuscript database

It is estimated that food-borne pathogens cause approximately 76 million cases of gastrointestinal illnesses, 325,000 hospitalizations, and 5,000 deaths in the United States annually. Genomic, proteomic, and metabolomic studies, particularly, genome sequencing projects are providing valuable inform...

Molecular medicine and the development of cancer chemopreventive agents.

PubMed

Izzotti, Alberto

2012-07-01

Chemoprevention is effective in inhibiting the onset of cancer in experimental animal models, but the transferability of similar results to humans is questionable. Therefore, reliable intermediate molecular biomarkers are needed to evaluate the efficacy of chemopreventive agents before the onset of cancer. The use of genomic biomarkers is limited by their poor predictive value. Although post-genomic biomarkers (i.e., gene-expression analyses) are useful for evaluating the safety, efficacy, and mechanistic basis of chemopreventive agents, the biomarkers are often poorly related to the phenotype, due to posttranscriptional regulation. Proteome analyses can evaluate preclinical phenotype alterations, but only at low protein counts. MicroRNA alterations, which are essential for the development of cancer, may be modulated by chemopreventive agents. Furthermore, microRNA delivery may be used to counteract carcinogenesis. Exposure to cigarette smoke induces microRNA let-7 downregulation and cell proliferation that can be converted to cell growth arrest and apoptosis upon let-7a transfection. Therefore, microRNAs are reliable biomarkers for evaluating chemoprevention efficacy and may be used to counteract carcinogenesis. © 2012 New York Academy of Sciences.

Elucidating the fungal stress response by proteomics.

PubMed

Kroll, Kristin; Pähtz, Vera; Kniemeyer, Olaf

2014-01-31

Fungal species need to cope with stress, both in the natural environment and during interaction of human- or plant pathogenic fungi with their host. Many regulatory circuits governing the fungal stress response have already been discovered. However, there are still large gaps in the knowledge concerning the changes of the proteome during adaptation to environmental stress conditions. With the application of proteomic methods, particularly 2D-gel and gel-free, LC/MS-based methods, first insights into the composition and dynamic changes of the fungal stress proteome could be obtained. Here, we review the recent proteome data generated for filamentous fungi and yeasts. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Proteome-wide Adaptations of Mouse Skeletal Muscles during a Full Month in Space.

PubMed

Tascher, Georg; Brioche, Thomas; Maes, Pauline; Chopard, Angèle; O'Gorman, Donal; Gauquelin-Koch, Guillemette; Blanc, Stéphane; Bertile, Fabrice

2017-07-07

The safety of space flight is challenged by a severe loss of skeletal muscle mass, strength, and endurance that may compromise the health and performance of astronauts. The molecular mechanisms underpinning muscle atrophy and decreased performance have been studied mostly after short duration flights and are still not fully elucidated. By deciphering the muscle proteome changes elicited in mice after a full month aboard the BION-M1 biosatellite, we observed that the antigravity soleus incurred the greatest changes compared with locomotor muscles. Proteomics data notably suggested mitochondrial dysfunction, metabolic and fiber type switching toward glycolytic type II fibers, structural alterations, and calcium signaling-related defects to be the main causes for decreased muscle performance in flown mice. Alterations of the protein balance, mTOR pathway, myogenesis, and apoptosis were expected to contribute to muscle atrophy. Moreover, several signs reflecting alteration of telomere maintenance, oxidative stress, and insulin resistance were found as possible additional deleterious effects. Finally, 8 days of recovery post flight were not sufficient to restore completely flight-induced changes. Thus in-depth proteomics analysis unraveled the complex and multifactorial remodeling of skeletal muscle structure and function during long-term space flight, which should help define combined sets of countermeasures before, during, and after the flight.

Unlocking the proteomic information encoded in MALDI-TOF-MS data used for microbial identification and characterization.

PubMed

Fagerquist, Clifton K

2017-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is increasingly utilized as a rapid technique to identify microorganisms including pathogenic bacteria. However, little attention has been paid to the significant proteomic information encoded in the MS peaks that collectively constitute the MS 'fingerprint'. This review/perspective is intended to explore this topic in greater detail in the hopes that it may spur interest and further research in this area. Areas covered: This paper examines the recent literature on utilizing MALDI-TOF for bacterial identification. Critical works highlighting protein biomarker identification of bacteria, arguments for and against protein biomarker identification, proteomic approaches to biomarker identification, emergence of MALDI-TOF-TOF platforms and their use for top-down proteomic identification of bacterial proteins, protein denaturation and its effect on protein ion fragmentation, collision cross-sections and energy deposition during desorption/ionization are also explored. Expert commentary: MALDI-TOF and TOF-TOF mass spectrometry platforms will continue to provide chemical analyses that are rapid, cost-effective and high throughput. These instruments have proven their utility in the taxonomic identification of pathogenic bacteria at the genus and species level and are poised to more fully characterize these microorganisms to the benefit of clinical microbiology, food safety and other fields.

Proteomics approaches advance our understanding of plant self-incompatibility response.

PubMed

Sankaranarayanan, Subramanian; Jamshed, Muhammad; Samuel, Marcus A

2013-11-01

Self-incompatibility (SI) in plants is a genetic mechanism that prevents self-fertilization and promotes out-crossing needed to maintain genetic diversity. SI has been classified into two broad categories: the gametophytic self-incompatibility (GSI) and the sporophytic self-incompatibility (SSI) based on the genetic mechanisms involved in 'self' pollen rejection. Recent proteomic approaches to identify potential candidates involved in SI have shed light onto a number of previously unidentified mechanisms required for SI response. SI proteome research has progressed from the use of isoelectric focusing in early days to the latest third-generation technique of comparative isobaric tag for relative and absolute quantitation (iTRAQ) used in recent times. We will focus on the proteome-based approaches used to study self-incompatibility (GSI and SSI), recent developments in the field of incompatibility research with emphasis on SSI and future prospects of using proteomic approaches to study self-incompatibility.

Proteomic platform for the identification of proteins in olive (Olea europaea) pulp.

PubMed

Capriotti, Anna Laura; Cavaliere, Chiara; Foglia, Patrizia; Piovesana, Susy; Samperi, Roberto; Stampachiacchiere, Serena; Laganà, Aldo

2013-10-24

The nutritional and cancer-protective properties of the oil extracted mechanically from the ripe fruits of Olea europaea trees are attracting constantly more attention worldwide. The preparation of high-quality protein samples from plant tissues for proteomic analysis poses many challenging problems. In this study we employed a proteomic platform based on two different extraction methods, SDS and CHAPS based protocols, followed by two precipitation protocols, TCA/acetone and MeOH precipitation, in order to increase the final number of identified proteins. The use of advanced MS techniques in combination with the Swissprot and NCBI Viridiplantae databases and TAIR10 Arabidopsis database allowed us to identify 1265 proteins, of which 22 belong to O. europaea. The application of this proteomic platform for protein extraction and identification will be useful also for other proteomic studies on recalcitrant plant/fruit tissues. Copyright © 2013. Published by Elsevier B.V.

Proteomics of Plant Pathogenic Fungi

PubMed Central

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V.

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection. PMID:20589070

Proteomics of plant pathogenic fungi.

PubMed

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Implementation of Recommendations from the One System Comparative Evaluation of the Hanford Tank Farms and Waste Treatment Plant Safety Bases

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

Garrett, Richard L.; Niemi, Belinda J.; Paik, Ingle K.

2013-11-07

A Comparative Evaluation was conducted for One System Integrated Project Team to compare the safety bases for the Hanford Waste Treatment and Immobilization Plant Project (WTP) and Tank Operations Contract (TOC) (i.e., Tank Farms) by an Expert Review Team. The evaluation had an overarching purpose to facilitate effective integration between WTP and TOC safety bases. It was to provide One System management with an objective evaluation of identified differences in safety basis process requirements, guidance, direction, procedures, and products (including safety controls, key safety basis inputs and assumptions, and consequence calculation methodologies) between WTP and TOC. The evaluation identified 25more » recommendations (Opportunities for Integration). The resolution of these recommendations resulted in 16 implementation plans. The completion of these implementation plans will help ensure consistent safety bases for WTP and TOC along with consistent safety basis processes. procedures, and analyses. and should increase the likelihood of a successful startup of the WTP. This early integration will result in long-term cost savings and significant operational improvements. In addition, the implementation plans lead to the development of eight new safety analysis methodologies that can be used at other U.S. Department of Energy (US DOE) complex sites where URS Corporation is involved.« less

Evaluating the efficacy of subcellular fractionation of blast cells using live cell labeling and 2D DIGE.

PubMed

Ho, Yin Ying; Penno, Megan; Perugini, Michelle; Lewis, Ian; Hoffmann, Peter

2012-01-01

Labeling of exposed cell surface proteins of live cells using CyDye DIGE fluor minimal dyes is an efficient strategy for cell surface proteome profiling and quantifying differentially expressed proteins in diseases. Here we describe a strategy to evaluate a two-step detergent-based protein fractionation method using live cell labeling followed by visualization of the fluorescently labeled cell surface proteins and fractionated proteins within a single 2D gel.

Proteomic changes involved in tenderization of bovine Longissimus dorsi muscle during prolonged ageing.

PubMed

Polati, Rita; Menini, Michele; Robotti, Elisa; Millioni, Renato; Marengo, Emilio; Novelli, Enrico; Balzan, Stefania; Cecconi, Daniela

2012-12-01

To study proteomic changes involved in tenderization of bovine Longissimus dorsi four Charolaise heifers and four Charolaise bull's muscles were sampled at slaughter after early and long ageing (2-4°C for 12 and 26days respectively). Descriptive sensory evaluation of samples were performed and their tenderness evaluated by Warner-Bratzler shear force test. Protein composition of fresh muscle and of meat aged was analysed by cartesian and polar 2-D electrophoresis. Student's t-test and Ranking-PCA analyses were performed to detect proteomic modulation, and the selected protein spots were identified by nano-HPLC-Chip MS/MS. This research has demonstrated that there are no differences between proteomic patterns of male and females Longissimus dorsi muscle, and that the extension of ageing beyond 12days, did not brings any concrete advantage in terms of sensory quality. Furthermore, the data presented here demonstrated that meat maturation caused changes of the abundance of proteins involved in metabolic, structural, and stress related processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparative proteomics in alkaptonuria provides insights into inflammation and oxidative stress.

PubMed

Braconi, Daniela; Bernardini, Giulia; Paffetti, Alessandro; Millucci, Lia; Geminiani, Michela; Laschi, Marcella; Frediani, Bruno; Marzocchi, Barbara; Santucci, Annalisa

2016-12-01

Alkaptonuria (AKU) is an ultra-rare inborn error of metabolism associated with a defective catabolism of phenylalanine and tyrosine leading to increased systemic levels of homogentisic acid (HGA). Excess HGA is partly excreted in the urine, partly accumulated within the body and deposited onto connective tissues under the form of an ochronotic pigment, leading to a range of clinical manifestations. No clear genotype/phenotype correlation was found in AKU, and today there is the urgent need to identify biomarkers able to monitor AKU progression and evaluate response to treatment. With this aim, we provided the first proteomic study on serum and plasma samples from alkaptonuric individuals showing pathological SAA, CRP and Advanced Oxidation Protein Products (AOPP) levels. Interesting similarities with proteomic studies on other rheumatic diseases were highlighted together with proteome alterations supporting the existence of oxidative stress and inflammation in AKU. Potential candidate biomarkers to assess disease severity, monitor disease progression and evaluate response to treatment were identified as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Proteome analysis in the assessment of ageing.

PubMed

Nkuipou-Kenfack, Esther; Koeck, Thomas; Mischak, Harald; Pich, Andreas; Schanstra, Joost P; Zürbig, Petra; Schumacher, Björn

2014-11-01

Based on demographic trends, the societies in many developed countries are facing an increasing number and proportion of people over the age of 65. The raise in elderly populations along with improved health-care will be concomitant with an increased prevalence of ageing-associated chronic conditions like cardiovascular, renal, and respiratory diseases, arthritis, dementia, and diabetes mellitus. This is expected to pose unprecedented challenges both for individuals and societies and their health care systems. An ultimate goal of ageing research is therefore the understanding of physiological ageing and the achievement of 'healthy' ageing by decreasing age-related pathologies. However, on a molecular level, ageing is a complex multi-mechanistic process whose contributing factors may vary individually, partly overlap with pathological alterations, and are often poorly understood. Proteome analysis potentially allows modelling of these multifactorial processes. This review summarises recent proteomic research on age-related changes identified in animal models and human studies. We combined this information with pathway analysis to identify molecular mechanisms associated with ageing. We identified some molecular pathways that are affected in most or even all organs and others that are organ-specific. However, appropriately powered studies are needed to confirm these findings based in in silico evaluation. Copyright © 2014 Elsevier B.V. All rights reserved.

The current status of clinical proteomics and the use of MRM and MRM(3) for biomarker validation.

PubMed

Lemoine, Jérôme; Fortin, Tanguy; Salvador, Arnaud; Jaffuel, Aurore; Charrier, Jean-Philippe; Choquet-Kastylevsky, Geneviève

2012-05-01

The transfer of biomarkers from the discovery field to clinical use is still, despite progress, on a road filled with pitfalls. Since the emergence of proteomics, thousands of putative biomarkers have been published, often with overlapping diagnostic capacities. The strengthening of the robustness of discovery technologies, particularly in mass spectrometry, has been followed by intense discussions on establishing well-defined evaluation procedures for the identified targets to ultimately allow the clinical validation and then the clinical use of some of these biomarkers. Some of the obstacles to the evaluation process have been the lack of the availability of quick and easy-to-develop, easy-to-use, robust, specific and sensitive alternative quantitative methods when immunoaffinity-based tests are unavailable. Multiple reaction monitoring (MRM; also called selected reaction monitoring) is currently proving its capabilities as a complementary or alternative technique to ELISA for large biomarker panel evaluation. Here, we present how MRM(3) can overcome the lack of specificity and sensitivity often encountered by MRM when tracking minor proteins diluted by complex biological matrices.

Sys-BodyFluid: a systematical database for human body fluid proteome research

PubMed Central

Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong

2009-01-01

Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10 000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/. PMID:18978022

Sys-BodyFluid: a systematical database for human body fluid proteome research.

PubMed

Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong

2009-01-01

Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10,000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/.

Proteomic Stable Isotope Probing Reveals Biosynthesis Dynamics of Slow Growing Methane Based Microbial Communities

PubMed Central

Marlow, Jeffrey J.; Skennerton, Connor T.; Li, Zhou; Chourey, Karuna; Hettich, Robert L.; Pan, Chongle; Orphan, Victoria J.

2016-01-01

Marine methane seep habitats represent an important control on the global flux of methane. Nucleotide-based meta-omics studies outline community-wide metabolic potential, but expression patterns of environmentally relevant proteins are poorly characterized. Proteomic stable isotope probing (proteomic SIP) provides additional information by characterizing phylogenetically specific, functionally relevant activity in mixed microbial communities, offering enhanced detection through system-wide product integration. Here we applied proteomic SIP to 15NH4+ and CH4 amended seep sediment microcosms in an attempt to track protein synthesis of slow-growing, low-energy microbial systems. Across all samples, 3495 unique proteins were identified, 11% of which were 15N-labeled. Consistent with the dominant anaerobic oxidation of methane (AOM) activity commonly observed in anoxic seep sediments, proteins associated with sulfate reduction and reverse methanogenesis—including the ANME-2 associated methylenetetrahydromethanopterin reductase (Mer)—were all observed to be actively synthesized (15N-enriched). Conversely, proteins affiliated with putative aerobic sulfur-oxidizing epsilon- and gammaproteobacteria showed a marked decrease over time in our anoxic sediment incubations. The abundance and phylogenetic range of 15N-enriched methyl-coenzyme M reductase (Mcr) orthologs, many of which exhibited novel post-translational modifications, suggests that seep sediments provide niches for multiple organisms performing analogous metabolisms. In addition, 26 proteins of unknown function were consistently detected and actively expressed under conditions supporting AOM, suggesting that they play important roles in methane seep ecosystems. Stable isotope probing in environmental proteomics experiments provides a mechanism to determine protein durability and evaluate lineage-specific responses in complex microbial communities placed under environmentally relevant conditions. Our work here demonstrates the active synthesis of a metabolically specific minority of enzymes, revealing the surprising longevity of most proteins over the course of an extended incubation experiment in an established, slow-growing, methane-impacted environmental system. PMID:27199908

Proteomics of drug resistance in Candida glabrata biofilms.

PubMed

Seneviratne, C Jayampath; Wang, Yu; Jin, Lijian; Abiko, Y; Samaranayake, Lakshman P

2010-04-01

Candida glabrata is a fungal pathogen that causes a variety of mucosal and systemic infections among compromised patient populations with higher mortality rates. Previous studies have shown that biofilm mode of the growth of the fungus is highly resistant to antifungal agents compared with the free-floating or planktonic mode of growth. Therefore, in the present study, we used 2-D DIGE to evaluate the differential proteomic profiles of C. glabrata under planktonic and biofilm modes of growth. Candida glabrata biofilms were developed on polystyrene surfaces and age-matched planktonic cultures were obtained in parallel. Initially, biofilm architecture, viability, and antifungal susceptibility were evaluated. Differentially expressed proteins more than 1.5-fold in DIGE analysis were subjected to MS/MS. The transcriptomic regulation of these biomarkers was evaluated by quantitative real-time PCR. Candida glabrata biofilms were highly resistant to the antifungals and biocides compared with the planktonic mode of growth. Candida glabrata biofilm proteome when compared with its planktonic proteome showed upregulation of stress response proteins, while glycolysis enzymes were downregulated. Similar trend could be observed at transcriptomic level. In conclusion, C. glabrata biofilms possess higher amount of stress response proteins, which may potentially contribute to the higher antifungal resistance seen in C. glabrata biofilms.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

PubMed

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R

2018-06-07

Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection.

PubMed

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie; Gruden, Kristina

2017-07-06

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato ( Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it.

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection

PubMed Central

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie

2017-01-01

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato (Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it. PMID:28684682

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

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

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Pressurized Pepsin Digestion in Proteomics

PubMed Central

López-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.; Hixson, Kim K.; Tian, Zhixin; Lee, Jung Hwa; Lee, Sang-Won; Tolić, Nikola; Weitz, Karl K.; Belov, Mikhail E.; Smith, Richard D.; Paša-Tolić, Ljiljana

2011-01-01

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome. PMID:20627868

SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers.

PubMed

Zanivan, Sara; Maione, Federica; Hein, Marco Y; Hernández-Fernaud, Juan Ramon; Ostasiewicz, Pawel; Giraudo, Enrico; Mann, Matthias

2013-12-01

Proteomics has been successfully used for cell culture on dishes, but more complex cellular systems have proven to be challenging and so far poorly approached with proteomics. Because of the complexity of the angiogenic program, we still do not have a complete understanding of the molecular mechanisms involved in this process, and there have been no in depth quantitative proteomic studies. Plating endothelial cells on matrigel recapitulates aspects of vessel growth, and here we investigate this mechanism by using a spike-in SILAC quantitative proteomic approach. By comparing proteomic changes in primary human endothelial cells morphogenesis on matrigel to general adhesion mechanisms in cells spreading on culture dish, we pinpoint pathways and proteins modulated by endothelial cells. The cell-extracellular matrix adhesion proteome depends on the adhesion substrate, and a detailed proteomic profile of the extracellular matrix secreted by endothelial cells identified CLEC14A as a matrix component, which binds to MMRN2. We verify deregulated levels of these proteins during tumor angiogenesis in models of multistage carcinogenesis. This is the most in depth quantitative proteomic study of endothelial cell morphogenesis, which shows the potential of applying high accuracy quantitative proteomics to in vitro models of vessel growth to shed new light on mechanisms that accompany pathological angiogenesis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000359.

Sherlock Holmes and the proteome--a detective story.

PubMed

Righetti, Pier Giorgio; Boschetti, Egisto

2007-02-01

The performance of a hexapeptide ligand library in capturing the 'hidden proteome' is illustrated and evaluated. This library, insolubilized on an organic polymer and available under the trade name 'Equalizer Bead Technology', acts by capturing all components of a given proteome, by concentrating rare and very rare proteins, and simultaneously diluting the abundant ones. This results in a proteome of 'normalized' relative abundances, amenable to analysis by MS and any other analytical tool. Examples are given of analysis of human urine and serum, as well as cell and tissue lysates, such as Escherichia coli and Saccharomyces cerevisiae extracts. Another important application is impurity tracking and polishing of recombinant DNA products, especially biopharmaceuticals meant for human consumption.

P-MartCancer: A New Online Platform to Access CPTAC Datasets and Enable New Analyses | Office of Cancer Clinical Proteomics Research

Cancer.gov

The November 1, 2017 issue of Cancer Research is dedicated to a collection of computational resource papers in genomics, proteomics, animal models, imaging, and clinical subjects for non-bioinformaticists looking to incorporate computing tools into their work. Scientists at Pacific Northwest National Laboratory have developed P-MartCancer, an open, web-based interactive software tool that enables statistical analyses of peptide or protein data generated from mass-spectrometry (MS)-based global proteomics experiments.

CPTAC Team Releases Targeted Proteomic Assays for Ovarian Cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Pacific Northwest National Laboratory (PNNL) investigators in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), announces the public release of 98 targeted mass spectrometry-based assays for ovarian cancer research studies.  Chosen based on proteogenomic observations from the recently published multi-institutional collaborative project between PNNL and Johns Hopkins University that comprehensively examined the collections of proteins in the tumors of ovarian cancer patients (highlighted in a paper in

ms_lims, a simple yet powerful open source laboratory information management system for MS-driven proteomics.

PubMed

Helsens, Kenny; Colaert, Niklaas; Barsnes, Harald; Muth, Thilo; Flikka, Kristian; Staes, An; Timmerman, Evy; Wortelkamp, Steffi; Sickmann, Albert; Vandekerckhove, Joël; Gevaert, Kris; Martens, Lennart

2010-03-01

MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High-throughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ms_lims), a freely available, open-source system based on a central database to automate data management and processing in MS-driven proteomics analyses.

Pressurized Pepsin Digestion in Proteomics: An Automatable Alternative to Trypsin for Integrated Top-down Bottom-up Proteomics

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

Lopez-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.

2011-02-01

Integrated top-down bottom-up proteomics combined with online digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to highthroughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications (PTMs). Herein, we describe recent efforts towards efficient integration of bottom-up and top-down LCMS based proteomic strategies. Since most proteomic platforms (i.e. LC systems) operate in acidic environments, we exploited themore » compatibility of the pepsin (i.e. the enzyme’s natural acidic activity) for the integration of bottom-up and top-down proteomics. Pressure enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an offline mode using a Barocycler or an online mode using a modified high pressure LC system referred to as a fast online digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultra-rapid integrated bottom-up top-down proteomic strategy employing a standard mixture of proteins and a monkey pox virus proteome.« less

Evaluation of several two-dimensional gel electrophoresis techniques in cardiac proteomics.

PubMed

Li, Zhao Bo; Flint, Paul W; Boluyt, Marvin O

2005-09-01

Two-dimensional gel electrophoresis (2-DE) is currently the best method for separating complex mixtures of proteins, and its use is gradually becoming more common in cardiac proteome analysis. A number of variations in basic 2-DE have emerged, but their usefulness in analyzing cardiac tissue has not been evaluated. The purpose of the present study was to systematically evaluate the capabilities and limitations of several 2-DE techniques for separating proteins from rat heart tissue. Immobilized pH gradient strips of various pH ranges, parameters of protein loading and staining, subcellular fractionation, and detection of phosphorylated proteins were studied. The results provide guidance for proteome analysis of cardiac and other tissues in terms of selection of the isoelectric point separating window for cardiac proteins, accurate quantitation of cardiac protein abundance, stabilization of technical variation, reduction of sample complexity, enrichment of low-abundant proteins, and detection of phosphorylated proteins.

Low-Molecular-Weight Plasma Proteome Analysis Using Top-Down Mass Spectrometry.

PubMed

Cheon, Dong Huey; Yang, Eun Gyeong; Lee, Cheolju; Lee, Ji Eun

2017-01-01

While human plasma has a wealth of diagnostic information regarding the state of the human body in heath and disease, low molecular weight (LMW) proteome (<30 kDa) has been shown to contain a rich source of diagnostic biomarkers. Here we describe a protocol for top-down proteomic analysis to identify and characterize the LMW proteoforms present in four types of human plasma samples without immunoaffinity depletion and with depletion of the top two, six, and seven high-abundance proteins. Each type of plasma sample was first fractionated based on molecular weight using gel-eluted liquid fraction entrapment electrophoresis (GELFrEE). Then, the GELFrEE fractions containing up to 30 kDa were subjected to nanocapillary-LC-MS/MS, and the high-resolution MS and MS/MS data were processed using ProSightPC software. As a result, a total of 442 LMW proteins and cleaved products, including those with posttranslational modifications (PTMs) and single amino acid variations (SAAVs), were identified with a threshold E-value of 1 × 10 -4 from the four types of plasma samples.

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics

PubMed Central

Lavallée-Adam, Mathieu

2017-01-01

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. PMID:27010334

Evolution of Novel 3D Culture Systems for Studies of Human Liver Function and Assessments of the Hepatotoxicity of Drugs and Drug Candidates.

PubMed

Andersson, Tommy B

2017-10-01

The pharmaceutical industry urgently needs reliable pre-clinical models to evaluate the efficacy and safety of new chemical entities before they enter the clinical trials. Development of in vitro model systems that emulate the functions of the human liver organ has been an elusive task. Cell lines exhibit a low drug-metabolizing capacity and primary liver cells rapidly dedifferentiate in culture, which restrict their usefulness substantially. Recently, the development of hepatocyte spheroid cultures has shown promising results. The proteome and transcriptome in the spheroids were similar to the liver tissue, and hepatotoxicity of selected substances was detected at in vivo-relevant concentrations. © 2017 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling.

PubMed

Xue, Lu; Lin, Lin; Zhou, Wenbin; Chen, Wendong; Tang, Jun; Sun, Xiujie; Huang, Peiwu; Tian, Ruijun

2018-06-09

Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 μL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Wang, Jing; Ma, Zihao; Carr, Steven A.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC).more » Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. Molecular & Cellular Proteomics 16: 10.1074/mcp.M116.060301, 121–134, 2017.« less

Proteome-wide analysis and diel proteomic profiling of the cyanobacterium Arthrospira platensis PCC 8005.

PubMed

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation.

Proteome-Wide Analysis and Diel Proteomic Profiling of the Cyanobacterium Arthrospira platensis PCC 8005

PubMed Central

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation. PMID:24914774

Proteomics in the study of the molecular taxonomy and epidemiology of bacterial pathogens.

PubMed

Cash, Phillip

2009-06-01

The ability to discriminate bacterial isolates is important for a number of areas of research in Medical Microbiology, particularly in defining bacterial taxonomy and monitoring transmission in epidemiological investigations. Molecular techniques capable of typing bacteria at the level of the genome and proteome are now widely used for these investigations. This review considers two electrophoretic methods for typing bacteria on the basis of their proteomes, namely 1-D SDS-PAGE and 2-DE. The application of these two techniques for bacterial typing is described with reference to two publications that appeared in Electrophoresis [Costa, Electrophoresis 1990, 11, 382-391 and Cash et al., Electrophoresis 1997, 18, 1472-1482]. Even though these methods have been used for nearly 20 years to differentiate bacterial isolates they remain key technologies in proteome-based typing methods. The developments that have arisen from the two key papers are described in order to highlight the advantages and disadvantages in typing bacteria at the level of their proteomes. Some of the difficulties associated with electrophoretic typing methods can be overcome by using non-gel proteomic methods based on MS to provide improved sensitivity and specificity. The application of proteomic methods to investigate bacterial taxonomy, epidemiology and pathogenesis in general has significant potential in furthering our understanding of infectious diseases.

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

Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis.

PubMed

Lo, Andy; Tang, Yanan; Chen, Lu; Li, Liang

2013-07-25

Isotope labeling liquid chromatography-mass spectrometry (LC-MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparative analysis of soybean plasma membrane proteins under osmotic stress using gel-based and LC MS/MS-based proteomics approaches.

PubMed

Nouri, Mohammad-Zaman; Komatsu, Setsuko

2010-05-01

To study the soybean plasma membrane proteome under osmotic stress, two methods were used: a gel-based and a LC MS/MS-based proteomics method. Two-day-old seedlings were subjected to 10% PEG for 2 days. Plasma membranes were purified from seedlings using a two-phase partitioning method and their purity was verified by measuring ATPase activity. Using the gel-based proteomics, four and eight protein spots were identified as up- and downregulated, respectively, whereas in the nanoLC MS/MS approach, 11 and 75 proteins were identified as up- and downregulated, respectively, under PEG treatment. Out of osmotic stress responsive proteins, most of the transporter proteins and all proteins with high number of transmembrane helices as well as low-abundance proteins could be identified by the LC MS/MS-based method. Three homologues of plasma membrane H(+)-ATPase, which are transporter proteins involved in ion efflux, were upregulated under osmotic stress. Gene expression of this protein was increased after 12 h of stress exposure. Among the identified proteins, seven proteins were mutual in two proteomics techniques, in which calnexin was the highly upregulated protein. Accumulation of calnexin in plasma membrane was confirmed by immunoblot analysis. These results suggest that under hyperosmotic conditions, calnexin accumulates in the plasma membrane and ion efflux accelerates by upregulation of plasma membrane H(+)-ATPase protein.

Beyond the proteome: Mass Spectrometry Special Interest Group (MS-SIG) at ISMB/ECCB 2013

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

Ryu, Soyoung; Payne, Samuel H.; Schaab, Christoph

2014-07-02

Mass spectrometry special interest group (MS-SIG) aims to bring together experts from the global research community to discuss highlights and challenges in the field of mass spectrometry (MS)-based proteomics and computational biology. The rapid echnological developments in MS-based proteomics have enabled the generation of a large amount of meaningful information on hundreds to thousands of proteins simultaneously from a biological sample; however, the complexity of the MS data require sophisticated computational algorithms and software for data analysis and interpretation. This year’s MS-SIG meeting theme was ‘Beyond the Proteome’ with major focuses on improving protein identification/quantification and using proteomics data tomore » solve interesting problems in systems biology and clinical research.« less

Making a protein extract from plant pathogenic fungi for gel- and LC-based proteomics.

PubMed

Fernández, Raquel González; Redondo, Inmaculada; Jorrin-Novo, Jesus V

2014-01-01

Proteomic technologies have become a successful tool to provide relevant information on fungal biology. In the case of plant pathogenic fungi, this approach would allow a deeper knowledge of the interaction and the biological cycle of the pathogen, as well as the identification of pathogenicity and virulence factors. These two elements open up new possibilities for crop disease diagnosis and environment-friendly crop protection. Phytopathogenic fungi, due to its particular cellular characteristics, can be considered as a recalcitrant biological material, which makes it difficult to obtain quality protein samples for proteomic analysis. This chapter focuses on protein extraction for gel- and LC-based proteomics with specific protocols of our current research with Botrytis cinerea.

Nutrigenomics: the cutting edge and Asian perspectives.

PubMed

Kato, Hisanori

2008-01-01

One of the two major goals of nutrigenomics is to make full use of genomic information to reveal how genetic variations affect nutrients and other food factors and thereby realize tailor-made nutrition (nutrigenetics). The other major goal of nutrigenomics is to comprehensively understand the response of the body to diets and food factors through various 'omics' technologies such as transcriptomics, proteomics, and metabolomics. The most successfully exploited technology to date is transcriptome analysis, due mainly to its efficiency and high-throughput feature. This technology has already provided a substantial amount of data on, for instance, the novel function of food factors, the unknown mechanism of the effect of nutrients, and even safety issues of foods. The nutrigenomics database that we have created now holds the publication data of several hundred of such 'omics' studies. Furthermore, the transcriptomics approach is being applied to food safety issues. For ex-ample, the data we have obtained thus far suggest that this new technology will facilitate the safety evaluation of newly developed foods and will help clarify the mechanism of toxic effects resulting from the excessive intake of a nutrient. The 'omics' data accumulated by our group and others strongly support the promise of the systems biology approach to food and nutrition science.

Comparison of Plasma Exosomes by Differential Ultracentrifugation and Solvent Precipitation Methods.

PubMed

Peng, Qiao; Zhang, Jing; Zhou, Gang

2018-06-01

Emerging evidence has identified that exosomes play a pivotal role in intercellular signal transmission. However, the standardized purification techniques to isolate high quality exosomes are still deficient at present. This study was to evaluate reproducibility and efficiency of differential ultracentrifugation and solvent precipitation-based kits by isolating plasma-derived exosomes from oral lichen planus patients. Morphology, exosomal biomarkers, particle size distribution, proteomic components, and protein yield of isolated exosomes were evaluated by transmission electron microscope, western blot, laser diffraction instrument, Coomassie staining, and BCA protein assay kit, respectively. TEM displayed representative cup-shaped morphology of exosomes and western blot identified exosomal biomarkers CD9 and CD63. The size distribution showed that particles by differential ultracentrifugation were mainly from 26.15 nm to 166.5 nm, while some of the particles obtained by solvent precipitation kits were larger than 1,000 nm. In addition, exosomes isolated by solvent precipitation kits showed a significantly higher amount of protein yield due to plasma albumin contamination. Both differential ultracentrifugation and precipitation based kits could successfully isolate plasma exosomes, and exosomes by differential ultracentrifugation were purer and more appropriate for further proteomic analysis.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Simulated linear test applied to quantitative proteomics.

PubMed

Pham, T V; Jimenez, C R

2016-09-01

Omics studies aim to find significant changes due to biological or functional perturbation. However, gene and protein expression profiling experiments contain inherent technical variation. In discovery proteomics studies where the number of samples is typically small, technical variation plays an important role because it contributes considerably to the observed variation. Previous methods place both technical and biological variations in tightly integrated mathematical models that are difficult to adapt for different technological platforms. Our aim is to derive a statistical framework that allows the inclusion of a wide range of technical variability. We introduce a new method called the simulated linear test, or the s-test, that is easy to implement and easy to adapt for different models of technical variation. It generates virtual data points from the observed values according to a pre-defined technical distribution and subsequently employs linear modeling for significance analysis. We demonstrate the flexibility of the proposed approach by deriving a new significance test for quantitative discovery proteomics for which missing values have been a major issue for traditional methods such as the t-test. We evaluate the result on two label-free (phospho) proteomics datasets based on ion-intensity quantitation. Available at http://www.oncoproteomics.nl/software/stest.html : t.pham@vumc.nl. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer.

PubMed

Song, Yimeng; Zhong, Lijun; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

2017-12-01

Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation. Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues. More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results. The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hands-on workshops as an effective means of learning advanced technologies including genomics, proteomics and bioinformatics.

PubMed

Reisdorph, Nichole; Stearman, Robert; Kechris, Katerina; Phang, Tzu Lip; Reisdorph, Richard; Prenni, Jessica; Erle, David J; Coldren, Christopher; Schey, Kevin; Nesvizhskii, Alexey; Geraci, Mark

2013-12-01

Genomics and proteomics have emerged as key technologies in biomedical research, resulting in a surge of interest in training by investigators keen to incorporate these technologies into their research. At least two types of training can be envisioned in order to produce meaningful results, quality publications and successful grant applications: (1) immediate short-term training workshops and (2) long-term graduate education or visiting scientist programs. We aimed to fill the former need by providing a comprehensive hands-on training course in genomics, proteomics and informatics in a coherent, experimentally-based framework. This was accomplished through a National Heart, Lung, and Blood Institute (NHLBI)-sponsored 10-day Genomics and Proteomics Hands-on Workshop held at National Jewish Health (NJH) and the University of Colorado School of Medicine (UCD). The course content included comprehensive lectures and laboratories in mass spectrometry and genomics technologies, extensive hands-on experience with instrumentation and software, video demonstrations, optional workshops, online sessions, invited keynote speakers, and local and national guest faculty. Here we describe the detailed curriculum and present the results of short- and long-term evaluations from course attendees. Our educational program consistently received positive reviews from participants and had a substantial impact on grant writing and review, manuscript submissions and publications. Copyright © 2013. Production and hosting by Elsevier Ltd.

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

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

Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Jacobs, Jon M.

2011-12-01

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If theymore » are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.« less

Implementation of statistical process control for proteomic experiments via LC MS/MS.

PubMed

Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J

2014-04-01

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

Knowledge Translation: Moving Proteomics Science to Innovation in Society.

PubMed

Holmes, Christina; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-06-01

Proteomics is one of the pivotal next-generation biotechnologies in the current "postgenomics" era. Little is known about the ways in which innovative proteomics science is navigating the complex socio-political space between laboratory and society. It cannot be assumed that the trajectory between proteomics laboratory and society is linear and unidirectional. Concerned about public accountability and hopes for knowledge-based innovations, funding agencies and citizens increasingly expect that emerging science and technologies, such as proteomics, are effectively translated and disseminated as innovation in society. Here, we describe translation strategies promoted in the knowledge translation (KT) and science communication literatures and examine the use of these strategies within the field of proteomics. Drawing on data generated from qualitative interviews with proteomics scientists and ethnographic observation of international proteomics conferences over a 5-year period, we found that proteomics science incorporates a variety of KT strategies to reach knowledge users outside the field. To attain the full benefit of KT, however, proteomics scientists must challenge their own normative assumptions and approaches to innovation dissemination-beyond the current paradigm relying primarily on publication for one's scientific peers within one's field-and embrace the value of broader (interdisciplinary) KT strategies in promoting the uptake of their research. Notably, the Human Proteome Organization (HUPO) is paying increasing attention to a broader range of KT strategies, including targeted dissemination, integrated KT, and public outreach. We suggest that increasing the variety of KT strategies employed by proteomics scientists is timely and would serve well the omics system sciences community.

Cycling transport safety quantification

NASA Astrophysics Data System (ADS)

Drbohlav, Jiri; Kocourek, Josef

2018-05-01

Dynamic interest in cycling transport brings the necessity to design safety cycling infrastructure. In las few years, couple of norms with safety elements have been designed and suggested for the cycling infrastructure. But these were not fully examined. The main parameter of suitable and fully functional transport infrastructure is the evaluation of its safety. Common evaluation of transport infrastructure safety is based on accident statistics. These statistics are suitable for motor vehicle transport but unsuitable for the cycling transport. Cycling infrastructure evaluation of safety is suitable for the traffic conflicts monitoring. The results of this method are fast, based on real traffic situations and can be applied on any traffic situations.

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study

DOE PAGES

Sun, Su; Xie, Shangxian; Cheng, Yanbing; ...

2017-09-12

Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level formore » the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.« less

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study.

PubMed

Sun, Su; Xie, Shangxian; Cheng, Yanbing; Yu, Hongbo; Zhao, Honglu; Li, Muzi; Li, Xiaotong; Zhang, Xiaoyu; Yuan, Joshua S; Dai, Susie Y

2017-09-12

Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level for the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.

Proteomic and Bioinformatic Profile of Primary Human Oral Epithelial Cells

PubMed Central

Ghosh, Santosh K.; Yohannes, Elizabeth; Bebek, Gurkan; Weinberg, Aaron; Jiang, Bin; Willard, Belinda; Chance, Mark R.; Kinter, Michael T.; McCormick, Thomas S.

2012-01-01

Wounding of the oral mucosa occurs frequently in a highly septic environment. Remarkably, these wounds heal quickly and the oral cavity, for the most part, remains healthy. Deciphering the normal human oral epithelial cell (NHOEC) proteome is critical for understanding the mechanism(s) of protection elicited when the mucosal barrier is intact, as well as when it is breached. Combining 2D gel electrophoresis with shotgun proteomics resulted in identification of 1662 NHOEC proteins. Proteome annotations were performed based on protein classes, molecular functions, disease association and membership in canonical and metabolic signaling pathways. Comparing the NHOEC proteome with a database of innate immunity-relevant interactions (InnateDB) identified 64 common proteins associated with innate immunity. Comparison with published salivary proteomes revealed that 738/1662 NHOEC proteins were common, suggesting that significant numbers of salivary proteins are of epithelial origin. Gene ontology analysis showed similarities in the distributions of NHOEC and saliva proteomes with regard to biological processes, and molecular functions. We also assessed the inter-individual variability of the NHOEC proteome and observed it to be comparable with other primary cells. The baseline proteome described in this study should serve as a resource for proteome studies of the oral mucosa, especially in relation to disease processes. PMID:23035736

Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study

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

Sun, Su; Xie, Shangxian; Cheng, Yanbing

Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level formore » the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.« less

Making proteomics data accessible and reusable: current state of proteomics databases and repositories.

PubMed

Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-03-01

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Smoke-induced microRNA and related proteome alterations. Modulation by chemopreventive agents.

PubMed

De Flora, Silvio; Balansky, Roumen; D'Agostini, Francesco; Cartiglia, Cristina; Longobardi, Mariagrazia; Steele, Vernon E; Izzotti, Alberto

2012-12-15

Dysregulation of microRNAs (miRNAs) has important consequences on gene and protein expression since a single miRNA targets a number of genes simultaneously. This article provides a review of published data and ongoing studies regarding the effects of cigarette smoke (CS), either mainstream (MCS) or environmental (ECS), on the expression of miRNAs and related proteins. The results generated in mice, rats, and humans provided evidence that exposure to CS results in an intense dysregulation of miRNA expression in the respiratory tract, which is mainly oriented in the sense of downregulation. In parallel, there was an upregulation of proteins targeted by the downregulated miRNAs. These trends reflect an attempt to defend the respiratory tract by means of antioxidant mechanisms, detoxification of carcinogens, DNA repair, anti-inflammatory pathways, apoptosis, etc. However, a long-lasting exposure to CS causes irreversible miRNA alterations that activate carcinogenic mechanisms, such as modulation of oncogenes and oncosuppressor genes, cell proliferation, recruitment of undifferentiated stem cells, inflammation, inhibition of intercellular communications, angiogenesis, invasion, and metastasis. The miRNA alterations induced by CS in the lung of mice and rats are similar to those observed in the human respiratory tract. Since a number of miRNAs that are modulated by CS and/or chemopreventive agents are subjected to single nucleotide polymorphisms in humans, they can be evaluated according to toxicogenomic/pharmacogenomics approaches. A variety of cancer chemopreventive agents tested in our laboratory modulated both baseline and CS-related miRNA and proteome alterations, thus contributing to evaluate both safety and efficacy of dietary and pharmacological agents. Copyright © 2012 UICC.

Making proteomics data accessible and reusable: Current state of proteomics databases and repositories

PubMed Central

Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-01-01

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. PMID:25158685

The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature

PubMed Central

Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey

2016-01-01

Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395

Advances in microscale separations towards nanoproteomics applications

DOE PAGES

Yi, Lian; Piehowski, Paul D.; Shi, Tujin; ...

2017-07-21

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

Advances in microscale separations towards nanoproteomics applications

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

Yi, Lian; Piehowski, Paul D.; Shi, Tujin

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

The HUPO proteomics standards initiative--overcoming the fragmentation of proteomics data.

PubMed

Hermjakob, Henning

2006-09-01

Proteomics is a key field of modern biomolecular research, with many small and large scale efforts producing a wealth of proteomics data. However, the vast majority of this data is never exploited to its full potential. Even in publicly funded projects, often the raw data generated in a specific context is analysed, conclusions are drawn and published, but little attention is paid to systematic documentation, archiving, and public access to the data supporting the scientific results. It is often difficult to validate the results stated in a particular publication, and even simple global questions like "In which cellular contexts has my protein of interest been observed?" can currently not be answered with realistic effort, due to a lack of standardised reporting and collection of proteomics data. The Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organisation (HUPO), defines community standards for data representation in proteomics to facilitate systematic data capture, comparison, exchange and verification. In this article we provide an overview of PSI organisational structure, activities, and current results, as well as ways to get involved in the broad-based, open PSI process.

Proteomics in medical microbiology.

PubMed

Cash, P

2000-04-01

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.

YPED: An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

PubMed Central

Colangelo, Christopher M.; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L.; Carriero, Nicholas J.; Gulcicek, Erol E.; Lam, TuKiet T.; Wu, Terence; Bjornson, Robert D.; Bruce, Can; Nairn, Angus C.; Rinehart, Jesse; Miller, Perry L.; Williams, Kenneth R.

2015-01-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. PMID:25712262

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

PubMed

Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R

2015-02-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

A Study on Urban Road Traffic Safety Based on Matter Element Analysis

PubMed Central

Hu, Qizhou; Zhou, Zhuping; Sun, Xu

2014-01-01

This paper examines a new evaluation of urban road traffic safety based on a matter element analysis, avoiding the difficulties found in other traffic safety evaluations. The issue of urban road traffic safety has been investigated through the matter element analysis theory. The chief aim of the present work is to investigate the features of urban road traffic safety. Emphasis was placed on the construction of a criterion function by which traffic safety achieved a hierarchical system of objectives to be evaluated. The matter element analysis theory was used to create the comprehensive appraisal model of urban road traffic safety. The technique was used to employ a newly developed and versatile matter element analysis algorithm. The matter element matrix solves the uncertainty and incompatibility of the evaluated factors used to assess urban road traffic safety. The application results showed the superiority of the evaluation model and a didactic example was included to illustrate the computational procedure. PMID:25587267

Elucidation of salt stress defense and tolerance mechanisms of crop plants using proteomics--current achievements and perspectives.

PubMed

Barkla, Bronwyn J; Castellanos-Cervantes, Thelma; de León, José L Diaz; Matros, Andrea; Mock, Hans-Peter; Perez-Alfocea, Francisco; Salekdeh, Ghasem H; Witzel, Katja; Zörb, Christian

2013-06-01

Salinity is a major threat limiting the productivity of crop plants. A clear demand for improving the salinity tolerance of the major crop plants is imposed by the rapidly growing world population. This review summarizes the achievements of proteomic studies to elucidate the response mechanisms of selected model and crop plants to cope with salinity stress. We also aim at identifying research areas, which deserve increased attention in future proteome studies, as a prerequisite to identify novel targets for breeding strategies. Such areas include the impact of plant-microbial communities on the salinity tolerance of crops under field conditions, the importance of hormone signaling in abiotic stress tolerance, and the significance of control mechanisms underlying the observed changes in the proteome patterns. We briefly highlight the impact of novel tools for future proteome studies and argue for the use of integrated approaches. The evaluation of genetic resources by means of novel automated phenotyping facilities will have a large impact on the application of proteomics especially in combination with metabolomics or transcriptomics. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Activity-based protein profiling: from enzyme chemistry to proteomic chemistry.

PubMed

Cravatt, Benjamin F; Wright, Aaron T; Kozarich, John W

2008-01-01

Genome sequencing projects have provided researchers with a complete inventory of the predicted proteins produced by eukaryotic and prokaryotic organisms. Assignment of functions to these proteins represents one of the principal challenges for the field of proteomics. Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale. Here, we review the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.

Proteomics Perspectives in Rotator Cuff Research: A Systematic Review of Gene Expression and Protein Composition in Human Tendinopathy

PubMed Central

Sejersen, Maria Hee Jung; Frost, Poul; Hansen, Torben Bæk; Deutch, Søren Rasmussen; Svendsen, Susanne Wulff

2015-01-01

Background Rotator cuff tendinopathy including tears is a cause of significant morbidity. The molecular pathogenesis of the disorder is largely unknown. This review aimed to present an overview of the literature on gene expression and protein composition in human rotator cuff tendinopathy and other tendinopathies, and to evaluate perspectives of proteomics – the comprehensive study of protein composition - in tendon research. Materials and Methods We conducted a systematic search of the literature published between 1 January 1990 and 18 December 2012 in PubMed, Embase, and Web of Science. We included studies on objectively quantified differential gene expression and/or protein composition in human rotator cuff tendinopathy and other tendinopathies as compared to control tissue. Results We identified 2199 studies, of which 54 were included; 25 studies focussed on rotator cuff or biceps tendinopathy. Most of the included studies quantified prespecified mRNA molecules and proteins using polymerase chain reactions and immunoassays, respectively. There was a tendency towards an increase of collagen I (11 of 15 studies) and III (13 of 14), metalloproteinase (MMP)-1 (6 of 12), -9 (7 of 7), -13 (4 of 7), tissue inhibitor of metalloproteinase (TIMP)-1 (4 of 7), and vascular endothelial growth factor (4 of 7), and a decrease in MMP-3 (10 of 12). Fourteen proteomics studies of tendon tissues/cells failed inclusion, mostly because they were conducted in animals or in vitro. Conclusions Based on methods, which only allowed simultaneous quantification of a limited number of prespecified mRNA molecules or proteins, several proteins appeared to be differentially expressed/represented in rotator cuff tendinopathy and other tendinopathies. No proteomics studies fulfilled our inclusion criteria, although proteomics technologies may be a way to identify protein profiles (including non-prespecified proteins) that characterise specific tendon disorders or stages of tendinopathy. Thus, our results suggested an untapped potential for proteomics in tendon research. PMID:25879758

Proteomics perspectives in rotator cuff research: a systematic review of gene expression and protein composition in human tendinopathy.

PubMed

Sejersen, Maria Hee Jung; Frost, Poul; Hansen, Torben Bæk; Deutch, Søren Rasmussen; Svendsen, Susanne Wulff

2015-01-01

Rotator cuff tendinopathy including tears is a cause of significant morbidity. The molecular pathogenesis of the disorder is largely unknown. This review aimed to present an overview of the literature on gene expression and protein composition in human rotator cuff tendinopathy and other tendinopathies, and to evaluate perspectives of proteomics--the comprehensive study of protein composition--in tendon research. We conducted a systematic search of the literature published between 1 January 1990 and 18 December 2012 in PubMed, Embase, and Web of Science. We included studies on objectively quantified differential gene expression and/or protein composition in human rotator cuff tendinopathy and other tendinopathies as compared to control tissue. We identified 2199 studies, of which 54 were included; 25 studies focussed on rotator cuff or biceps tendinopathy. Most of the included studies quantified prespecified mRNA molecules and proteins using polymerase chain reactions and immunoassays, respectively. There was a tendency towards an increase of collagen I (11 of 15 studies) and III (13 of 14), metalloproteinase (MMP)-1 (6 of 12), -9 (7 of 7), -13 (4 of 7), tissue inhibitor of metalloproteinase (TIMP)-1 (4 of 7), and vascular endothelial growth factor (4 of 7), and a decrease in MMP-3 (10 of 12). Fourteen proteomics studies of tendon tissues/cells failed inclusion, mostly because they were conducted in animals or in vitro. Based on methods, which only allowed simultaneous quantification of a limited number of prespecified mRNA molecules or proteins, several proteins appeared to be differentially expressed/represented in rotator cuff tendinopathy and other tendinopathies. No proteomics studies fulfilled our inclusion criteria, although proteomics technologies may be a way to identify protein profiles (including non-prespecified proteins) that characterise specific tendon disorders or stages of tendinopathy. Thus, our results suggested an untapped potential for proteomics in tendon research.

Quantitative proteomics in the field of microbiology.

PubMed

Otto, Andreas; Becher, Dörte; Schmidt, Frank

2014-03-01

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent advances in proteomics of cereals.

PubMed

Bansal, Monika; Sharma, Madhu; Kanwar, Priyanka; Goyal, Aakash

Cereals contribute a major part of human nutrition and are considered as an integral source of energy for human diets. With genomic databases already available in cereals such as rice, wheat, barley, and maize, the focus has now moved to proteome analysis. Proteomics studies involve the development of appropriate databases based on developing suitable separation and purification protocols, identification of protein functions, and can confirm their functional networks based on already available data from other sources. Tremendous progress has been made in the past decade in generating huge data-sets for covering interactions among proteins, protein composition of various organs and organelles, quantitative and qualitative analysis of proteins, and to characterize their modulation during plant development, biotic, and abiotic stresses. Proteomics platforms have been used to identify and improve our understanding of various metabolic pathways. This article gives a brief review of efforts made by different research groups on comparative descriptive and functional analysis of proteomics applications achieved in the cereal science so far.

Quantitative Analysis of Global Proteome and Lysine Acetylome Reveal the Differential Impacts of VPA and SAHA on HL60 Cells.

PubMed

Zhu, Xiaoyu; Liu, Xin; Cheng, Zhongyi; Zhu, Jun; Xu, Lei; Wang, Fengsong; Qi, Wulin; Yan, Jiawei; Liu, Ning; Sun, Zimin; Liu, Huilan; Peng, Xiaojun; Hao, Yingchan; Zheng, Nan; Wu, Quan

2016-01-29

Valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA) are both HDAC inhibitors (HDACi). Previous studies indicated that both inhibitors show therapeutic effects on acute myeloid leukaemia (AML), while the differential impacts of the two different HDACi on AML treatment still remains elusive. In this study, using 3-plex SILAC based quantitative proteomics technique, anti-acetyllysine antibody based affinity enrichment, high resolution LC-MS/MS and intensive bioinformatic analysis, the quantitative proteome and acetylome in SAHA and VPA treated AML HL60 cells were extensively studied. In total, 5,775 proteins and 1,124 lysine acetylation sites were successfully obtained in response to VAP and SAHA treatment. It is found that VPA and SAHA treatment differently induced proteome and acetylome profiling in AML HL60 cells. This study revealed the differential impacts of VPA and SAHA on proteome/acetylome in AML cells, deepening our understanding of HDAC inhibitor mediated AML therapeutics.

Plant proteomics in India and Nepal: current status and challenges ahead.

PubMed

Deswal, Renu; Gupta, Ravi; Dogra, Vivek; Singh, Raksha; Abat, Jasmeet Kaur; Sarkar, Abhijit; Mishra, Yogesh; Rai, Vandana; Sreenivasulu, Yelam; Amalraj, Ramesh Sundar; Raorane, Manish; Chaudhary, Ram Prasad; Kohli, Ajay; Giri, Ashok Prabhakar; Chakraborty, Niranjan; Zargar, Sajad Majeed; Agrawal, Vishwanath Prasad; Agrawal, Ganesh Kumar; Job, Dominique; Renaut, Jenny; Rakwal, Randeep

2013-10-01

Plant proteomics has made tremendous contributions in understanding the complex processes of plant biology. Here, its current status in India and Nepal is discussed. Gel-based proteomics is predominantly utilized on crops and non-crops to analyze majorly abiotic (49 %) and biotic (18 %) stress, development (11 %) and post-translational modifications (7 %). Rice is the most explored system (36 %) with major focus on abiotic mainly dehydration (36 %) stress. In spite of expensive proteomics setup and scarcity of trained workforce, output in form of publications is encouraging. To boost plant proteomics in India and Nepal, researchers have discussed ground level issues among themselves and with the International Plant Proteomics Organization (INPPO) to act in priority on concerns like food security. Active collaboration may help in translating this knowledge to fruitful applications.

Analysis of the efficacy of Taiwanese freeze-dried neurotoxic antivenom against Naja kaouthia, Naja siamensis and Ophiophagus hannah through proteomics and animal model approaches.

PubMed

Liu, Chien-Chun; You, Chen-Hsien; Wang, Po-Jung; Yu, Jau-Song; Huang, Guo-Jen; Liu, Chien-Hsin; Hsieh, Wen-Chin; Lin, Chih-Chuan

2017-12-01

In Southeast Asia, envenoming resulting from cobra snakebites is an important public health issue in many regions, and antivenom therapy is the standard treatment for the snakebite. Because these cobras share a close evolutionary history, the amino acid sequences of major venom components in different snakes are very similar. Therefore, either monovalent or polyvalent antivenoms may offer paraspecific protection against envenomation of humans by several different snakes. In Taiwan, a bivalent antivenom-freeze-dried neurotoxic antivenom (FNAV)-against Bungarus multicinctus and Naja atra is available. However, whether this antivenom is also capable of neutralizing the venom of other species of snakes is not known. Here, to expand the clinical application of Taiwanese FNAV, we used an animal model to evaluate the neutralizing ability of FNAV against the venoms of three common snakes in Southeast Asia, including two 'true' cobras Naja kaouthia (Thailand) and Naja siamensis (Thailand), and the king cobra Ophiophagus hannah (Indonesia). We further applied mass spectrometry (MS)-based proteomic techniques to characterize venom proteomes and identify FNAV-recognizable antigens in the venoms of these Asian snakes. Neutralization assays in a mouse model showed that FNAV effectively neutralized the lethality of N. kaouthia and N. siamensis venoms, but not O. hannah venom. MS-based venom protein identification results further revealed that FNAV strongly recognized three-finger toxin and phospholipase A2, the major protein components of N. kaouthia and N. siamensis venoms. The characterization of venom proteomes and identification of FNAV-recognizable venom antigens may help researchers to further develop more effective antivenom designed to block the toxicity of dominant toxic proteins, with the ultimate goal of achieving broadly therapeutic effects against these cobra snakebites.

Comparative proteomic analysis of fibrotic liver of rats fed high fat diet contained lard versus corn oil.

PubMed

Wang, Hualin; Sit, Wat-Hung; Tipoe, George Lim; Liu, Zhiguo; Wan, Jennifer Man-Fan

2017-02-01

The influences of dietary fatty acids on the progress of chronic liver diseases have attracted lots of attentions, but the mechanisms of the effects of lipids rich in saturated fatty acids or PUFAs on hepatic fibrogenesis remain unclear. Female Fischer 344 rats were fed normal chow or chow plus 20% (w/w) of corn oil or lard, respectively, and injected CCl 4 twice a week for 4 weeks to induce liver fibrosis. Masson's staining was adopted to illustrate the fibrosis level. The mRNA expression level of α-SMA and the DNA methylation level of its promoter region were analyzed. A 2-DE gel based proteomic approach was constructed to investigate the differential expression level of hepatic proteome between three diet groups. Histological evaluations and α-SMA expression analysis illustrated the high corn oil intake has no effects on hepatic fibrogenesis, but lard intake aggravated liver fibrosis, partly attributed to DNA demethylation of α-SMA promoter region. 2-DE Gel based proteomic study demonstrated excessive lard consumption elevated the expression of fibrosis related alpha-1-antitrypsin precursor, and endoplasmic reticulum stress related proteins such as heat shock cognate 71 kDa, eukaryotic translation initiation factor 4A1 and protein disulfide isomerase associated 3. Moreover, unlike corn oil rich in PUFAs, lard had no effects to elevate the expression of glutathione S-transferases, but decreased the expression of iron store related proteins heme binding protein 1 and ferritin. Lard intake aggravates CCl 4 induced liver fibrosis via enhancing the expression of fibrogenesis and ER stress related proteins, and disturbing the hepatic transmethylation reaction. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

NCI, NHLBI, FDA, AACC, and CMS Collaborate in Advancing Proteomics Regulatory Science | Office of Cancer Clinical Proteomics Research

Cancer.gov

Despite great strides in proteomics and the growing number of articles citing the discovery of potential biomarkers, the actual rate of introduction of Food and Drug Administration (FDA) approved protein analytes has been relatively unchanged over the past 10 years. One of reasons for the lack of new protein-based biomarkers approved has been a lack of information and understanding by the proteomics research community to the regulatory process used by the FDA. To address this issue, Dr.

Analysis of the variability of human normal urine by 2D-GE reveals a "public" and a "private" proteome.

PubMed

Molina, Laurence; Salvetat, Nicolas; Ameur, Randa Ben; Peres, Sabine; Sommerer, Nicolas; Jarraya, Fayçal; Ayadi, Hammadi; Molina, Franck; Granier, Claude

2011-12-10

The characterization of the normal urinary proteome is steadily progressing and represents a major interest in the assessment of clinical urinary biomarkers. To estimate quantitatively the variability of the normal urinary proteome, urines of 20 healthy people were collected. We first evaluated the impact of the sample conservation temperature on urine proteome integrity. Keeping the urine sample at RT or at +4°C until storage at -80°C seems the best way for long-term storage of samples for 2D-GE analysis. The quantitative variability of the normal urinary proteome was estimated on the 20 urines mapped by 2D-GE. The occurrence of the 910 identified spots was analysed throughout the gels and represented in a virtual 2D gel. Sixteen percent of the spots were found to occur in all samples and 23% occurred in at least 90% of urines. About 13% of the protein spots were present only in 10% or less of the samples, thus representing the most variable part of the normal urinary proteome. Twenty proteins corresponding to a fraction of the fully conserved spots were identified by mass spectrometry. In conclusion, a "public" urinary proteome, common to healthy individuals, seems to coexist with a "private" urinary proteome, which is more specific to each individual. Copyright © 2011 Elsevier B.V. All rights reserved.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

PubMed

Lindsey, Merry L; Mayr, Manuel; Gomes, Aldrin V; Delles, Christian; Arrell, D Kent; Murphy, Anne M; Lange, Richard A; Costello, Catherine E; Jin, Yu-Fang; Laskowitz, Daniel T; Sam, Flora; Terzic, Andre; Van Eyk, Jennifer; Srinivas, Pothur R

2015-09-01

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings. © 2015 American Heart Association, Inc.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

Mining for Microbial Gems: Integrating Proteomics in the Postgenomic Natural Product Discovery Pipeline.

PubMed

Du, Chao; van Wezel, Gilles P

2018-04-30

Natural products (NPs) are a major source of compounds for medical, agricultural, and biotechnological industries. Many of these compounds are of microbial origin, and, in particular, from Actinobacteria or filamentous fungi. To successfully identify novel compounds that correlate to a bioactivity of interest, or discover new enzymes with desired functions, systematic multiomics approaches have been developed over the years. Bioinformatics tools harness the rapidly expanding wealth of genome sequence information, revealing previously unsuspected biosynthetic diversity. Varying growth conditions or application of elicitors are applied to activate cryptic biosynthetic gene clusters, and metabolomics provide detailed insights into the NPs they specify. Combining these technologies with proteomics-based approaches to profile the biosynthetic enzymes provides scientists with insights into the full biosynthetic potential of microorganisms. The proteomics approaches include enrichment strategies such as employing activity-based probes designed by chemical biology, as well as unbiased (quantitative) proteomics methods. In this review, the opportunities and challenges in microbial NP research are discussed, and, in particular, the application of proteomics to link biosynthetic enzymes to the molecules they produce, and vice versa. © 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simple Sodium Dodecyl Sulfate-Assisted Sample Preparation Method for LC-MS-based Proteomic Applications

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

Zhou, Jianying; Dann, Geoffrey P.; Shi, Tujin

2012-03-10

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for highly efficient biological sample extraction; however, SDS presents a significant challenge to LC-MS-based proteomic analyses due to its severe interference with reversed-phase LC separations and electrospray ionization interfaces. This study reports a simple SDS-assisted proteomic sample preparation method facilitated by a novel peptide-level SDS removal protocol. After SDS-assisted protein extraction and digestion, SDS was effectively (>99.9%) removed from peptides through ion substitution-mediated DS- precipitation with potassium chloride (KCl) followed by {approx}10 min centrifugation. Excellent peptide recovery (>95%) was observed for less than 20 {mu}g of peptides.more » Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage from this SDS-assisted protocol was comparable to or better than those obtained from other standard proteomic preparation methods in both mammalian tissues and bacterial samples. These results suggest that this SDS-assisted protocol is a practical, simple, and broadly applicable proteomic sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.« less

Combining genomic and proteomic approaches for epigenetics research

PubMed Central

Han, Yumiao; Garcia, Benjamin A

2014-01-01

Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656

Proteomic evaluation of milk from different mammalian species as a substitute for breast milk.

PubMed

D'Auria, Enza; Agostoni, Carlo; Giovannini, Marcello; Riva, Enrica; Zetterström, Rolf; Fortin, Riccardo; Greppi, Gian Franco; Bonizzi, Luigi; Roncada, Paola

2005-12-01

As milk represents the main source of nutrition for infants, the question of an effective human milk substitute becomes mandatory when a formula-fed baby is allergic to cows' milk proteins. In this case, formulas containing extensively hydrolysed milk proteins should be preferred, but even such a formula may cause allergic reactions in highly sensitive patients. If there is evidence of cows' milk allergy with IgE-associated symptoms, after 6 mo of age, a soy bean formula may be recommended only when tolerance to soy protein has been established by clinical challenge. In infants with allergic reactions to cows' milk proteins, even after extensive hydrolyzation, proteomic techniques coupled to immunological methods may make it possible to select other milk products that do not contain the same allergens as ordinary cow's milk. In this paper, evidence will be presented that proteomic evaluation of proteins from different mammalian species may be a suitable method of testing whether proteins from the milk of different mammalian species may be used as a substitute for untreated bovine milk. Proteomic evaluation of milk from different mammalian species may not only be of help when recommending suitable feeding in cases of cows' milk allergy but also gives new insight into the background to allergic reactions caused by milk proteins.

Dentistry proteomics: from laboratory development to clinical practice.

PubMed

Rezende, Taia M B; Lima, Stella M F; Petriz, Bernardo A; Silva, Osmar N; Freire, Mirna S; Franco, Octávio L

2013-12-01

Despite all the dental information acquired over centuries and the importance of proteome research, the cross-link between these two areas only emerged around mid-nineties. Proteomic tools can help dentistry in the identification of risk factors, early diagnosis, prevention, and systematic control that will promote the evolution of treatment in all dentistry specialties. This review mainly focuses on the evolution of dentistry in different specialties based on proteomic research and how these tools can improve knowledge in dentistry. The subjects covered are an overview of proteomics in dentistry, specific information on different fields in dentistry (dental structure, restorative dentistry, endodontics, periodontics, oral pathology, oral surgery, and orthodontics) and future directions. There are many new proteomic technologies that have never been used in dentistry studies and some dentistry areas that have never been explored by proteomic tools. It is expected that a greater integration of these areas will help to understand what is still unknown in oral health and disease. Copyright © 2013 Wiley Periodicals, Inc.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

NASA Astrophysics Data System (ADS)

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-06-01

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

PubMed Central

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-01-01

Mass spectrometry–based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications. PMID:27049631

Evaluation of Drosophila metabolic labeling strategies for in vivo quantitative proteomic analyses with applications to early pupa formation and amino acid starvation.

PubMed

Chang, Ying-Che; Tang, Hong-Wen; Liang, Suh-Yuen; Pu, Tsung-Hsien; Meng, Tzu-Ching; Khoo, Kay-Hooi; Chen, Guang-Chao

2013-05-03

Although stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics was first developed as a cell culture-based technique, stable isotope-labeled amino acids have since been successfully introduced in vivo into select multicellular model organisms by manipulating the feeding diets. An earlier study by others has demonstrated that heavy lysine labeled Drosophila melanogaster can be derived by feeding with an exclusive heavy lysine labeled yeast diet. In this work, we have further evaluated the use of heavy lysine and/or arginine for metabolic labeling of fruit flies, with an aim to determine its respective quantification accuracy and versatility. In vivo conversion of heavy lysine and/or heavy arginine to several nonessential amino acids was observed in labeled flies, leading to distorted isotope pattern and underestimated heavy to light ratio. These quantification defects can nonetheless be rectified at protein level using the normalization function. The only caveat is that such a normalization strategy may not be suitable for every biological application, particularly when modified peptides need to be individually quantified at peptide level. In such cases, we showed that peptide ratios calculated from the summed intensities of all isotope peaks are less affected by the heavy amino acid conversion and therefore less sequence-dependent and more reliable. Applying either the single Lys8 or double Lys6/Arg10 metabolic labeling strategy to flies, we quantitatively mapped the proteomic changes during the onset of metamorphosis and upon amino acid deprivation. The expression of a number of steroid hormone 20-hydroxyecdysone regulated proteins was found to be changed significantly during larval-pupa transition, while several subunits of the V-ATPase complex and components regulating actomyosin were up-regulated under starvation-induced autophagy conditions.

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

Liu, Xing; Xu, Yanli; Meng, Qian

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP andmore » NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.« less

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

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

Mu, Jun; Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing; Chongqing Key Laboratory of Neurobiology, Chongqing

Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology andmore » proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of ApoB gives insights into the pathogenesis of TBM.« less

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

The Impact II, a Very High-Resolution Quadrupole Time-of-Flight Instrument (QTOF) for Deep Shotgun Proteomics*

PubMed Central

Beck, Scarlet; Michalski, Annette; Raether, Oliver; Lubeck, Markus; Kaspar, Stephanie; Goedecke, Niels; Baessmann, Carsten; Hornburg, Daniel; Meier, Florian; Paron, Igor; Kulak, Nils A.; Cox, Juergen; Mann, Matthias

2015-01-01

Hybrid quadrupole time-of-flight (QTOF) mass spectrometry is one of the two major principles used in proteomics. Although based on simple fundamentals, it has over the last decades greatly evolved in terms of achievable resolution, mass accuracy, and dynamic range. The Bruker impact platform of QTOF instruments takes advantage of these developments and here we develop and evaluate the impact II for shotgun proteomics applications. Adaption of our heated liquid chromatography system achieved very narrow peptide elution peaks. The impact II is equipped with a new collision cell with both axial and radial ion ejection, more than doubling ion extraction at high tandem MS frequencies. The new reflectron and detector improve resolving power compared with the previous model up to 80%, i.e. to 40,000 at m/z 1222. We analyzed the ion current from the inlet capillary and found very high transmission (>80%) up to the collision cell. Simulation and measurement indicated 60% transfer into the flight tube. We adapted MaxQuant for QTOF data, improving absolute average mass deviations to better than 1.45 ppm. More than 4800 proteins can be identified in a single run of HeLa digest in a 90 min gradient. The workflow achieved high technical reproducibility (R2 > 0.99) and accurate fold change determination in spike-in experiments in complex mixtures. Using label-free quantification we rapidly quantified haploid against diploid yeast and characterized overall proteome differences in mouse cell lines originating from different tissues. Finally, after high pH reversed-phase fractionation we identified 9515 proteins in a triplicate measurement of HeLa peptide mixture and 11,257 proteins in single measurements of cerebellum—the highest proteome coverage reported with a QTOF instrument so far. PMID:25991688

Mitochondrial proteome disruption in the diabetic heart through targeted epigenetic regulation at the mitochondrial heat shock protein 70 (mtHsp70) nuclear locus.

PubMed

Shepherd, Danielle L; Hathaway, Quincy A; Nichols, Cody E; Durr, Andrya J; Pinti, Mark V; Hughes, Kristen M; Kunovac, Amina; Stine, Seth M; Hollander, John M

2018-06-01

>99% of the mitochondrial proteome is nuclear-encoded. The mitochondrion relies on a coordinated multi-complex process for nuclear genome-encoded mitochondrial protein import. Mitochondrial heat shock protein 70 (mtHsp70) is a key component of this process and a central constituent of the protein import motor. Type 2 diabetes mellitus (T2DM) disrupts mitochondrial proteomic signature which is associated with decreased protein import efficiency. The goal of this study was to manipulate the mitochondrial protein import process through targeted restoration of mtHsp70, in an effort to restore proteomic signature and mitochondrial function in the T2DM heart. A novel line of cardiac-specific mtHsp70 transgenic mice on the db/db background were generated and cardiac mitochondrial subpopulations were isolated with proteomic evaluation and mitochondrial function assessed. MicroRNA and epigenetic regulation of the mtHsp70 gene during T2DM were also evaluated. MtHsp70 overexpression restored cardiac function and nuclear-encoded mitochondrial protein import, contributing to a beneficial impact on proteome signature and enhanced mitochondrial function during T2DM. Further, transcriptional repression at the mtHsp70 genomic locus through increased localization of H3K27me3 during T2DM insult was observed. Our results suggest that restoration of a key protein import constituent, mtHsp70, provides therapeutic benefit through attenuation of mitochondrial and contractile dysfunction in T2DM. Copyright © 2018 Elsevier Ltd. All rights reserved.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525

NITPICK: peak identification for mass spectrometry data.

PubMed

Renard, Bernhard Y; Kirchner, Marc; Steen, Hanno; Steen, Judith A J; Hamprecht, Fred A

2008-08-28

The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments. This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on fractional averaging, a novel extension to Senko's well-known averaging model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra. Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from (http://hci.iwr.uni-heidelberg.de/mip/proteomics/).

A gel-free proteomic-based method for the characterization of Bordetella pertussis clinical isolates

PubMed Central

Williamson, Yulanda M.; Moura, Hercules; Simmons, Kaneatra; Whitmon, Jennifer; Melnick, Nikkol; Rees, Jon; Woolfitt, Adrian; Schieltz, David M.; Tondella, Maria L.; Ades, Edwin; Sampson, Jacquelyn; Carlone, George; Barr, John R.

2017-01-01

Bordetella pertussis (Bp) is the etiologic agent of pertussis or whooping cough, a highly contagious respiratory disease occurring primarily in infants and young children. Although vaccine preventable, pertussis cases have increased over the years leading researchers to re-evaluate vaccine control strategies. Since bacterial outer membrane proteins, comprising the surfaceome, often play roles in pathogenesis and antibody-mediated immunity, three recent Bp circulating isolates were examined using proteomics to identify any potential changes in surface protein expression. Fractions enriched for outer membrane proteins were digested with trypsin and the peptides analyzed by nano liquid chromatography-electrospray ionization-mass spectrometry (nLC-ESI-MS), followed by database analysis to elucidate the surfaceomes of our three Bp isolates. Furthermore, a less labor intensive non-gel based antibody affinity capture technology in conjunction with MS was employed to assess each Bp strains' immunogenic outer membrane proteins. This novel technique is generally applicable allowing for the identification of immunogenic surface expressed proteins on pertussis and other pathogenic bacteria. PMID:22537821

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

PubMed

Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

2012-12-01

To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

A root cause analysis project in a medication safety course.

PubMed

Schafer, Jason J

2012-08-10

To develop, implement, and evaluate team-based root cause analysis projects as part of a required medication safety course for second-year pharmacy students. Lectures, in-class activities, and out-of-class reading assignments were used to develop students' medication safety skills and introduce them to the culture of medication safety. Students applied these skills within teams by evaluating cases of medication errors using root cause analyses. Teams also developed error prevention strategies and formally presented their findings. Student performance was assessed using a medication errors evaluation rubric. Of the 211 students who completed the course, the majority performed well on root cause analysis assignments and rated them favorably on course evaluations. Medication error evaluation and prevention was successfully introduced in a medication safety course using team-based root cause analysis projects.

Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML database--Xindice.

PubMed

Li, Feng; Li, Maoyu; Xiao, Zhiqiang; Zhang, Pengfei; Li, Jianling; Chen, Zhuchu

2006-01-11

Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database. The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database. Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at http://www.xyproteomics.org/.

Astragaloside IV Attenuates Glutamate-Induced Neurotoxicity in PC12 Cells through Raf-MEK-ERK Pathway.

PubMed

Yue, Rongcai; Li, Xia; Chen, Bingyang; Zhao, Jing; He, Weiwei; Yuan, Hu; Yuan, Xing; Gao, Na; Wu, Guozhen; Jin, Huizi; Shan, Lei; Zhang, Weidong

2015-01-01

Astragaloside IV (AGS-IV) is a main active ingredient of Astragalus membranaceus Bunge, a medicinal herb prescribed as an immunostimulant, hepatoprotective, antiperspirant, a diuretic or a tonic as documented in Chinese Materia Medica. In the present study, we employed a high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS to investigate the possible mechanism of action involved in the neuroprotective effect of AGS-IV against glutamate-induced neurotoxicity in PC12 cells. Differential proteins were identified, among which 13 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (vimentin and Gap43) were randomly selected, and their expression levels were further confirmed by western blots analysis. The results matched well with those of proteomics. Furthermore, network analysis of protein-protein interactions (PPI) and pathways enrichment with AGS-IV associated proteins were carried out to illustrate its underlying molecular mechanism. Proteins associated with signal transduction, immune system, signaling molecules and interaction, and energy metabolism play important roles in neuroprotective effect of AGS-IV and Raf-MEK-ERK pathway was involved in the neuroprotective effect of AGS-IV against glutamate-induced neurotoxicity in PC12 cells. This study demonstrates that comparative proteomics based on shotgun approach is a valuable tool for molecular mechanism studies, since it allows the simultaneously evaluate the global proteins alterations.

P2P proteomics -- data sharing for enhanced protein identification

PubMed Central

2012-01-01

Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories. PMID:22293032

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Proteomics data repositories: Providing a safe haven for your data and acting as a springboard for further research

PubMed Central

Vizcaíno, Juan Antonio; Foster, Joseph M.; Martens, Lennart

2010-01-01

Despite the fact that data deposition is not a generalised fact yet in the field of proteomics, several mass spectrometry (MS) based proteomics repositories are publicly available for the scientific community. The main existing resources are: the Global Proteome Machine Database (GPMDB), PeptideAtlas, the PRoteomics IDEntifications database (PRIDE), Tranche, and NCBI Peptidome. In this review the capabilities of each of these will be described, paying special attention to four key properties: data types stored, applicable data submission strategies, supported formats, and available data mining and visualization tools. Additionally, the data contents from model organisms will be enumerated for each resource. There are other valuable smaller and/or more specialized repositories but they will not be covered in this review. Finally, the concept behind the ProteomeXchange consortium, a collaborative effort among the main resources in the field, will be introduced. PMID:20615486

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

PubMed

Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

2016-01-01

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Proteome studies of filamentous fungi.

PubMed

Baker, Scott E; Panisko, Ellen A

2011-01-01

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide variety of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, nongel-based proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of variations on the general methods and technologies for identifying peptides in a given sample. We present a method that can serve as a "baseline" for proteomic studies of fungi.

A randomized controlled trial to evaluate the Make Safe Happen® app-a mobile technology-based safety behavior change intervention for increasing parents' safety knowledge and actions.

PubMed

McKenzie, Lara B; Roberts, Kristin J; Clark, Roxanne; McAdams, Rebecca; Abdel-Rasoul, Mahmoud; Klein, Elizabeth G; Keim, Sarah A; Kristel, Orie; Szymanski, Alison; Cotton, Christopher G; Shields, Wendy C

2018-03-12

Many unintentional injuries that occur in and around the home can be prevented through the use of safety equipment and by consistently following existing safety recommendations. Unfortunately, uptake of these safety behaviors is unacceptably low. This paper describes the design of the Make Safe Happen® smartphone application evaluation study, which aims to evaluate a mobile technology-based safety behavior change intervention on parents' safety knowledge and actions. Make Safe Happen® app evaluation study is a randomized controlled trial. Participants will be parents of children aged 0-12 years who are recruited from national consumer online survey panels. Parents will complete a pretest survey, and will be randomized to receive the Make Safe Happen® app or a non-injury-related app, and then complete a posttest follow-up survey after 1 week. Primary outcomes are: (1) safety knowledge; (2) safety behaviors; (3) safety device acquisition and use, and (4) behavioral intention to take safety actions. Anticipated study results are presented. Wide-reaching interventions, to reach substantial parent and caregiver audiences, to effectively reduce childhood injuries are needed. This study will contribute to the evidence-base about how to increase safety knowledge and actions to prevent home-related injuries in children. NCT02751203 ; Pre-results.

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2011-06-01

spectroscopy-based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and...will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr. Michael Kennedy, Miami University. Changes in proteomic profiles will be...based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and

The quest of the human proteome and the missing proteins: digging deeper.

PubMed

Reddy, Panga Jaipal; Ray, Sandipan; Srivastava, Sanjeeva

2015-05-01

Given the diverse range of transcriptional and post-transcriptional mechanisms of gene regulation, the estimates of the human proteome is likely subject to scientific surprises as the field of proteomics has gained momentum worldwide. In this regard, the establishment of the "Human Proteome Draft" using high-resolution mass spectrometry (MS), tissue microarrays, and immunohistochemistry by three independent research groups (laboratories of Pandey, Kuster, and Uhlen) accelerated the pace of proteomics research. The Chromosome Centric Human Proteome Project (C-HPP) has taken initiative towards the completion of the Human Proteome Project (HPP) so as to understand the proteomics correlates of common complex human diseases and biological diversity, not to mention person-to-person and population differences in response to drugs, nutrition, vaccines, and other health interventions and host-environment interactions. Although high-resolution MS-based and antibody microarray approaches have shown enormous promises, we are still unable to map the whole human proteome due to the presence of numerous "missing proteins." In December 2014, at the Indian Institute of Technology Bombay, Mumbai the 6(th) Annual Meeting of the Proteomics Society, India (PSI) and the International Proteomics Conference was held. As part of this interdisciplinary summit, a panel discussion session on "The Quest of the Human Proteome and Missing Proteins" was organized. Eminent scientists in the field of proteomics and systems biology, including Akhilesh Pandey, Gilbert S. Omenn, Mark S. Baker, and Robert L. Mortiz, shed light on different aspects of the human proteome drafts and missing proteins. Importantly, the possible reasons for the "missing proteins" in shotgun MS workflow were identified and debated by experts as low tissue expression, lack of enzymatic digestion site, or protein lost during extraction, among other contributing factors. To capture the missing proteins, the experts' collective view was to study the wider tissue range with multiple digesting enzymes and follow targeted proteomics workflow in particular. On the innovation trajectory from the proteomics laboratory to novel proteomics diagnostics and therapeutics in society, we will also need new conceptual frames for translation science and innovation strategy in proteomics. These will embody both technical as well as rigorous social science and humanities considerations to understand the correlates of the proteome from cell to society.

The role of targeted chemical proteomics in pharmacology

PubMed Central

Sutton, Chris W

2012-01-01

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351

Toward the Standardization of Mitochondrial Proteomics: The Italian Mitochondrial Human Proteome Project Initiative.

PubMed

Alberio, Tiziana; Pieroni, Luisa; Ronci, Maurizio; Banfi, Cristina; Bongarzone, Italia; Bottoni, Patrizia; Brioschi, Maura; Caterino, Marianna; Chinello, Clizia; Cormio, Antonella; Cozzolino, Flora; Cunsolo, Vincenzo; Fontana, Simona; Garavaglia, Barbara; Giusti, Laura; Greco, Viviana; Lucacchini, Antonio; Maffioli, Elisa; Magni, Fulvio; Monteleone, Francesca; Monti, Maria; Monti, Valentina; Musicco, Clara; Petrosillo, Giuseppe; Porcelli, Vito; Saletti, Rosaria; Scatena, Roberto; Soggiu, Alessio; Tedeschi, Gabriella; Zilocchi, Mara; Roncada, Paola; Urbani, Andrea; Fasano, Mauro

2017-12-01

The Mitochondrial Human Proteome Project aims at understanding the function of the mitochondrial proteome and its crosstalk with the proteome of other organelles. Being able to choose a suitable and validated enrichment protocol of functional mitochondria, based on the specific needs of the downstream proteomics analysis, would greatly help the researchers in the field. Mitochondrial fractions from ten model cell lines were prepared using three enrichment protocols and analyzed on seven different LC-MS/MS platforms. All data were processed using neXtProt as reference database. The data are available for the Human Proteome Project purposes through the ProteomeXchange Consortium with the identifier PXD007053. The processed data sets were analyzed using a suite of R routines to perform a statistical analysis and to retrieve subcellular and submitochondrial localizations. Although the overall number of identified total and mitochondrial proteins was not significantly dependent on the enrichment protocol, specific line to line differences were observed. Moreover, the protein lists were mapped to a network representing the functional mitochondrial proteome, encompassing mitochondrial proteins and their first interactors. More than 80% of the identified proteins resulted in nodes of this network but with a different ability in coisolating mitochondria-associated structures for each enrichment protocol/cell line pair.

Proteomics in Argentina - limitations and future perspectives: A special emphasis on meat proteomics.

PubMed

Fadda, Silvina; Almeida, André M

2015-11-01

Argentina is one of the most relevant countries in Latin America, playing a major role in regional economics, culture and science. Over the last 80 years, Argentinean history has been characterized by several upward and downward phases that had major consequences on the development of science in the country and most recently on proteomics. In this article, we characterize the evolution of Proteomics sciences in Argentina over the last decade and a half. We describe the proteomics publication output of the country in the framework of the regional and international contexts, demonstrating that Argentina is solidly anchored in a regional context, showing results similar to other emergent and Latin American countries, albeit still far from the European, American or Australian realities. We also provide a case-study on the importance of Proteomics to a specific sector in the area of food science: the use of bacteria of technological interest, highlighting major achievements obtained by Argentinean proteomics scientists. Finally, we provide a general picture of the endeavors being undertaken by Argentinean Proteomics scientists and their international collaborators to promote the Proteomics-based research with the new generation of scientists and PhD students in both Argentina and other countries in the Southern cone. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The secrets of Oriental panacea: Panax ginseng.

PubMed

Colzani, Mara; Altomare, Alessandra; Caliendo, Matteo; Aldini, Giancarlo; Righetti, Pier Giorgio; Fasoli, Elisa

2016-01-01

The Panax ginseng root proteome has been investigated via capture with combinatorial peptide ligand libraries (CPLL) at three different pH values. Proteomic characterization by SDS-PAGE and nLC–MS/MS analysis, via LTQ-Orbitrap XL, led to the identification of a total of 207 expressed proteins. This quite large number of identifications was achieved by consulting two different plant databases: P. ginseng and Arabidopsis thaliana. The major groups of identified proteins were associated to structural species (19.2%), oxidoreductase (19.5%), dehydrogenases (7.6%) and synthases (9.0%). For the first time, an exploration of protein–protein interactions was performed by merging all recognized proteins and building an interactomic map, characterized by 196 nodes and 1554 interactions. Finally a peptidomic analysis was developed combining different in-silico enzymatic digestions to simulate the human gastrointestinal process: from 661 generated peptides, 95 were identified as possible bioactives and in particular 6 of them were characterized by antimicrobial activity. The present report offers new insight for future investigations focused on elucidation of biological properties of P. ginseng proteome and peptidome. Ginseng is a traditional oriental herbal remedy whose use is very diffused in all the world for its numerous pharmacological effects. However, the exact mechanism of action of ginseng components, both ginsenosides and proteins, is still unidentified. So the common use of ginseng requires strict investigations to assess both its efficiency and its safety. Although many reports have been published regarding the pharmacological effects of ginseng, little is known about the biochemical pathways of root. Proteomics analysis could be useful to elucidate the physiological pathways. In this manuscript, an integrated approach to proteomics and peptidomics will usher in exploration of Panax ginseng proteins and proteolytic peptides, obtained by in-silico gastrointestinal digestion, characterized by antimicrobial action. The present research would pave the way for better knowledge of metabolic functions connected with ginseng proteome and provide with new information necessary to understand better antimicrobial activity of P. ginseng.

Effects of diuretics on urinary proteins.

PubMed

Li, Xundou

2015-01-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. The human orthologs of most of these 14 proteins affected are stable in the healthy human urinary proteome, and 10 of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics.

Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics.

PubMed

Lavallée-Adam, Mathieu; Yates, John R

2016-03-24

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the Web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

RPP-PRT-58489, Revision 1, One Systems Consistent Safety Analysis Methodologies Report. 24590-WTP-RPT-MGT-15-014

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

Gupta, Mukesh; Niemi, Belinda; Paik, Ingle

2015-09-02

In 2012, One System Nuclear Safety performed a comparison of the safety bases for the Tank Farms Operations Contractor (TOC) and Hanford Tank Waste Treatment and Immobilization Plant (WTP) (RPP-RPT-53222 / 24590-WTP-RPT-MGT-12-018, “One System Report of Comparative Evaluation of Safety Bases for Hanford Waste Treatment and Immobilization Plant Project and Tank Operations Contract”), and identified 25 recommendations that required further evaluation for consensus disposition. This report documents ten NSSC approved consistent methodologies and guides and the results of the additional evaluation process using a new set of evaluation criteria developed for the evaluation of the new methodologies.

Evaluation of the Quality of Occupational Health and Safety Management Systems Based on Key Performance Indicators in Certified Organizations.

PubMed

Mohammadfam, Iraj; Kamalinia, Mojtaba; Momeni, Mansour; Golmohammadi, Rostam; Hamidi, Yadollah; Soltanian, Alireza

2017-06-01

Occupational Health and Safety Management Systems are becoming more widespread in organizations. Consequently, their effectiveness has become a core topic for researchers. This paper evaluates the performance of the Occupational Health and Safety Assessment Series 18001 specification in certified companies in Iran. The evaluation is based on a comparison of specific criteria and indictors related to occupational health and safety management practices in three certified and three noncertified companies. Findings indicate that the performance of certified companies with respect to occupational health and safety management practices is significantly better than that of noncertified companies. Occupational Health and Safety Assessment Series 18001-certified companies have a better level of occupational health and safety; this supports the argument that Occupational Health and Safety Management Systems play an important strategic role in health and safety in the workplace.

Tissue proteomics of the low-molecular weight proteome using an integrated cLC-ESI-QTOFMS approach.

PubMed

Alvarez, MeiHwa Tanielle Bench; Shah, Dipti Jigar; Thulin, Craig D; Graves, Steven W

2013-05-01

Analysis of the protein/peptide composition of tissue has provided meaningful insights into tissue biology and even disease mechanisms. However, little has been published regarding top down methods to investigate lower molecular weight (MW) (500-5000 Da) species in tissue. Here, we evaluate a tissue proteomics approach involving tissue homogenization followed by depletion of large proteins and then cLC-MS (where c stands for capillary) analysis to interrogate the low MW/low abundance tissue proteome. In the development of this method, sheep heart, lung, liver, kidney, and spleen were surveyed to test our ability to observe tissue differences. After categorical tissue differences were demonstrated, a detailed study of this method's reproducibility was undertaken to determine whether or not it is suitable for analyzing more subtle differences in the abundance of small proteins and peptides. Our results suggest that this method should be useful in exploring the low MW proteome of tissues. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Noninvasive diagnosis of intraamniotic infection: proteomic biomarkers in vaginal fluid.

PubMed

Hitti, Jane; Lapidus, Jodi A; Lu, Xinfang; Reddy, Ashok P; Jacob, Thomas; Dasari, Surendra; Eschenbach, David A; Gravett, Michael G; Nagalla, Srinivasa R

2010-07-01

We analyzed the vaginal fluid proteome to identify biomarkers of intraamniotic infection among women in preterm labor. Proteome analysis was performed on vaginal fluid specimens from women with preterm labor, using multidimensional liquid chromatography, tandem mass spectrometry, and label-free quantification. Enzyme immunoassays were used to quantify candidate proteins. Classification accuracy for intraamniotic infection (positive amniotic fluid bacterial culture and/or interleukin-6 >2 ng/mL) was evaluated using receiver-operator characteristic curves obtained by logistic regression. Of 170 subjects, 30 (18%) had intraamniotic infection. Vaginal fluid proteome analysis revealed 338 unique proteins. Label-free quantification identified 15 proteins differentially expressed in intraamniotic infection, including acute-phase reactants, immune modulators, high-abundance amniotic fluid proteins and extracellular matrix-signaling factors; these findings were confirmed by enzyme immunoassay. A multi-analyte algorithm showed accurate classification of intraamniotic infection. Vaginal fluid proteome analyses identified proteins capable of discriminating between patients with and without intraamniotic infection. Copyright (c) 2010 Mosby, Inc. All rights reserved.

A systematic evaluation of normalization methods in quantitative label-free proteomics.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2018-01-01

To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normalization method is a pivotal task for the reliability of the downstream analysis and results. Many normalization methods commonly used in proteomics have been adapted from the DNA microarray techniques. Previous studies comparing normalization methods in proteomics have focused mainly on intragroup variation. In this study, several popular and widely used normalization methods representing different strategies in normalization are evaluated using three spike-in and one experimental mouse label-free proteomic data sets. The normalization methods are evaluated in terms of their ability to reduce variation between technical replicates, their effect on differential expression analysis and their effect on the estimation of logarithmic fold changes. Additionally, we examined whether normalizing the whole data globally or in segments for the differential expression analysis has an effect on the performance of the normalization methods. We found that variance stabilization normalization (Vsn) reduced variation the most between technical replicates in all examined data sets. Vsn also performed consistently well in the differential expression analysis. Linear regression normalization and local regression normalization performed also systematically well. Finally, we discuss the choice of a normalization method and some qualities of a suitable normalization method in the light of the results of our evaluation. © The Author 2016. Published by Oxford University Press.

Multidimensional proteomics for cell biology.

PubMed

Larance, Mark; Lamond, Angus I

2015-05-01

The proteome is a dynamic system in which each protein has interconnected properties - dimensions - that together contribute to the phenotype of a cell. Measuring these properties has proved challenging owing to their diversity and dynamic nature. Advances in mass spectrometry-based proteomics now enable the measurement of multiple properties for thousands of proteins, including their abundance, isoform expression, turnover rate, subcellular localization, post-translational modifications and interactions. Complementing these experimental developments are new data analysis, integration and visualization tools as well as data-sharing resources. Together, these advances in the multidimensional analysis of the proteome are transforming our understanding of various cellular and physiological processes.

Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes

NASA Astrophysics Data System (ADS)

Hu, Zhang-Zhi; Valencia, Julio C.; Huang, Hongzhan; Chi, An; Shabanowitz, Jeffrey; Hearing, Vincent J.; Appella, Ettore; Wu, Cathy

2007-01-01

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for seven lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis. Heterogeneous sources of human organelle proteins and rodent homologs are mapped to human UniProtKB protein entries based on ID and/or peptide mappings, followed by functional annotation and categorization using the iProXpress proteomic expression analysis system. Cataloging organelle proteomes allows close examination of both shared and unique proteins among various LROs and reveals their functional relevance. The proteomic comparisons show that LROs are a closely related family of organelles. The shared proteins indicate the dynamic and hybrid nature of LROs, while the unique transmembrane proteins may represent additional candidate marker proteins for LROs. This comparative analysis, therefore, provides a basis for hypothesis formulation and experimental validation of organelle proteins and their functional roles.

Top-down Proteomics in Health and Disease: Challenges and Opportunities

PubMed Central

Gregorich, Zachery R.; Ge, Ying

2014-01-01

Proteomics is essential for deciphering how molecules interact as a system and for understanding the functions of cellular systems in human disease; however, the unique characteristics of the human proteome, which include a high dynamic range of protein expression and extreme complexity due to a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses challenging. An emerging “top-down” mass spectrometry (MS)-based proteomics approach, which provides a “bird’s eye” view of all proteoforms, has unique advantages for the assessment of PTMs and sequence variations. Recently, a number of studies have showcased the potential of top-down proteomics for unraveling of disease mechanisms and discovery of new biomarkers. Nevertheless, the top-down approach still faces significant challenges in terms of protein solubility, separation, and the detection of large intact proteins, as well as the under-developed data analysis tools. Consequently, new technological developments are urgently needed to advance the field of top-down proteomics. Herein, we intend to provide an overview of the recent applications of top-down proteomics in biomedical research. Moreover, we will outline the challenges and opportunities facing top-down proteomics strategies aimed at understanding and diagnosing human diseases. PMID:24723472

A toolbox for safety instrumented system evaluation based on improved continuous-time Markov chain

NASA Astrophysics Data System (ADS)

Wardana, Awang N. I.; Kurniady, Rahman; Pambudi, Galih; Purnama, Jaka; Suryopratomo, Kutut

2017-08-01

Safety instrumented system (SIS) is designed to restore a plant into a safe condition when pre-hazardous event is occur. It has a vital role especially in process industries. A SIS shall be meet with safety requirement specifications. To confirm it, SIS shall be evaluated. Typically, the evaluation is calculated by hand. This paper presents a toolbox for SIS evaluation. It is developed based on improved continuous-time Markov chain. The toolbox supports to detailed approach of evaluation. This paper also illustrates an industrial application of the toolbox to evaluate arch burner safety system of primary reformer. The results of the case study demonstrates that the toolbox can be used to evaluate industrial SIS in detail and to plan the maintenance strategy.

Operational Experience of an Open-Access, Subscription-Based Mass Spectrometry and Proteomics Facility.

PubMed

Williamson, Nicholas A

2018-03-01

This paper discusses the successful adoption of a subscription-based, open-access model of service delivery for a mass spectrometry and proteomics facility. In 2009, the Mass Spectrometry and Proteomics Facility at the University of Melbourne (Australia) moved away from the standard fee for service model of service provision. Instead, the facility adopted a subscription- or membership-based, open-access model of service delivery. For a low fixed yearly cost, users could directly operate the instrumentation but, more importantly, there were no limits on usage other than the necessity to share available instrument time with all other users. All necessary training from platform staff and many of the base reagents were also provided as part of the membership cost. These changes proved to be very successful in terms of financial outcomes for the facility, instrument access and usage, and overall research output. This article describes the systems put in place as well as the overall successes and challenges associated with the operation of a mass spectrometry/proteomics core in this manner. Graphical abstract ᅟ.

Operational Experience of an Open-Access, Subscription-Based Mass Spectrometry and Proteomics Facility

NASA Astrophysics Data System (ADS)

Williamson, Nicholas A.

2018-03-01

This paper discusses the successful adoption of a subscription-based, open-access model of service delivery for a mass spectrometry and proteomics facility. In 2009, the Mass Spectrometry and Proteomics Facility at the University of Melbourne (Australia) moved away from the standard fee for service model of service provision. Instead, the facility adopted a subscription- or membership-based, open-access model of service delivery. For a low fixed yearly cost, users could directly operate the instrumentation but, more importantly, there were no limits on usage other than the necessity to share available instrument time with all other users. All necessary training from platform staff and many of the base reagents were also provided as part of the membership cost. These changes proved to be very successful in terms of financial outcomes for the facility, instrument access and usage, and overall research output. This article describes the systems put in place as well as the overall successes and challenges associated with the operation of a mass spectrometry/proteomics core in this manner. [Figure not available: see fulltext.

Analyses of flooding tolerance of soybean varieties at emergence and varietal differences in their proteomes.

PubMed

Nanjo, Yohei; Jang, Hee-Young; Kim, Hong-Sig; Hiraga, Susumu; Woo, Sun-Hee; Komatsu, Setsuko

2014-10-01

Flooding of fields due to heavy and/or continuous rainfall influences soybean production. To identify soybean varieties with flooding tolerance at the seedling emergence stage, 128 soybean varieties were evaluated using a flooding tolerance index, which is based on plant survival rates, the lack of apparent damage and lateral root development, and post-flooding radicle elongation rate. The soybean varieties were ranked according to their flooding tolerance index, and it was found that the tolerance levels of soybean varieties exhibit a continuum of differences between varieties. Subsequently, tolerant, moderately tolerant and sensitive varieties were selected and subjected to comparative proteomic analysis to clarify the tolerance mechanism. Proteomic analysis of the radicles, combined with correlation analysis, showed that the ratios of RNA binding/processing related proteins and flooding stress indicator proteins were significantly correlated with flooding tolerance index. The RNA binding/processing related proteins were positively correlated in untreated soybeans, whereas flooding stress indicator proteins were negatively correlated in flooded soybeans. These results suggest that flooding tolerance is regulated by mechanisms through multiple factors and is associated with abundance levels of the identified proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

PubMed

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

Evaluation of molecular brain changes associated with environmental stress in rodent models compared to human major depressive disorder: A proteomic systems approach.

PubMed

Cox, David Alan; Gottschalk, Michael Gerd; Stelzhammer, Viktoria; Wesseling, Hendrik; Cooper, Jason David; Bahn, Sabine

2016-11-25

Rodent models of major depressive disorder (MDD) are indispensable when screening for novel treatments, but assessing their translational relevance with human brain pathology has proved difficult. Using a novel systems approach, proteomics data obtained from post-mortem MDD anterior prefrontal cortex tissue (n = 12) and matched controls (n = 23) were compared with equivalent data from three commonly used preclinical models exposed to environmental stressors (chronic mild stress, prenatal stress and social defeat). Functional pathophysiological features associated with depression-like behaviour were identified in these models through enrichment of protein-protein interaction networks. A cross-species comparison evaluated which model(s) represent human MDD pathology most closely. Seven functional domains associated with MDD and represented across at least two models such as "carbohydrate metabolism and cellular respiration" were identified. Through statistical evaluation using kernel-based machine learning techniques, the social defeat model was found to represent MDD brain changes most closely for four of the seven domains. This is the first study to apply a method for directly evaluating the relevance of the molecular pathology of multiple animal models to human MDD on the functional level. The methodology and findings outlined here could help to overcome translational obstacles of preclinical psychiatric research.

Evaluation of the safety performance of highway alignments based on fault tree analysis and safety boundaries.

PubMed

Chen, Yikai; Wang, Kai; Xu, Chengcheng; Shi, Qin; He, Jie; Li, Peiqing; Shi, Ting

2018-05-19

To overcome the limitations of previous highway alignment safety evaluation methods, this article presents a highway alignment safety evaluation method based on fault tree analysis (FTA) and the characteristics of vehicle safety boundaries, within the framework of dynamic modeling of the driver-vehicle-road system. Approaches for categorizing the vehicle failure modes while driving on highways and the corresponding safety boundaries were comprehensively investigated based on vehicle system dynamics theory. Then, an overall crash probability model was formulated based on FTA considering the risks of 3 failure modes: losing steering capability, losing track-holding capability, and rear-end collision. The proposed method was implemented on a highway segment between Bengbu and Nanjing in China. A driver-vehicle-road multibody dynamics model was developed based on the 3D alignments of the Bengbu to Nanjing section of Ning-Luo expressway using Carsim, and the dynamics indices, such as sideslip angle and, yaw rate were obtained. Then, the average crash probability of each road section was calculated with a fixed-length method. Finally, the average crash probability was validated against the crash frequency per kilometer to demonstrate the accuracy of the proposed method. The results of the regression analysis and correlation analysis indicated good consistency between the results of the safety evaluation and the crash data and that it outperformed the safety evaluation methods used in previous studies. The proposed method has the potential to be used in practical engineering applications to identify crash-prone locations and alignment deficiencies on highways in the planning and design phases, as well as those in service.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

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

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dissecting plasmodesmata molecular composition by mass spectrometry-based proteomics.

PubMed

Salmon, Magali S; Bayer, Emmanuelle M F

2012-01-01

In plants, the intercellular communication through the membranous channels called plasmodesmata (PD; singular plasmodesma) plays pivotal roles in the orchestration of development, defence responses, and viral propagation. PD are dynamic structures embedded in the plant cell wall that are defined by specialized domains of the endoplasmic reticulum (ER) and the plasma membrane (PM). PD structure and unique functions are guaranteed by their particular molecular composition. Yet, up to recent years and despite numerous approaches such as mutant screens, immunolocalization, or screening of random cDNAs, only few PD proteins had been conclusively identified and characterized. A clear breakthrough in the search of PD constituents came from mass-spectrometry-based proteomic approaches coupled with subcellular fractionation strategies. Due to their position, firmly anchored in the extracellular matrix, PD are notoriously difficult to isolate for biochemical analysis. Proteomic-based approaches have therefore first relied on the use of cell wall fractions containing embedded PD then on "free" PD fractions whereby PD membranes were released from the walls by enzymatic degradation. To discriminate between likely contaminants and PD protein candidates, bioinformatics tools have often been used in combination with proteomic approaches. GFP fusion proteins of selected candidates have confirmed the PD association of several protein families. Here we review the accomplishments and limitations of the proteomic-based strategies to unravel the functional and structural complexity of PD. We also discuss the role of the identified PD-associated proteins.

How well can morphology assess cell death modality? A proteomics study

PubMed Central

Chernobrovkin, Alexey L; Zubarev, Roman A

2016-01-01

While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200–500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment. PMID:27752363

Maillard Proteomics: Opening New Pages

PubMed Central

Soboleva, Alena; Schmidt, Rico; Vikhnina, Maria; Grishina, Tatiana; Frolov, Andrej

2017-01-01

Protein glycation is a ubiquitous non-enzymatic post-translational modification, formed by reaction of protein amino and guanidino groups with carbonyl compounds, presumably reducing sugars and α-dicarbonyls. Resulting advanced glycation end products (AGEs) represent a highly heterogeneous group of compounds, deleterious in mammals due to their pro-inflammatory effect, and impact in pathogenesis of diabetes mellitus, Alzheimer’s disease and ageing. The body of information on the mechanisms and pathways of AGE formation, acquired during the last decades, clearly indicates a certain site-specificity of glycation. It makes characterization of individual glycation sites a critical pre-requisite for understanding in vivo mechanisms of AGE formation and developing adequate nutritional and therapeutic approaches to reduce it in humans. In this context, proteomics is the methodology of choice to address site-specific molecular changes related to protein glycation. Therefore, here we summarize the methods of Maillard proteomics, specifically focusing on the techniques providing comprehensive structural and quantitative characterization of glycated proteome. Further, we address the novel break-through areas, recently established in the field of Maillard research, i.e., in vitro models based on synthetic peptides, site-based diagnostics of metabolism-related diseases (e.g., diabetes mellitus), proteomics of anti-glycative defense, and dynamics of plant glycated proteome during ageing and response to environmental stress. PMID:29231845

Evaluation of formalin-fixed paraffin-embedded tissues in the proteomic analysis of parathyroid glands

PubMed Central

2011-01-01

Background Proteomic research in the field of parathyroid tissues is limited by the very small dimension of the glands and by the low incidence of cancer lesions (1%). Formalin-fixed paraffin-embedded (FFPE) tissue specimens are a potentially valuable resource for discovering protein cancer biomarkers. In this study we have verified the applicability of a heat induced protein extraction from FFPE parathyroid adenoma tissues followed by a gel-based or gel-free proteomic approach in order to achieve protein separation and identification. Results The best results for high quality MS spectra and parameters, were obtained by using a gel-free approach, and up to 163 unique proteins were identified. Similar results were obtained by applying both SDS-out and SDS-out + TCA/Acetone techniques during the gel-free method. Western blot analysis carried out with specific antibodies suggested that the antigenicity was not always preserved, while specific immunoreactions were detected for calmodulin, B box and SPRY domain-containing protein (BSPRY), peroxiredoxin 6 (PRDX 6) and parvalbumin. Conclusions In spite of some limitations mainly due to the extensive formalin-induced covalent cross-linking, our results essentially suggest the applicability of a proteomic approach to FFPE parathyroid specimens. From our point of view, FFPE extracts might be an alternative source, especially in the validation phase of protein biomarkers when a large cohort of samples is required and the low availability of frozen tissues might be constraining. PMID:21651755

Proteome alteration induced by hTERT transfection of human fibroblast cells.

PubMed

Mazzucchelli, Gabriel D; Gabelica, Valérie; Smargiasso, Nicolas; Fléron, Maximilien; Ashimwe, Wilson; Rosu, Frédéric; De Pauw-Gillet, Marie-Claire; Riou, Jean-François; De Pauw, Edwin

2008-04-17

Telomerase confers cellular immortality by elongating telomeres, thereby circumventing the Hayflick limit. Extended-life-span cells have been generated by transfection with the human telomerase reverse transcriptase (hTERT) gene. hTERT transfected cell lines may be of outstanding interest to monitor the effect of drugs targeting the telomerase activity. The incidence of hTERT gene transfection at the proteome level is a prerequisite to that purpose. The effect of the transfection has been studied on the proteome of human fibroblast (WI38). Cytosolic and nuclear fractions of WI38 cells, empty vector transfected WI38 (WI38-HPV) and hTERT WI38 cells were submitted to a 2D-DIGE (Two-Dimensional Differential In-Gel Electrophoresis) analysis. Only spots that had a similar abundance in WI38 and WI38-HPV, but were differentially expressed in WI38 hTERT were selected for MS identification. This method directly points to the proteins linked with the hTERT expression. Number of false positive differentially expressed proteins has been excluded by using control WI38-HPV cells. The proteome alteration induced by hTERT WI38 transfection should be taken into account in subsequent use of the cell line for anti-telomerase drugs evaluation. 2D-DIGE experiment shows that 57 spots out of 2246 are significantly differentially expressed in the cytosolic fraction due to hTERT transfection, and 38 were confidently identified. In the nuclear fraction, 44 spots out of 2172 were selected in the differential proteome analysis, and 14 were identified. The results show that, in addition to elongating telomeres, hTERT gene transfection has other physiological roles, among which an enhanced ER capacity and a potent cell protection against apoptosis. We show that the methodology reduces the complexity of the proteome analysis and highlights proteins implicated in other processes than telomere elongation. hTERT induced proteome changes suggest that telomerase expression enhances natural cell repair mechanisms and stress resistance probably required for long term resistance of immortalized cells. Thus, hTERT transfected cells can not be only consider as an immortal equivalent to parental cells but also as cells which are over-resistant to stresses. These findings are the prerequisite for any larger proteomics aiming to evaluate anti-telomerase drugs proteome alteration and thus therapeutics induced cell reactions.

Emerging techniques for the discovery and validation of therapeutic targets for skeletal diseases.

PubMed

Cho, Christine H; Nuttall, Mark E

2002-12-01

Advances in genomics and proteomics have revolutionised the drug discovery process and target validation. Identification of novel therapeutic targets for chronic skeletal diseases is an extremely challenging process based on the difficulty of obtaining high-quality human diseased versus normal tissue samples. The quality of tissue and genomic information obtained from the sample is critical to identifying disease-related genes. Using a genomics-based approach, novel genes or genes with similar homology to existing genes can be identified from cDNA libraries generated from normal versus diseased tissue. High-quality cDNA libraries are prepared from uncontaminated homogeneous cell populations harvested from tissue sections of interest. Localised gene expression analysis and confirmation are obtained through in situ hybridisation or immunohistochemical studies. Cells overexpressing the recombinant protein are subsequently designed for primary cell-based high-throughput assays that are capable of screening large compound banks for potential hits. Afterwards, secondary functional assays are used to test promising compounds. The same overexpressing cells are used in the secondary assay to test protein activity and functionality as well as screen for small-molecule agonists or antagonists. Once a hit is generated, a structure-activity relationship of the compound is optimised for better oral bioavailability and pharmacokinetics allowing the compound to progress into development. Parallel efforts from proteomics, as well as genetics/transgenics, bioinformatics and combinatorial chemistry, and improvements in high-throughput automation technologies, allow the drug discovery process to meet the demands of the medicinal market. This review discusses and illustrates how different approaches are incorporated into the discovery and validation of novel targets and, consequently, the development of potentially therapeutic agents in the areas of osteoporosis and osteoarthritis. While current treatments exist in the form of hormone replacement therapy, antiresorptive and anabolic agents for osteoporosis, there are no disease-modifying therapies for the treatment of the most common human joint disease, osteoarthritis. A massive market potential for improved options with better safety and efficacy still remains. Therefore, the application of genomics and proteomics for both diseases should provide much needed novel therapeutic approaches to treating these major world health problems.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research.

PubMed

Zürbig, Petra; Jahn, Holger

2012-12-01

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of an Improved Proteomics Method for Abundant Protein Cleanup: Molecular and Genomic Mechanisms Study in Plant Defense*

PubMed Central

Zhang, Yixiang; Gao, Peng; Xing, Zhuo; Jin, Shumei; Chen, Zhide; Liu, Lantao; Constantino, Nasie; Wang, Xinwang; Shi, Weibing; Yuan, Joshua S.; Dai, Susie Y.

2013-01-01

High abundance proteins like ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) impose a consistent challenge for the whole proteome characterization using shot-gun proteomics. To address this challenge, we developed and evaluated Polyethyleneimine Assisted Rubisco Cleanup (PARC) as a new method by combining both abundant protein removal and fractionation. The new approach was applied to a plant insect interaction study to validate the platform and investigate mechanisms for plant defense against herbivorous insects. Our results indicated that PARC can effectively remove Rubisco, improve the protein identification, and discover almost three times more differentially regulated proteins. The significantly enhanced shot-gun proteomics performance was translated into in-depth proteomic and molecular mechanisms for plant insect interaction, where carbon re-distribution was used to play an essential role. Moreover, the transcriptomic validation also confirmed the reliability of PARC analysis. Finally, functional studies were carried out for two differentially regulated genes as revealed by PARC analysis. Insect resistance was induced by over-expressing either jacalin-like or cupin-like genes in rice. The results further highlighted that PARC can serve as an effective strategy for proteomics analysis and gene discovery. PMID:23943779

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

PubMed

Huang, Xin; Tolmachev, Aleksey V; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A; Smith, Richard D; Chan, Wing C; Hinrichs, Steven H; Fu, Kai; Ding, Shi-Jian

2011-03-04

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.

UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

PubMed Central

Huang, Xin; Tolmachev, Aleksey V.; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A.; Smith, Richard D.; Chan, Wing C.; Hinrichs, Steven H.; Fu, Kai; Ding, Shi-Jian

2011-01-01

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for post-measurement normalization of peptide ratios, which is required by the other programs. PMID:21158445

FRAMEWORK FOR EVALUATION OF PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELS FOR USE IN SAFETY OR RISK ASSESSMENT

EPA Science Inventory

ABSTRACT

Proposed applications of increasingly sophisticated biologically-based computational models, such as physiologically-based pharmacokinetic (PBPK) models, raise the issue of how to evaluate whether the models are adequate for proposed uses including safety or risk ...

UV irradiation-induced methionine oxidation in human skin keratins: Mass spectrometry-based non-invasive proteomic analysis.

PubMed

Lee, Seon Hwa; Matsushima, Keita; Miyamoto, Kohei; Oe, Tomoyuki

2016-02-05

Ultraviolet (UV) radiation is the major environmental factor that causes oxidative skin damage. Keratins are the main constituents of human skin and have been identified as oxidative target proteins. We have recently developed a mass spectrometry (MS)-based non-invasive proteomic methodology to screen oxidative modifications in human skin keratins. Using this methodology, UV effects on methionine (Met) oxidation in human skin keratins were investigated. The initial screening revealed that Met(259), Met(262), and Met(296) in K1 keratin were the most susceptible oxidation sites upon UVA (or UVB) irradiation of human tape-stripped skin. Subsequent liquid chromatography/electrospray ionization-MS and tandem MS analyses confirmed amino acid sequences and oxidation sites of tryptic peptides D(290)VDGAYMTK(298) (P1) and N(258)MQDMVEDYR(267) (P2). The relative oxidation levels of P1 and P2 increased in a time-dependent manner upon UVA irradiation. Butylated hydroxytoluene was the most effective antioxidant for artifactual oxidation of Met residues. The relative oxidation levels of P1 and P2 after UVA irradiation for 48 h corresponded to treatment with 100mM hydrogen peroxide for 15 min. In addition, Met(259) was oxidized by only UVA irradiation. The Met sites identified in conjunction with the current proteomic methodology can be used to evaluate skin damage under various conditions of oxidative stress. We demonstrated that the relative Met oxidation levels in keratins directly reflected UV-induced damages to human tape-stripped skin. Human skin proteins isolated by tape stripping were analyzed by MS-based non-invasive proteomic methodology. Met(259), Met(262), and Met(296) in K1 keratin were the most susceptible oxidation sites upon UV irradiation. Met(259) was oxidized by only UVA irradiation. Quantitative LC/ESI-SRM/MS analyses confirmed a time-dependent increase in the relative oxidation of target peptides (P1 and P2) containing these Met residues, upon UVA irradiation of isolated human skin. The relative oxidation levels of P1 and P2 along with the current proteomic methodology could be applied to the assessment of oxidative stress levels in skin after exposure to sunlight. Copyright © 2015 Elsevier B.V. All rights reserved.

Genic insights from integrated human proteomics in GeneCards.

PubMed

Fishilevich, Simon; Zimmerman, Shahar; Kohn, Asher; Iny Stein, Tsippi; Olender, Tsviya; Kolker, Eugene; Safran, Marilyn; Lancet, Doron

2016-01-01

GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite's next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein-RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL:http://www.genecards.org/. © The Author(s) 2016. Published by Oxford University Press.

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

Proteomics of the Human Placenta: Promises and Realities

PubMed Central

Robinson, J.M.; Ackerman, W.E.; Kniss, D.A.; Takizawa, T.; Vandré, D.D.

2015-01-01

Proteomics is an area of study that sets as its ultimate goal the global analysis of all of the proteins expressed in a biological system of interest. However, technical limitations currently hamper proteome-wide analyses of complex systems. In a more practical sense, a desired outcome of proteomics research is the translation of large protein data sets into formats that provide meaningful information regarding clinical conditions (e.g., biomarkers to serve as diagnostic and/or prognostic indicators of disease). Herein, we discuss placental proteomics by describing existing studies, pointing out their strengths and weaknesses. In so doing, we strive to inform investigators interested in this area of research about the current gap between hyperbolic promises and realities. Additionally, we discuss the utility of proteomics in discovery-based research, particularly as regards the capacity to unearth novel insights into placental biology. Importantly, when considering under studied systems such as the human placenta and diseases associated with abnormalities in placental function, proteomics can serve as a robust ‘shortcut’ to obtaining information unlikely to be garnered using traditional approaches. PMID:18222537

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Proteome-Wide Profiling of Targets of Cysteine reactive Small Molecules by Using Ethynyl Benziodoxolone Reagents.

PubMed

Abegg, Daniel; Frei, Reto; Cerato, Luca; Prasad Hari, Durga; Wang, Chao; Waser, Jerome; Adibekian, Alexander

2015-09-07

In this study, we present a highly efficient method for proteomic profiling of cysteine residues in complex proteomes and in living cells. Our method is based on alkynylation of cysteines in complex proteomes using a "clickable" alkynyl benziodoxolone bearing an azide group. This reaction proceeds fast, under mild physiological conditions, and with a very high degree of chemoselectivity. The formed azide-capped alkynyl-cysteine adducts are readily detectable by LC-MS/MS, and can be further functionalized with TAMRA or biotin alkyne via CuAAC. We demonstrate the utility of alkynyl benziodoxolones for chemical proteomics applications by identifying the proteomic targets of curcumin, a diarylheptanoid natural product that was and still is part of multiple human clinical trials as anticancer agent. Our results demonstrate that curcumin covalently modifies several key players of cellular signaling and metabolism, most notably the enzyme casein kinase I gamma. We anticipate that this new method for cysteine profiling will find broad application in chemical proteomics and drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics data exchange and storage: the need for common standards and public repositories.

PubMed

Jiménez, Rafael C; Vizcaíno, Juan Antonio

2013-01-01

Both the existence of data standards and public databases or repositories have been key factors behind the development of the existing "omics" approaches. In this book chapter we first review the main existing mass spectrometry (MS)-based proteomics resources: PRIDE, PeptideAtlas, GPMDB, and Tranche. Second, we report on the current status of the different proteomics data standards developed by the Proteomics Standards Initiative (PSI): the formats mzML, mzIdentML, mzQuantML, TraML, and PSI-MI XML are then reviewed. Finally, we present an easy way to query and access MS proteomics data in the PRIDE database, as a representative of the existing repositories, using the workflow management system (WMS) tool Taverna. Two different publicly available workflows are explained and described.

M2Lite: An Open-source, Light-weight, Pluggable and Fast Proteome Discoverer MSF to mzIdentML Tool.

PubMed

Aiyetan, Paul; Zhang, Bai; Chen, Lily; Zhang, Zhen; Zhang, Hui

2014-04-28

Proteome Discoverer is one of many tools used for protein database search and peptide to spectrum assignment in mass spectrometry-based proteomics. However, the inadequacy of conversion tools makes it challenging to compare and integrate its results to those of other analytical tools. Here we present M2Lite, an open-source, light-weight, easily pluggable and fast conversion tool. M2Lite converts proteome discoverer derived MSF files to the proteomics community defined standard - the mzIdentML file format. M2Lite's source code is available as open-source at https://bitbucket.org/paiyetan/m2lite/src and its compiled binaries and documentation can be freely downloaded at https://bitbucket.org/paiyetan/m2lite/downloads.

Identification of Proteins Related to Epigenetic Regulation in the Malignant Transformation of Aberrant Karyotypic Human Embryonic Stem Cells by Quantitative Proteomics

PubMed Central

Sun, Yi; Yang, Yixuan; Zeng, Sicong; Tan, Yueqiu; Lu, Guangxiu; Lin, Ge

2014-01-01

Previous reports have demonstrated that human embryonic stem cells (hESCs) tend to develop genomic alterations and progress to a malignant state during long-term in vitro culture. This raises concerns of the clinical safety in using cultured hESCs. However, transformed hESCs might serve as an excellent model to determine the process of embryonic stem cell transition. In this study, ITRAQ-based tandem mass spectrometry was used to quantify normal and aberrant karyotypic hESCs proteins from simple to more complex karyotypic abnormalities. We identified and quantified 2583 proteins, and found that the expression levels of 316 proteins that represented at least 23 functional molecular groups were significantly different in both normal and abnormal hESCs. Dysregulated protein expression in epigenetic regulation was further verified in six pairs of hESC lines in early and late passage. In summary, this study is the first large-scale quantitative proteomic analysis of the malignant transformation of aberrant karyotypic hESCs. The data generated should serve as a useful reference of stem cell-derived tumor progression. Increased expression of both HDAC2 and CTNNB1 are detected as early as the pre-neoplastic stage, and might serve as prognostic markers in the malignant transformation of hESCs. PMID:24465727

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2009-06-01

We are working with our collaborators at the Applied Biotechnology Branch, A ir Force Research Lab, W right-Patterson Air Force Base, to accomplish...with systemic lupus erythematosus. Arthritis Rheum 2001;44:2350–7. 33. Zappitelli M, Duffy CM, Bernard C, Gupta IR . Evaluation of activity, chronicity...Children’s Hospital, Chicago, IL: Dr. Linda Wagner-Weiner (data collection); Becky Puplava (study coordinator). University of Okla- homa Health Sciences

Quantitative targeted proteomics for understanding the blood-brain barrier: towards pharmacoproteomics.

PubMed

Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya

2014-06-01

The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.

Evaluation of different protein extraction methods for banana (Musa spp.) root proteome analysis by two-dimensional electrophoresis.

PubMed

Vaganan, M Mayil; Sarumathi, S; Nandakumar, A; Ravi, I; Mustaffa, M M

2015-02-01

Four protocols viz., the trichloroacetic acid-acetone (TCA), phenol-ammonium acetate (PAA), phenol/SDS-ammonium acetate (PSA) and trisbase-acetone (TBA) were evaluated with modifications for protein extraction from banana (Grand Naine) roots, considered as recalcitrant tissues for proteomic analysis. The two-dimensional electrophoresis (2-DE) separated proteins were compared based on protein yield, number of resolved proteins, sum of spot quantity, average spot intensity and proteins resolved in 4-7 pI range. The PAA protocol yielded more proteins (0.89 mg/g of tissues) and protein spots (584) in 2-DE gel than TCA and other protocols. Also, the PAA protocol was superior in terms of sum of total spot quantity and average spot intensity than TCA and other protocols, suggesting phenol as extractant and ammonium acetate as precipitant of proteins were the most suitable for banana rooteomics analysis by 2-DE. In addition, 1:3 ratios of root tissue to extraction buffer and overnight protein precipitation were most efficient to obtain maximum protein yield.

Proteomics of survival structures of fungal pathogens.

PubMed

Loginov, Dmitry; Šebela, Marek

2016-09-25

Fungal pathogens are causal agents of numerous human, animal, and plant diseases. They employ various infection modes to overcome host defense systems. Infection mechanisms of different fungi have been subjected to many comprehensive studies. These investigations have been facilitated by the development of various '-omics' techniques, and proteomics has one of the leading roles in this regard. Fungal conidia and sclerotia could be considered the most important structures for pathogenesis as their germination is one of the first steps towards a host infection. They represent interesting objects for proteomic studies because of the presence of unique proteins with unexplored biotechnological potential required for pathogen viability, development and the subsequent host infection. Proteomic peculiarities of survival structures of different fungi, including those of biotechnological significance (e.g., Asperillus fumigatus, A. nidulans, Metarhizium anisopliae), in a dormant state, as well as changes in the protein production during early stages of fungal development are the subjects of the present review. We focused on biological aspects of proteomic studies of fungal survival structures rather than on an evaluation of proteomic approaches. For that reason, proteins that have been identified in this context are discussed from the point of view of their involvement in different biological processes and possible functions assigned to them. This is the first review paper summarizing recent advances in proteomics of fungal survival structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Independent evaluation of light-vehicle safety applications based on vehicle-to-vehicle communications used in the 2012-2013 safety pilot model deployment

DOT National Transportation Integrated Search

2015-12-01

This report presents the methodology and results of the independent evaluation of safety applications for passenger vehicles in the 2012-2013 Safety Pilot Model Deployment, part of the United States Department of Transportations Intelligent Transp...

What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

PubMed Central

Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

2017-01-01

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895

A systems biology-led insight into the role of the proteome in neurodegenerative diseases.

PubMed

Fasano, Mauro; Monti, Chiara; Alberio, Tiziana

2016-09-01

Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases. Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer's disease, Parkinson's disease and other neurodegenerative disorders, as well as of affected human tissues. Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

PubMed

Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

2017-11-01

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

Integrated Analysis of Transcriptomic and Proteomic Data

PubMed Central

Haider, Saad; Pal, Ranadip

2013-01-01

Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of the transcriptome or the proteome. Based on the central dogma, it was generally assumed that there exist a direct correspondence between mRNA transcripts and generated protein expressions. However, recent studies have shown that the correlation between mRNA and Protein expressions can be low due to various factors such as different half lives and post transcription machinery. Thus, a joint analysis of the transcriptomic and proteomic data can provide useful insights that may not be deciphered from individual analysis of mRNA or protein expressions. This article reviews the existing major approaches for joint analysis of transcriptomic and proteomic data. We categorize the different approaches into eight main categories based on the initial algorithm and final analysis goal. We further present analogies with other domains and discuss the existing research problems in this area. PMID:24082820

Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality.

PubMed

Hawkridge, Adam M; Muddiman, David C

2009-01-01

Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry-based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed.

TrSDB: a proteome database of transcription factors

PubMed Central

Hermoso, Antoni; Aguilar, Daniel; Aviles, Francesc X.; Querol, Enrique

2004-01-01

TrSDB—TranScout Database—(http://ibb.uab.es/trsdb) is a proteome database of eukaryotic transcription factors based upon predicted motifs by TranScout and data sources such as InterPro and Gene Ontology Annotation. Nine eukaryotic proteomes are included in the current version. Extensive and diverse information for each database entry, different analyses considering TranScout classification and similarity relationships are offered for research on transcription factors or gene expression. PMID:14681387

Inhibition of Aurora A Kinase by Alisertib Induces Autophagy and Cell Cycle Arrest and Increases Chemosensitivity in Human Hepatocellular Carcinoma HepG2 Cells.

PubMed

Zhu, Qiaohua; Yu, Xinfa; Zhou, Zhi-Wei; Zhou, Chengyu; Chen, Xiao-Wu; Zhou, Shu-Feng

2017-01-01

Aurora A kinase represent a feasible target in cancer therapy. To evaluate the proteomic response of human liver carcinoma cells to alisertib (ALS) and identify the molecular targets of ALS, we examined the effects of ALS on the proliferation, cell cycle, autophagy, apoptosis, and chemosensitivity in HepG2 cells. The stable-isotope labeling by amino acids in cell culture (SILAC) based quantitative proteomic study was performed to evaluate the proteomic response to ALS. Cell cycle distribution and apoptosis were assessed using flow cytometry and autophagy was determined using flow cytometry and confocal microscopy. Our SILAC proteomic study showed that ALS regulated the expression of 914 proteins, with 407 molecules being up-regulated and 507 molecules being down-regulated in HepG2 cells. Ingenuity pathway analysis (IPA) and KEGG pathway analysis identified 146 and 32 signaling pathways were regulated by ALS, respectively, which were associated with cell survival, programmed cell death, and nutrition-energy metabolism. Subsequently, the verification experiments showed that ALS remarkably arrested HepG2 cells in G2/M phase and led to an accumulation of aneuploidy via regulating the expression of key cell cycle regulators. ALS induced a marked autophagy in a concentration- and time-dependent manner via the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) signaling pathway. Autophagy inhibition promoted the pro-apoptotic effect of ALS, indicating a cyto-protective role of ALS-induced autophagy. ALS increased the chemosensitivity of HepG2 cells to cisplatin and doxorubicin. Taken together, ALS induces autophagy and cell cycle arrest in HepG2 cells via PI3K/Akt/mTOR-mediated pathway. Autophagy inhibition may promote the anticancer effect of ALS and sensitize the chemotherapy in HepG2 cells. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Evaluation of Three Protein-Extraction Methods for Proteome Analysis of Maize Leaf Midrib, a Compound Tissue Rich in Sclerenchyma Cells.

PubMed

Wang, Ning; Wu, Xiaolin; Ku, Lixia; Chen, Yanhui; Wang, Wei

2016-01-01

Leaf morphology is closely related to the growth and development of maize (Zea mays L.) plants and final kernel production. As an important part of the maize leaf, the midrib holds leaf blades in the aerial position for maximum sunlight capture. Leaf midribs of adult plants contain substantial sclerenchyma cells with heavily thickened and lignified secondary walls and have a high amount of phenolics, making protein extraction and proteome analysis difficult in leaf midrib tissue. In the present study, three protein-extraction methods that are commonly used in plant proteomics, i.e., phenol extraction, TCA/acetone extraction, and TCA/acetone/phenol extraction, were qualitatively and quantitatively evaluated based on 2DE maps and MS/MS analysis using the midribs of the 10th newly expanded leaves of maize plants. Microscopy revealed the existence of substantial amounts of sclerenchyma underneath maize midrib epidermises (particularly abaxial epidermises). The spot-number order obtained via 2DE mapping was as follows: phenol extraction (655) > TCA/acetone extraction (589) > TCA/acetone/phenol extraction (545). MS/MS analysis identified a total of 17 spots that exhibited 2-fold changes in abundance among the three methods (using phenol extraction as a control). Sixteen of the proteins identified were hydrophilic, with GRAVY values ranging from -0.026 to -0.487. For all three methods, we were able to obtain high-quality protein samples and good 2DE maps for the maize leaf midrib. However, phenol extraction produced a better 2DE map with greater resolution between spots, and TCA/acetone extraction produced higher protein yields. Thus, this paper includes a discussion regarding the possible reasons for differential protein extraction among the three methods. This study provides useful information that can be used to select suitable protein extraction methods for the proteome analysis of recalcitrant plant tissues that are rich in sclerenchyma cells.

Proteomic Analysis of Grape Berry Cell Cultures Reveals that Developmentally Regulated Ripening Related Processes Can Be Studied Using Cultured Cells

PubMed Central

Sharathchandra, Ramaschandra G.; Stander, Charmaine; Jacobson, Dan; Ndimba, Bongani; Vivier, Melané A.

2011-01-01

Background This work describes a proteomics profiling method, optimized and applied to berry cell suspensions to evaluate organ-specific cultures as a platform to study grape berry ripening. Variations in berry ripening within a cluster(s) on a vine and in a vineyard are a major impediment towards complete understanding of the functional processes that control ripening, specifically when a characterized and homogenous sample is required. Berry cell suspensions could overcome some of these problems, but their suitability as a model system for berry development and ripening needs to be established first. Methodology/Principal Findings In this study we report on the proteomic evaluation of the cytosolic proteins obtained from synchronized cell suspension cultures that were established from callus lines originating from green, véraison and ripe Vitis vinifera berry explants. The proteins were separated using liquid phase IEF in a Microrotofor cell and SDS PAGE. This method proved superior to gel-based 2DE. Principal component analysis confirmed that biological and technical repeats grouped tightly and importantly, showed that the proteomes of berry cultures originating from the different growth/ripening stages were distinct. A total of twenty six common bands were selected after band matching between different growth stages and twenty two of these bands were positively identified. Thirty two % of the identified proteins are currently annotated as hypothetical. The differential expression profile of the identified proteins, when compared with published literature on grape berry ripening, suggested common trends in terms of relative abundance in the different developmental stages between real berries and cell suspensions. Conclusions The advantages of having suspension cultures that accurately mimic specific developmental stages are profound and could significantly contribute to the study of the intricate regulatory and signaling networks responsible for berry development and ripening. PMID:21379583

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

Advances in Proteomics Data Analysis and Display Using an Accurate Mass and Time Tag Approach

PubMed Central

Zimmer, Jennifer S.D.; Monroe, Matthew E.; Qian, Wei-Jun; Smith, Richard D.

2007-01-01

Proteomics has recently demonstrated utility in understanding cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled to high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced. PMID:16429408

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

[Significance of re-evaluation and development of Chinese herbal drugs].

PubMed

Gao, Yue; Ma, Zengchun; Zhang, Boli

2012-01-01

The research of new herbal drugs involves in new herbal drugs development and renew the old drugs. It is necessary to research new herbal drugs based on the theory of traditional Chinese medicine (TCM). The current development of famous TCM focuses on the manufacture process, quality control standards, material basis and clinical research. But system management of security evaluation is deficient, the relevant system for the safety assessment TCM has not been established. The causes of security problems, security risks, target organ of toxicity, weak link of safety evaluation, and ideas of safety evaluation are discussed in this paper. The toxicology research of chinese herbal drugs is necessary based on standard of good laboratory practices (GLP), the characteristic of Chinese herbal drugs is necessary to be fully integrated into safety evaluation. The safety of new drug research is necessary to be integrated throughout the entire process. Famous Chinese medicine safety research must be paid more attention in the future.

Recent advances in stable isotope labeling based techniques for proteome relative quantification.

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2014-10-24

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected. Copyright © 2014 Elsevier B.V. All rights reserved.

The Gel Electrophoresis Markup Language (GelML) from the Proteomics Standards Initiative

PubMed Central

Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J. Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R

2011-01-01

The Human Proteome Organisation’s Proteomics Standards Initiative (HUPO-PSI) has developed the GelML data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for mass spectrometry data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications. PMID:20677327

The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative.

PubMed

Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R

2010-09-01

The Human Proteome Organisation's Proteomics Standards Initiative has developed the GelML (gel electrophoresis markup language) data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for MS data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.

Multiclassifier combinatorial proteomics of organelle shadows at the example of mitochondria in chromatin data.

PubMed

Kustatscher, Georg; Grabowski, Piotr; Rappsilber, Juri

2016-02-01

Subcellular localization is an important aspect of protein function, but the protein composition of many intracellular compartments is poorly characterized. For example, many nuclear bodies are challenging to isolate biochemically and thus remain inaccessible to proteomics. Here, we explore covariation in proteomics data as an alternative route to subcellular proteomes. Rather than targeting a structure of interest biochemically, we target it by machine learning. This becomes possible by taking data obtained for one organelle and searching it for traces of another organelle. As an extreme example and proof-of-concept we predict mitochondrial proteins based on their covariation in published interphase chromatin data. We detect about ⅓ of the known mitochondrial proteins in our chromatin data, presumably most as contaminants. However, these proteins are not present at random. We show covariation of mitochondrial proteins in chromatin proteomics data. We then exploit this covariation by multiclassifier combinatorial proteomics to define a list of mitochondrial proteins. This list agrees well with different databases on mitochondrial composition. This benchmark test raises the possibility that, in principle, covariation proteomics may also be applicable to structures for which no biochemical isolation procedures are available. © 2015 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Activation of Human Peripheral Blood Eosinophils by Cytokines in a Comparative Time-Course Proteomic/Phosphoproteomic Study.

PubMed

Soman, Kizhake V; Stafford, Susan J; Pazdrak, Konrad; Wu, Zheng; Luo, Xuemei; White, Wendy I; Wiktorowicz, John E; Calhoun, William J; Kurosky, Alexander

2017-08-04

Activated eosinophils contribute to airway dysfunction and tissue remodeling in asthma and thus are considered to be important factors in asthma pathology. We report here comparative proteomic and phosphoproteomic changes upon activation of eosinophils using eight cytokines individually and in selected cytokine combinations in time-course reactions. Differential protein and phosphoprotein expressions were determined by mass spectrometry after 2-dimensional gel electrophoresis (2DGE) and by LC-MS/MS. We found that each cytokine-stimulation produced significantly different changes in the eosinophil proteome and phosphoproteome, with phosphoproteomic changes being more pronounced and having an earlier onset. Furthermore, we observed that IL-5, GM-CSF, and IL-3 showed the greatest change in protein expression and phosphorylation, and this expression differed markedly from those of the other five cytokines evaluated. Comprehensive univariate and multivariate statistical analyses were employed to evaluate the comparative results. We also monitored eosinophil activation using flow cytometry (FC) analysis of CD69. In agreement with our proteomic studies, FC indicated that IL-5, GM-CSF, and IL-3 were more effective than the other five cytokines studied in stimulating a cell surface CD69 increase indicative of eosinophil activation. Moreover, selected combinations of cytokines revealed proteomic patterns with many proteins in common with single cytokine expression patterns but also showed a greater effect of the two cytokines employed, indicating a more complex signaling pathway that was reflective of a more typical inflammatory pathology.

Functional insights from proteome-wide structural modeling of Treponema pallidum subspecies pallidum, the causative agent of syphilis.

PubMed

Houston, Simon; Lithgow, Karen Vivien; Osbak, Kara Krista; Kenyon, Chris Richard; Cameron, Caroline E

2018-05-16

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale. Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens. Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

A human protein atlas for normal and cancer tissues based on antibody proteomics.

PubMed

Uhlén, Mathias; Björling, Erik; Agaton, Charlotta; Szigyarto, Cristina Al-Khalili; Amini, Bahram; Andersen, Elisabet; Andersson, Ann-Catrin; Angelidou, Pia; Asplund, Anna; Asplund, Caroline; Berglund, Lisa; Bergström, Kristina; Brumer, Harry; Cerjan, Dijana; Ekström, Marica; Elobeid, Adila; Eriksson, Cecilia; Fagerberg, Linn; Falk, Ronny; Fall, Jenny; Forsberg, Mattias; Björklund, Marcus Gry; Gumbel, Kristoffer; Halimi, Asif; Hallin, Inga; Hamsten, Carl; Hansson, Marianne; Hedhammar, My; Hercules, Görel; Kampf, Caroline; Larsson, Karin; Lindskog, Mats; Lodewyckx, Wald; Lund, Jan; Lundeberg, Joakim; Magnusson, Kristina; Malm, Erik; Nilsson, Peter; Odling, Jenny; Oksvold, Per; Olsson, Ingmarie; Oster, Emma; Ottosson, Jenny; Paavilainen, Linda; Persson, Anja; Rimini, Rebecca; Rockberg, Johan; Runeson, Marcus; Sivertsson, Asa; Sköllermo, Anna; Steen, Johanna; Stenvall, Maria; Sterky, Fredrik; Strömberg, Sara; Sundberg, Mårten; Tegel, Hanna; Tourle, Samuel; Wahlund, Eva; Waldén, Annelie; Wan, Jinghong; Wernérus, Henrik; Westberg, Joakim; Wester, Kenneth; Wrethagen, Ulla; Xu, Lan Lan; Hober, Sophia; Pontén, Fredrik

2005-12-01

Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, approximately 400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

Impacts on silkworm larvae midgut proteomics by transgenic Trichoderma strain and analysis of glutathione S-transferase sigma 2 gene essential for anti-stress response of silkworm larvae.

PubMed

Li, Yingying; Dou, Kai; Gao, Shigang; Sun, Jianan; Wang, Meng; Fu, Kehe; Yu, Chuanjin; Wu, Qiong; Li, Yaqian; Chen, Jie

2015-08-03

Lepidoptera is a large order of insects that have major impacts on humans as agriculture pests. The midgut is considered an important target for insect control. In the present study, 10 up-regulated, 18 down-regulated, and one newly emerged protein were identified in the transgenic Trichoderma-treated midgut proteome. Proteins related to stress response, biosynthetic process, and metabolism process were further characterized through quantitative real-time PCR (qPCR). Of all the identified proteins, the glutathione S-transferase sigma 2 (GSTs2) gene displayed enhanced expression when larvae were fed with Trichoderma wild-type or transgenic strains. Down regulation of GSTs2 expression by RNA interference (RNAi) resulted in inhibition of silkworm growth when larvae were fed with mulberry leaves treated with the transgenic Trichoderma strain. Weight per larva decreased by 18.2%, 11.9%, and 10.7% in the untreated control, ddH2O, and GFP dsRNA groups, respectively, at 24h, while the weight decrease was higher at 42.4%, 28.8% and 32.4% at 72 h after treatment. Expression of glutathione S-transferase omega 2 (GSTo2) was also enhanced when larvae were fed with mulberry leaves treated with the transgenic Trichoderma strain. These results indicated that there was indeed correlation between enhanced expression of GSTs2 and the anti-stress response of silkworm larvae against Trichoderma. This study represents the first attempt at understanding the effects of transgenic organisms on the midgut proteomic changes in silkworm larvae. Our findings could not only broaden the biological control targets of insect at the molecular level, but also provide a theoretical foundation for biological safety evaluation of the transgenic Trichoderma strain. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterization of the effects of trace concentrations of graphene oxide on zebrafish larvae through proteomic and standard methods.

PubMed

Zou, Wei; Zhou, Qixing; Zhang, Xingli; Mu, Li; Hu, Xiangang

2018-09-15

The effects of graphene oxide (GO) carbon nanomaterials on ecosystems have been well characterized, but the toxicity of GO at predicted environmental concentrations to living organisms at the protein level remain largely unknown. In the present work, the adverse effects and mechanisms of GO at predicted environmental concentrations were evaluated by integrating proteomics and standard analyses for the first time. The abundances of 243 proteins, including proteins involved in endocytosis (e.g., cltcb, arf6, capzb and dnm1a), oxidative stress (e.g., gpx4b, sod2, and prdx1), cytoskeleton assembly (e.g., krt8, krt94, lmna and vim), mitochondrial function (e.g., ndufa10, ndufa8, cox5aa, and cox6b1), Ca 2+ handling (e.g., atp1b2a, atp1b1a, atp6v0a1b and ncx4a) and cardiac function (e.g., tpm4a, tpm2, tnni2a.1 and tnnt3b), were found to be notably altered in response to exposure 100 μg/L GO. The results revealed that GO caused malformation and mortality, likely through the downregulation of proteins related to actin filaments and formation of the cytoskeleton, and induced oxidative stress and mitochondrial disorders by altering the levels of antioxidant enzymes and proteins associated with the mitochondrial membrane respiratory chain. Exposure to GO also increased the heart rate of zebrafish larvae and induced pericardial edema, likely by changing the expression of proteins related to Ca 2+ balance and cardiac function. This study provides new proteomic-level insights into GO toxicity against aquatic organisms, which will greatly benefit our understanding of the bio-safety of GO and its toxicity at predicted environmental concentrations. Copyright © 2018 Elsevier Inc. All rights reserved.

A Comparison of Protein Extraction Methods Suitable for Gel-Based Proteomic Studies of Aphid Proteins

PubMed Central

Cilia, M.; Fish, T.; Yang, X.; Mclaughlin, M.; Thannhauser, T. W.

2009-01-01

Protein extraction methods can vary widely in reproducibility and in representation of the total proteome, yet there are limited data comparing protein isolation methods. The methodical comparison of protein isolation methods is the first critical step for proteomic studies. To address this, we compared three methods for isolation, purification, and solubilization of insect proteins. The aphid Schizaphis graminum, an agricultural pest, was the source of insect tissue. Proteins were extracted using TCA in acetone (TCA-acetone), phenol, or multi-detergents in a chaotrope solution. Extracted proteins were solubilized in a multiple chaotrope solution and examined using 1-D and 2-D electrophoresis and compared directly using 2-D Difference Gel Electrophoresis (2-D DIGE). Mass spectrometry was used to identify proteins from each extraction type. We were unable to ascribe the differences in the proteins extracted to particular physical characteristics, cell location, or biological function. The TCA-acetone extraction yielded the greatest amount of protein from aphid tissues. Each extraction method isolated a unique subset of the aphid proteome. The TCA-acetone method was explored further for its quantitative reliability using 2-D DIGE. Principal component analysis showed that little of the variation in the data was a result of technical issues, thus demonstrating that the TCA-acetone extraction is a reliable method for preparing aphid proteins for a quantitative proteomics experiment. These data suggest that although the TCA-acetone method is a suitable method for quantitative aphid proteomics, a combination of extraction approaches is recommended for increasing proteome coverage when using gel-based separation techniques. PMID:19721822

Proteomics analysis suggests broad functional changes in potato leaves triggered by phosphites and a complex indirect mode of action against Phytophthora infestans.

PubMed

Lim, Sanghyun; Borza, Tudor; Peters, Rick D; Coffin, Robert H; Al-Mughrabi, Khalil I; Pinto, Devanand M; Wang-Pruski, Gefu

2013-11-20

Phosphite (salts of phosphorous acid; Phi)-based fungicides are increasingly used in controlling oomycete pathogens, such as the late blight agent Phytophthora infestans. In plants, low amounts of Phi induce pathogen resistance through an indirect mode of action. We used iTRAQ-based quantitative proteomics to investigate the effects of phosphite on potato plants before and after infection with P. infestans. Ninety-three (62 up-regulated and 31 down-regulated) differentially regulated proteins, from a total of 1172 reproducibly identified proteins, were identified in the leaf proteome of Phi-treated potato plants. Four days post-inoculation with P. infestans, 16 of the 31 down-regulated proteins remained down-regulated and 42 of the 62 up-regulated proteins remained up-regulated, including 90% of the defense proteins. This group includes pathogenesis-related, stress-responsive, and detoxification-related proteins. Callose deposition and ultrastructural analyses of leaf tissues after infection were used to complement the proteomics approach. This study represents the first comprehensive proteomics analysis of the indirect mode of action of Phi, demonstrating broad effects on plant defense and plant metabolism. The proteomics data and the microscopy study suggest that Phi triggers a hypersensitive response that is responsible for induced resistance of potato leaves against P. infestans. Phosphie triggers complex functional changes in potato leaves that are responsible for the induced resistance against Phytophthora infestans. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Proteomic approach for identifying gonad differential proteins in the oyster (Crassostrea angulata) following food-chain contamination with HgCl2.

PubMed

Zhang, Qing-Hong; Huang, Lin; Zhang, Yong; Ke, Cai-Huan; Huang, He-Qing

2013-12-06

Hg discharged into the environmental waters can generally be bioaccumulated, transformed and transmited by living organisms, thus resulting in the formation of Hg-toxicity food chains. The pathway and toxicology of food chain contaminated with environmental Hg are rarely revealed by proteomics. Here, we showed that differential proteomics had the potential to understand reproduction toxicity mechanism in marine molluscs through the Hg-contaminated food chain. Hg bioaccumulation was found in every link of the HgCl2-Chlorella vulgaris-oyster-mice food chain. Morphological observations identified the lesions in both the oyster gonad and the mice ovary. Differential proteomics was used to study the mechanisms of Hg toxicity in the oyster gonad and to find some biomarkers of Hg contamination in food chain. Using 2-DE and MALDI-TOF/TOF MS, we identified 13 differential protein spots, of which six were up-regulated, six were down-regulated, while one was undecided. A portion of these differential proteins was further confirmed using real-time PCR and western blotting methods. Their major functions involved binding, protein translocation, catalysis, regulation of energy metabolism, reproductive functioning and structural molecular activity. Among these proteins, 14-3-3 protein, GTP binding protein, arginine kinase (AK) and 71kDa heat shock connate protein (HSCP 71) are considered to be suitable biomarkers of environmental Hg contamination. Furthermore, we established the gene correspondence, responding to Hg reproductive toxicity, between mouse and oyster, and then used real-time PCR to analyze mRNA differential expression of the corresponding genes in mice. The results indicated that the mechanism of Hg reproductive toxicity in mouse was similar to that in oyster. We suggest that the proteomics would be further developed in application research of food safety including toxicological mechanism. It is well known that mercury (Hg) is one of the best toxic metal elements in nature. The research reports as previously described indicated that multiple mercury compounds can directly contaminate the aquatic animals by flowing of water body and through the diffusion of air. The pollution sources of the mercury compounds in marine water were mainly found from the pathways such as steam power plant and mineral exploitation which are located on the inshore. Of note, after being released into environmental waters, mercury compounds undergo the processes of bioaccumulation, transformation and transmission in living organisms, thus resulting in the multiple forms of Hg found in Hg-toxicity food chains, and among them, methyl mercury (MeHg) showing the high toxic characteristics is the main form of Hg. The abundant reports indicated that the metal salts were easily found within the various organs of the animals, but it is difficult to judge the level of its perniciousness according to its content only in vivo. Here, the algae to have been contaminated by the mercury compounds have the ability for contaminating both the fish and shellfish as food pathway quickly. If these fish and shellfish edible as food will be taken by human, they will further affect the human health badly. However, studies about their perniciousness are rarely reported, especially in using proteomics. The oysters as normal food are largely consumed in Southern China, especially in Xiamen City. Similarly, a pathway question that the contaminated oysters can effect on the human health such as cancer is unclear or poorly understood. Here, we showed that an analytical technology such as differential proteomics has potential to understand toxicity mechanism induced by Hg-contamination through the food pathway. It is for reason that the oyster proteomics including relative analytical methods have been used to reveal the contaminant level and to determine its perniciousness using toxic algae as food. Here, we also indicated that the research here shows great significance for both analysis of food safety and toxicology of the metal compounds. In addition, a few biomarkers have shown their strong potential for monitoring the level of Hg pollution in sea in the manuscript and gene correspondence between mouse and oyster, the two contiguous links of the Hg-contaminated food chain, was further investigated to better illustrate our finding in the analysis of food chain proteomics. Moreover, similar research work is rarely reported compared to the current proteomic development, showing that a lot of novel results by proteomic methods in the manuscript have strong potential for developing the new area of food chain proteomics. © 2013 Elsevier B.V. All rights reserved.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W.; Moritz, Robert L.

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W; Moritz, Robert L

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review.

PubMed

Nicolaou, Orthodoxia; Kousios, Andreas; Hadjisavvas, Andreas; Lauwerys, Bernard; Sokratous, Kleitos; Kyriacou, Kyriacos

2017-05-01

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry-based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Twenty-five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers.

PubMed

Runau, Franscois; Arshad, Ali; Isherwood, John; Norris, Leonie; Howells, Lynne; Metcalfe, Matthew; Dennison, Ashley

2015-06-01

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results. © 2015 American Society for Parenteral and Enteral Nutrition.

[PROTEOMIC ANALYSIS OF ADAPTIVE MECHANISMS TO SALINITY STRESS IN MARINE GASTROPODS LITTORINA SAXATILIS].

PubMed

Muraeva, O A; Maltseva, A L; Mikhailova, N A; Granovitch, A I

2015-01-01

Salinity is one of the most important abiotic environmental factors affecting marine animals. If salinity deviate from optimum, adaptive mechanisms switch on to maintain organism's physiological activity. In this study, the reaction of the snails Littorina saxatilis from natural habitats and in response to experimental salinity decreasing was analyzed on proteomic level. The isolation of all snails inside their shells and gradually declining mortality was observed under acute experimental salinity decrease (down to 10 per hundred). Proteomic changes were evaluated in the surviving experimental mollusks compared to control individual using differential 2D gel-electrophoresis (DIGE) and subsequent LC-MS/MS-identification of proteins. Approximately 10% of analyzed proteins underwent up- or down regulation during the experiment. Proteins of folding, antioxidant response, intercellular matrix, cell adhesion, cell signaling and metabolic enzymes were identified among them. Proteome changes observed in experimental hypoosmotic stress partially reproduced in the proteomes of mollusks that live in conditions of natural freshening (estuaries). Possible mechanisms involved in the adaptation process of L. saxatilis individuals to hypo-osmotic stress are discussed.

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

PubMed Central

Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2016-01-01

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion. PMID:27472422

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

SILAC-Based Comparative Proteomic Analysis of Lysosomes from Mammalian Cells Using LC-MS/MS.

PubMed

Thelen, Melanie; Winter, Dominic; Braulke, Thomas; Gieselmann, Volkmar

2017-01-01

Mass spectrometry-based proteomics of lysosomal proteins has led to significant advances in understanding lysosomal function and pathology. The ever-increasing sensitivity and resolution of mass spectrometry in combination with labeling procedures which allow comparative quantitative proteomics can be applied to shed more light on the steadily increasing range of lysosomal functions. In addition, investigation of alterations in lysosomal protein composition in the many lysosomal storage diseases may yield further insights into the molecular pathology of these disorders. Here, we describe a protocol which allows to determine quantitative differences in the lysosomal proteome of cells which are genetically and/or biochemically different or have been exposed to certain stimuli. The method is based on stable isotope labeling of amino acids in cell culture (SILAC). Cells are exposed to superparamagnetic iron oxide particles which are endocytosed and delivered to lysosomes. After homogenization of cells, intact lysosomes are rapidly enriched by passing the cell homogenates over a magnetic column. Lysosomes are eluted after withdrawal of the magnetic field and subjected to mass spectrometry.

Integrated Vehicle-Based Safety Systems (IVBSS) Light Vehicle Field Operational Test Independent Evaluation

DOT National Transportation Integrated Search

2011-10-01

This report presents the methodology and results of the independent evaluation of a prototype integrated crash warning system for : light vehicles as part of the Integrated Vehicle-Based Safety Systems initiative of the United States Department of : ...

jPOSTrepo: an international standard data repository for proteomes

PubMed Central

Okuda, Shujiro; Watanabe, Yu; Moriya, Yuki; Kawano, Shin; Yamamoto, Tadashi; Matsumoto, Masaki; Takami, Tomoyo; Kobayashi, Daiki; Araki, Norie; Yoshizawa, Akiyasu C.; Tabata, Tsuyoshi; Sugiyama, Naoyuki; Goto, Susumu; Ishihama, Yasushi

2017-01-01

Major advancements have recently been made in mass spectrometry-based proteomics, yielding an increasing number of datasets from various proteomics projects worldwide. In order to facilitate the sharing and reuse of promising datasets, it is important to construct appropriate, high-quality public data repositories. jPOSTrepo (https://repository.jpostdb.org/) has successfully implemented several unique features, including high-speed file uploading, flexible file management and easy-to-use interfaces. This repository has been launched as a public repository containing various proteomic datasets and is available for researchers worldwide. In addition, our repository has joined the ProteomeXchange consortium, which includes the most popular public repositories such as PRIDE in Europe for MS/MS datasets and PASSEL for SRM datasets in the USA. Later MassIVE was introduced in the USA and accepted into the ProteomeXchange, as was our repository in July 2016, providing important datasets from Asia/Oceania. Accordingly, this repository thus contributes to a global alliance to share and store all datasets from a wide variety of proteomics experiments. Thus, the repository is expected to become a major repository, particularly for data collected in the Asia/Oceania region. PMID:27899654

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

The HUPO proteomics standards initiative--easing communication and minimizing data loss in a changing world.

PubMed

Orchard, Sandra; Hermjakob, Henning

2008-03-01

The amount of data currently being generated by proteomics laboratories around the world is increasing exponentially, making it ever more critical that scientists are able to exchange, compare and retrieve datasets when re-evaluation of their original conclusions becomes important. Only a fraction of this data is published in the literature and important information is being lost every day as data formats become obsolete. The Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) was tasked with the creation of data standards and interchange formats to allow both the exchange and storage of such data irrespective of the hardware and software from which it was generated. This article will provide an update on the work of this group, the creation and implementation of these standards and the standards-compliant data repositories being established as result of their efforts.

MassSieve: Panning MS/MS peptide data for proteins

PubMed Central

Slotta, Douglas J.; McFarland, Melinda A.; Markey, Sanford P.

2010-01-01

We present MassSieve, a Java-based platform for visualization and parsimony analysis of single and comparative LC-MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC-MS/MS-based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments. PMID:20564260

Comparative Testis Tissue Proteomics Using 2-Dye Versus 3-Dye DIGE Analysis.

PubMed

Holland, Ashling

2018-01-01

Comparative tissue proteomics aims to analyze alterations of the proteome in response to a stimulus. Two-dimensional difference gel electrophoresis (2D-DIGE) is a modified and advanced form of 2D gel electrophoresis. DIGE is a powerful biochemical method that compares two or three protein samples on the same analytical gel, and can be used to establish differentially expressed protein levels between healthy normal and diseased pathological tissue sample groups. Minimal DIGE labeling can be used via a 2-dye system with Cy3 and Cy5 or a 3-dye system with Cy2, Cy3, and Cy5 to fluorescently label samples with CyDye flours pre-electrophoresis. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization. This form of quantitative high-resolution proteomics facilitates the comparative analysis and evaluation of tissue protein compositions. Comparing tissue groups under different conditions is crucially important for advancing the biomedical field by characterization of cellular processes, understanding pathophysiological development and tissue biomarker discovery. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of 2-dye and 3-dye DIGE minimal labeling.

Development of Best practices document for Peptide Standards | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Assay Development Working Group (ADWG) of the CPTAC Program is currently drafting a document to propose best practices for generation, quantification, storage, and handling of peptide standards used for mass spectrometry-based assays, as well as interpretation of quantitative proteomic data based on peptide standards. The ADWG is seeking input from commercial entities that provide peptide standards for mass spectrometry-based assays or that perform amino acid analysis.

Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance.

PubMed

Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P

2010-01-01

Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.

Open source libraries and frameworks for mass spectrometry based proteomics: A developer's perspective☆

PubMed Central

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23467006

Ultrahigh pressure fast size exclusion chromatography for top-down proteomics.

PubMed

Chen, Xin; Ge, Ying

2013-09-01

Top-down MS-based proteomics has gained a solid growth over the past few years but still faces significant challenges in the LC separation of intact proteins. In top-down proteomics, it is essential to separate the high mass proteins from the low mass species due to the exponential decay in S/N as a function of increasing molecular mass. SEC is a favored LC method for size-based separation of proteins but suffers from notoriously low resolution and detrimental dilution. Herein, we reported the use of ultrahigh pressure (UHP) SEC for rapid and high-resolution separation of intact proteins for top-down proteomics. Fast separation of intact proteins (6-669 kDa) was achieved in < 7 min with high resolution and high efficiency. More importantly, we have shown that this UHP-SEC provides high-resolution separation of intact proteins using a MS-friendly volatile solvent system, allowing the direct top-down MS analysis of SEC-eluted proteins without an additional desalting step. Taken together, we have demonstrated that UHP-SEC is an attractive LC strategy for the size separation of proteins with great potential for top-down proteomics. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

PubMed

Kakourou, Alexia; Vach, Werner; Nicolardi, Simone; van der Burgt, Yuri; Mertens, Bart

2016-10-01

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.

PubMed

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Next-Generation Proteomics and Its Application to Clinical Breast Cancer Research.

PubMed

Mardamshina, Mariya; Geiger, Tamar

2017-10-01

Proteomics technology aims to map the protein landscapes of biological samples, and it can be applied to a variety of samples, including cells, tissues, and body fluids. Because the proteins are the main functional molecules in the cells, their levels reflect much more accurately the cellular phenotype and the regulatory processes within them than gene levels, mutations, and even mRNA levels. With the advancement in the technology, it is possible now to obtain comprehensive views of the biological systems and to study large patient cohorts in a streamlined manner. In this review we discuss the technological advancements in mass spectrometry-based proteomics, which allow analysis of breast cancer tissue samples, leading to the first large-scale breast cancer proteomics studies. Furthermore, we discuss the technological developments in blood-based biomarker discovery, which provide the basis for future development of assays for routine clinical use. Although these are only the first steps in implementation of proteomics into the clinic, extensive collaborative work between these worlds will undoubtedly lead to major discoveries and advances in clinical practice. Copyright © 2017 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Clinical diagnosis and typing of systemic amyloidosis in subcutaneous fat aspirates by mass spectrometry-based proteomics

PubMed Central

Vrana, Julie A.; Theis, Jason D.; Dasari, Surendra; Mereuta, Oana M.; Dispenzieri, Angela; Zeldenrust, Steven R.; Gertz, Morie A.; Kurtin, Paul J.; Grogg, Karen L.; Dogan, Ahmet

2014-01-01

Examination of abdominal subcutaneous fat aspirates is a practical, sensitive and specific method for the diagnosis of systemic amyloidosis. Here we describe the development and implementation of a clinical assay using mass spectrometry-based proteomics to type amyloidosis in subcutaneous fat aspirates. First, we validated the assay comparing amyloid-positive (n=43) and -negative (n=26) subcutaneous fat aspirates. The assay classified amyloidosis with 88% sensitivity and 96% specificity. We then implemented the assay as a clinical test, and analyzed 366 amyloid-positive subcutaneous fat aspirates in a 4-year period as part of routine clinical care. The assay had a sensitivity of 90%, and diverse amyloid types, including immunoglobulin light chain (74%), transthyretin (13%), serum amyloid A (%1), gelsolin (1%), and lysozyme (1%), were identified. Using bioinformatics, we identified a universal amyloid proteome signature, which has high sensitivity and specificity for amyloidosis similar to that of Congo red staining. We curated proteome databases which included variant proteins associated with systemic amyloidosis, and identified clonotypic immunoglobulin variable gene usage in immunoglobulin light chain amyloidosis, and the variant peptides in hereditary transthyretin amyloidosis. In conclusion, mass spectrometry-based proteomic analysis of subcutaneous fat aspirates offers a powerful tool for the diagnosis and typing of systemic amyloidosis. The assay reveals the underlying pathogenesis by identifying variable gene usage in immunoglobulin light chains and the variant peptides in hereditary amyloidosis. PMID:24747948

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

PubMed

Jarnuczak, Andrew F; Lee, Dave C H; Lawless, Craig; Holman, Stephen W; Eyers, Claire E; Hubbard, Simon J

2016-09-02

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Analysis of School Food Safety Programs Based on HACCP Principles

ERIC Educational Resources Information Center

Roberts, Kevin R.; Sauer, Kevin; Sneed, Jeannie; Kwon, Junehee; Olds, David; Cole, Kerri; Shanklin, Carol

2014-01-01

Purpose/Objectives: The purpose of this study was to determine how school districts have implemented food safety programs based on HACCP principles. Specific objectives included: (1) Evaluate how schools are implementing components of food safety programs; and (2) Determine foodservice employees food-handling practices related to food safety.…

Evaluation of Vacuum Blasting and Heat Guns as Methods for Abating Lead- Based Paint on Buildings

DTIC Science & Technology

1993-09-01

INCOMPATIBILITY - Contact with powerful oxidizing agents such as FLUORINE, CHLORINE TRIFLUORIDE , MANGANESE TRIOXIDE, OXYGEN DIFLUORIDE, MANGANESE...investigating new technologies for lead-based paint abatement. This research evaluates the effectiveness , safety, LEC1L•.T• and cost of vacuum abrasive...paint abatement. This research evaluates the effectiveness , safety, and cost of vacuum abrasive units and heat guns as methods of removing lead-based

Proteomics for understanding miRNA biology

PubMed Central

Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh

2013-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164

Ultrasonic-based membrane aided sample preparation of urine proteomes.

PubMed

Jesus, Jemmyson Romário; Santos, Hugo M; López-Fernández, H; Lodeiro, Carlos; Arruda, Marco Aurélio Zezzi; Capelo, J L

2018-02-01

A new ultrafast ultrasonic-based method for shotgun proteomics as well as label-free protein quantification in urine samples is developed. The method first separates the urine proteins using nitrocellulose-based membranes and then proteins are in-membrane digested using trypsin. The enzymatic digestion process is accelerated from overnight to four minutes using a sonoreactor ultrasonic device. Overall, the sample treatment pipeline comprising protein separation, digestion and identification is done in just 3h. The process is assessed using urine of healthy volunteers. The method shows that male can be differentiated from female using the protein content of urine in a fast, easy and straightforward way. 232 and 226 proteins are identified in urine of male and female, respectively. From this, 162 are common to both genders, whilst 70 are unique to male and 64 to female. From the 162 common proteins, 13 are present at levels statistically different (p < 0.05). The method matches the analytical minimalism concept as outlined by Halls, as each stage of this analysis is evaluated to minimize the time, cost, sample requirement, reagent consumption, energy requirements and production of waste products. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of Native Protein Complexes and Protein Isoform Variation Using Size-fractionation-based Quantitative Proteomics*

PubMed Central

Kirkwood, Kathryn J.; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I.

2013-01-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community. PMID:24043423

Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics.

PubMed

Kirkwood, Kathryn J; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I

2013-12-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community.

Toxicogenomic analysis of N-nitrosomorpholine induced changes in rat liver: Comparison of genomic and proteomic responses and anchoring to histopathological parameters

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

Oberemm, A., E-mail: axel.oberemm@bfr.bund.d; Ahr, H.-J.; Bannasch, P.

2009-12-01

A common animal model of chemical hepatocarcinogenesis was used to examine the utility of transcriptomic and proteomic data to identify early biomarkers related to chemically induced carcinogenesis. N-nitrosomorpholine, a frequently used genotoxic model carcinogen, was applied via drinking water at 120 mg/L to male Wistar rats for 7 weeks followed by an exposure-free period of 43 weeks. Seven specimens of each treatment group (untreated control and 120 mg/L N-nitrosomorpholine in drinking water) were sacrificed at nine time points during and after N-nitrosomorpholine treatment. Individual samples from the liver were prepared for histological and toxicogenomic analyses. For histological detection of preneoplasticmore » and neoplastic tissue areas, sections were stained using antibodies against the placental form of glutathione-S-transferase (GST-P). Gene and protein expression profiles of liver tissue homogenates were analyzed using RG-U34A Affymetrix rat gene chips and two-dimensional gel electrophoresis-based proteomics, respectively. In order to compare results obtained by histopathology, transcriptomics and proteomics, GST-P-stained liver sections were evaluated morphometrically, which revealed a parallel time course of the area fraction of preneoplastic lesions and gene plus protein expression patterns. On the transcriptional level, an increase of hepatic GST-P expression was detectable as early as 3 weeks after study onset. Comparing deregulated genes and proteins, eight species were identified which showed a corresponding expression profile on both expression levels. Functional analysis suggests that these genes and corresponding proteins may be useful as biomarkers of early hepatocarcinogenesis.« less

Proteomic analysis of Rhodotorula mucilaginosa: dealing with the issues of a non-conventional yeast.

PubMed

Addis, Maria Filippa; Tanca, Alessandro; Landolfo, Sara; Abbondio, Marcello; Cutzu, Raffaela; Biosa, Grazia; Pagnozzi, Daniela; Uzzau, Sergio; Mannazzu, Ilaria

2016-08-01

Red yeasts ascribed to the species Rhodotorula mucilaginosa are gaining increasing attention, due to their numerous biotechnological applications, spanning carotenoid production, liquid bioremediation, heavy metal biotransformation and antifungal and plant growth-promoting actions, but also for their role as opportunistic pathogens. Nevertheless, their characterization at the 'omic' level is still scarce. Here, we applied different proteomic workflows to R. mucilaginosa with the aim of assessing their potential in generating information on proteins and functions of biotechnological interest, with a particular focus on the carotenogenic pathway. After optimization of protein extraction, we tested several gel-based (including 2D-DIGE) and gel-free sample preparation techniques, followed by tandem mass spectrometry analysis. Contextually, we evaluated different bioinformatic strategies for protein identification and interpretation of the biological significance of the dataset. When 2D-DIGE analysis was applied, not all spots returned a unambiguous identification and no carotenogenic enzymes were identified, even upon the application of different database search strategies. Then, the application of shotgun proteomic workflows with varying levels of sensitivity provided a picture of the information depth that can be reached with different analytical resources, and resulted in a plethora of information on R. mucilaginosa metabolism. However, also in these cases no proteins related to the carotenogenic pathway were identified, thus indicating that further improvements in sequence databases and functional annotations are strictly needed for increasing the outcome of proteomic analysis of this and other non-conventional yeasts. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients.

PubMed

Mu, Jun; Yang, Yongtao; Chen, Jin; Cheng, Ke; Li, Qi; Wei, Yongdong; Zhu, Dan; Shao, Weihua; Zheng, Peng; Xie, Peng

2015-10-30

Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

Analysis of soybean tissue culture protein dynamics using difference gel electrophoresis.

PubMed

Miernyk, Ján A; Jett, Alissa A; Johnston, Mark L

2016-01-01

Excised hypocotyls from developing soybean (Glycine max (L.) merr. cv. Jack) were cultivated on agar-solidified medium until callus formed. The calli were then propagated in liquid medium until stable, relatively uniform, finely-divided suspension cultures were obtained. Cells were typically transferred to fresh medium at 7-day intervals. Cultures were harvested by filtration five days (early log phase) or eight days (late log phase) after transfer. In order to evaluate dynamic changes, both intracellular and extracellular proteins were analyzed by 2-dimensional difference gel electrophoresis. Selected spots were subjected to in-gel tryptic-digestion and the resultant peptides were analyzed by nLC-MS/MS. In follow-up studies gel-free shot-gun analyses led to identification of 367 intracellular proteins and 188 extracellular proteins. The significance of the described research is two-fold. First a gel-based proteomics method was applied to the study of the dynamics of the secretome (extracellular proteins). Second, results of a shot-gun non-gel based proteomic survey of both cellular and extracellular proteins are presented. Published by Elsevier B.V.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics.

PubMed

Scifo, Enzo; Calza, Giulio; Fuhrmann, Martin; Soliymani, Rabah; Baumann, Marc; Lalowski, Maciej

2017-06-01

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

PubMed Central

Xu, Huajun; Zheng, Xiaojiao; Jia, Wei; Yin, Shankai

2015-01-01

Abstract Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA. PMID:26448002

Why proteomics is not the new genomics and the future of mass spectrometry in cell biology.

PubMed

Sidoli, Simone; Kulej, Katarzyna; Garcia, Benjamin A

2017-01-02

Mass spectrometry (MS) is an essential part of the cell biologist's proteomics toolkit, allowing analyses at molecular and system-wide scales. However, proteomics still lag behind genomics in popularity and ease of use. We discuss key differences between MS-based -omics and other booming -omics technologies and highlight what we view as the future of MS and its role in our increasingly deep understanding of cell biology. © 2017 Sidoli et al.

SearchGUI: A Highly Adaptable Common Interface for Proteomics Search and de Novo Engines.

PubMed

Barsnes, Harald; Vaudel, Marc

2018-05-25

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

Does water stress promote the proteome-wide adjustment of intrinsically disordered proteins in plants?

PubMed

Zamora-Briseño, Jesús Alejandro; Reyes-Hernández, Sandi Julissa; Zapata, Luis Carlos Rodríguez

2018-06-02

Plant response to water stress involves the activation of mechanisms expected to help them cope with water scarcity. Among these mechanisms, proteome-wide adjustment is well known. This includes actions to save energy, protect cellular and molecular components, and maintain vital functions of the cell. Intrinsically disordered proteins, which are proteins without a rigid three-dimensional structure, are seen as emerging multifunctional cellular components of proteomes. They are highly abundant in eukaryotic proteomes, and numerous functions for these proteins have been proposed. Here, we discuss several reasons why the collection of intrinsically disordered proteins in a proteome (disordome) could be subjected to an active regulation during conditions of water scarcity in plants. We also discuss the potential misinterpretations of disordome content estimations made so far due to bias-prone data and the need for reliable analysis based on experimental data in order to acknowledge the plasticity nature of the disordome.

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences

PubMed Central

Holmes, Christina; Carlson, Siobhan M.; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-01

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics. PMID:27134568

Automation, parallelism, and robotics for proteomics.

PubMed

Alterovitz, Gil; Liu, Jonathan; Chow, Jijun; Ramoni, Marco F

2006-07-01

The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences.

PubMed

Holmes, Christina; Carlson, Siobhan M; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-02

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics.

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

Universal Solid-phase Reversible Sample-Prep for Concurrent Proteome and N-glycome Characterization

PubMed Central

Zhou, Hui; Morley, Samantha; Kostel, Stephen; Freeman, Michael R.; Joshi, Vivek; Brewster, David; Lee, Richard S.

2017-01-01

SUMMARY We describe a novel Solid-phase Reversible Sample-Prep (SRS) platform, which enables rapid sample preparation for concurrent proteome and N-glycome characterization by mass spectrometry. SRS utilizes a uniquely functionalized, silica-based bead that has strong affinity toward proteins with minimal-to-no affinity for peptides and other small molecules. By leveraging the inherent size difference between, SRS permits high-capacity binding of proteins, rapid removal of small molecules (detergents, metabolites, salts, etc.), extensive manipulation including enzymatic and chemical treatments on beads-bound proteins, and easy recovery of N-glycans and peptides. The efficacy of SRS was evaluated in a wide range of biological samples including single glycoprotein, whole cell lysate, murine tissues, and human urine. To further demonstrate the SRS platform, we coupled a quantitative strategy to SRS to investigate the differences between DU145 prostate cancer cells and its DIAPH3-silenced counterpart. Our previous studies suggested that DIAPH3 silencing in DU145 prostate cancer cells induced transition to an amoeboid phenotype that correlated with tumor progression and metastasis. In this analysis we identified distinct proteomic and N-glycomic alterations between the two cells. Intriguingly, a metastasis-associated tyrosine kinase receptor ephrin-type-A receptor (EPHA2) was highly upregulated in DIAPH3-silenced cells, indicating underling connection between EPHA2 and DIAPH3. Moreover, distinct alterations in the N-glycome were identified, suggesting a cross-link between DIAPH3 and glycosyltransferase networks. Overall, SRS is an enabling universal sample preparation strategy that is not size limited and has the capability to efficiently prepare and clean peptides and N-glycans concurrently from nearly all sample types. Conceptually, SRS can be utilized for the analysis of other posttranslational modifications, and the unique surface chemistry can be further transformed for high-throughput automation. The technical simplicity, robustness, and modularity of SRS make it a highly promising technology with great potential in proteomic-based research. PMID:26791391

Overgrazing induces alterations in the hepatic proteome of sheep (Ovis aries): an iTRAQ-based quantitative proteomic analysis.

PubMed

Ren, Weibo; Hou, Xiangyang; Wang, Yuqing; Badgery, Warwick; Li, Xiliang; Ding, Yong; Guo, Huiqin; Wu, Zinian; Hu, Ningning; Kong, Lingqi; Chang, Chun; Jiang, Chao; Zhang, Jize

2016-01-01

The degradation of the steppe of Inner Mongolia, due to overgrazing, has resulted in ecosystem damage as well as extensive reductions in sheep production. The growth performance of sheep is greatly reduced because of overgrazing, which triggers massive economic losses every year. The liver is an essential organ that has very important roles in multiple functions, such as nutrient metabolism, immunity and others, which are closely related to animal growth. However, to our knowledge, no detailed studies have evaluated hepatic metabolism adaption in sheep due to overgrazing. The molecular mechanisms that underlie these effects remain unclear. In the present study, our group applied isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis to investigate changes in the protein profiles of sheep hepatic tissues when nutrition was reduced due to overgrazing (12.0 sheep/ha), with the goal of characterizing the molecular mechanisms of hepatic metabolism adaption in sheep in an overgrazing condition. The body weight daily gain of sheep was greatly decreased due to overgrazing. Overall, 41 proteins were found to be differentially abundant in the hepatic tissue between a light grazing group and an overgrazing group. Most of the differentially expressed proteins identified are involved in protein metabolism, transcriptional and translational regulation, and immune response. In particular, the altered abundance of kynureninase (KYNU) and HAL (histidine ammonia-lyase) involved in protein metabolic function, integrated with the changes of serum levels of blood urea nitrogen (BUN) and glucose (GLU), suggest that overgrazing triggers a shift in energy resources from carbohydrates to proteins, causing poorer nitrogen utilization efficiency. Altogether, these results suggest that the reductions in animal growth induced by overgrazing are associated with liver proteomic changes, especially the proteins involved in nitrogen compounds metabolism and immunity. This provides new information that can be used for nutritional supplementation to improve the growth performance of sheep in an overgrazing condition.

ProteoSign: an end-user online differential proteomics statistical analysis platform.

PubMed

Efstathiou, Georgios; Antonakis, Andreas N; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Divanach, Peter; Trudgian, David C; Thomas, Benjamin; Papanikolaou, Nikolas; Aivaliotis, Michalis; Acuto, Oreste; Iliopoulos, Ioannis

2017-07-03

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Comparative analysis of cerebrospinal fluid from the meningo-encephalitic stage of T. b. gambiense and rhodesiense sleeping sickness patients using TMT quantitative proteomics.

PubMed

Tiberti, Natalia; Sanchez, Jean-Charles

2015-09-01

The quantitative proteomics data here reported are part of a research article entitled "Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense", published by Tiberti et al., 2015. Transl. Proteomics 6, 1-9. Sleeping sickness (human African trypanosomiasis - HAT) is a deadly neglected tropical disease affecting mainly rural communities in sub-Saharan Africa. This parasitic disease is caused by the Trypanosoma brucei (T. b.) parasite, which is transmitted to the human host through the bite of the tse-tse fly. Two parasite sub-species, T. b. rhodesiense and T. b. gambiense, are responsible for two clinically different and geographically separated forms of sleeping sickness. The objective of the present study was to characterise and compare the cerebrospinal fluid (CSF) proteome of stage 2 (meningo-encephalitic stage) HAT patients suffering from T. b. gambiense or T. b. rhodesiense disease using high-throughput quantitative proteomics and the Tandem Mass Tag (TMT(®)) isobaric labelling. In order to evaluate the CSF proteome in the context of HAT pathophysiology, the protein dataset was then submitted to gene ontology and pathway analysis. Two significantly differentially expressed proteins (C-reactive protein and orosomucoid 1) were further verified on a larger population of patients (n=185) by ELISA, confirming the mass spectrometry results. By showing a predominant involvement of the acute immune response in rhodesiense HAT, the proteomics results obtained in this work will contribute to further understand the mechanisms of pathology occurring in HAT and to propose new biomarkers of potential clinical utility. The mass spectrometry raw data are available in the Pride Archive via ProteomeXchange through the identifier PXD001082.

Proteomic profile of serum of pregnant women carring a fetus with Down syndrome using nano uplc Q-tof ms/ms technology.

PubMed

López Uriarte, Graciela Arelí; Burciaga Flores, Carlos Horacio; Torres de la Cruz, Víctor Manuel; Medina Aguado, María Magdalena; Gómez Puente, Viviana Maricela; Romero Gutiérrez, Liliana Nayeli; Martínez de Villarreal, Laura Elia

2018-06-01

Prenatal diagnosis of Down syndrome (DS) is based on the calculated risk of maternal age, biochemical and ultrasonographic markers and recently by cfDNA. Differences in proteomic profiles may give an opportunity to find new biomarkers. Characterize proteome of serum of mothers carrying DS fetus. Blood serum samples of three groups of women were obtained, (a) 10 non-pregnant, (b) 10 pregnant with healthy fetus by ultrasound evaluation, (c) nine pregnant with DS fetus. Sample preparation was as follows: Albumin/IgG depletion, desalting, and trypsin digestion; the process was performed in nanoUPLC MS/MS. Data analysis was made with Mass Lynx 4.1 and ProteinLynx Global Server 3.0, peptide and protein recognition by MASCOT algorithm and UNIPROT-Swissprot database. Each group showed different protein profiles. Some proteins were shared between groups. Only sera from pregnant women showed proteins related to immune and clot pathways. Mothers with DS fetus had 42 specific proteins. We found a different serum protein profile in mothers carrying DS fetuses that do not reflect expression of genes in the extra chromosome. Further studies will be necessary to establish the role of these proteins in aneuploid fetus and analyze their possible use as potential biomarkers.

Proteomic analysis of processing by-products from canned and fresh tuna: identification of potentially functional food proteins.

PubMed

Sanmartín, Esther; Arboleya, Juan Carlos; Iloro, Ibon; Escuredo, Kepa; Elortza, Felix; Moreno, F Javier

2012-09-15

Proteomic approaches have been used to identify the main proteins present in processing by-products generated by the canning tuna-industry, as well as in by-products derived from filleting of skeletal red muscle of fresh tuna. Following fractionation by using an ammonium sulphate precipitation method, three proteins (tropomyosin, haemoglobin and the stress-shock protein ubiquitin) were identified in the highly heterogeneous and heat-treated material discarded by the canning-industry. Additionally, this fractionation method was successful to obtain tropomyosin of high purity from the heterogeneous starting material. By-products from skeletal red muscle of fresh tuna were efficiently fractionated to sarcoplasmic and myofibrillar fractions, prior to the identification based mainly on the combined searching of the peptide mass fingerprint (MALDI-TOF) and peptide fragment fingerprinting (MALDI LIFT-TOF/TOF) spectra of fifteen bands separated by 1D SDS-PAGE. Thus, the sarcoplasmic fraction contained myoglobin and several enzymes that are essential for efficient energy production, whereas the myofibrillar fraction had important contractile proteins, such as actin, tropomyosin, myosin or an isoform of the enzyme creatine kinase. Application of proteomic technologies has revealed new knowledge on the composition of important by-products from tuna species, enabling a better evaluation of their potential applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

MinOmics, an Integrative and Immersive Tool for Multi-Omics Analysis.

PubMed

Maes, Alexandre; Martinez, Xavier; Druart, Karen; Laurent, Benoist; Guégan, Sean; Marchand, Christophe H; Lemaire, Stéphane D; Baaden, Marc

2018-06-21

Proteomic and transcriptomic technologies resulted in massive biological datasets, their interpretation requiring sophisticated computational strategies. Efficient and intuitive real-time analysis remains challenging. We use proteomic data on 1417 proteins of the green microalga Chlamydomonas reinhardtii to investigate physicochemical parameters governing selectivity of three cysteine-based redox post translational modifications (PTM): glutathionylation (SSG), nitrosylation (SNO) and disulphide bonds (SS) reduced by thioredoxins. We aim to understand underlying molecular mechanisms and structural determinants through integration of redox proteome data from gene- to structural level. Our interactive visual analytics approach on an 8.3 m2 display wall of 25 MPixel resolution features stereoscopic three dimensions (3D) representation performed by UnityMol WebGL. Virtual reality headsets complement the range of usage configurations for fully immersive tasks. Our experiments confirm that fast access to a rich cross-linked database is necessary for immersive analysis of structural data. We emphasize the possibility to display complex data structures and relationships in 3D, intrinsic to molecular structure visualization, but less common for omics-network analysis. Our setup is powered by MinOmics, an integrated analysis pipeline and visualization framework dedicated to multi-omics analysis. MinOmics integrates data from various sources into a materialized physical repository. We evaluate its performance, a design criterion for the framework.

Mass Spectrometry Based Proteomic Analysis of Salivary Glands of Urban Malaria Vector Anopheles stephensi

PubMed Central

Vijay, Sonam

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes. PMID:25126571

Mass spectrometry based proteomic analysis of salivary glands of urban malaria vector Anopheles stephensi.

PubMed

Vijay, Sonam; Rawat, Manmeet; Sharma, Arun

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes.