Heterosis-associated proteome analyses of maize (Zea mays L.) seminal roots by quantitative label-free LC-MS.

PubMed

Marcon, Caroline; Lamkemeyer, Tobias; Malik, Waqas Ahmed; Ungrue, Denise; Piepho, Hans-Peter; Hochholdinger, Frank

2013-11-20

Heterosis is the superior performance of heterozygous F1-hybrid plants compared to their homozygous genetically distinct parents. Seminal roots are embryonic roots that play an important role during early maize (Zea mays L.) seedling development. In the present study the most abundant soluble proteins of 2-4cm seminal roots of the reciprocal maize F1-hybrids B73×Mo17 and Mo17×B73 and their parental inbred lines B73 and Mo17 were quantified by label-free LC-MS/MS. In total, 1918 proteins were detected by this shot-gun approach. Among those, 970 were represented by at least two peptides and were further analyzed. Eighty-five proteins displayed non-additive accumulation in at least one hybrid. The functional category protein metabolism was the most abundant class of non-additive proteins represented by 27 proteins. Within this category 16 of 17 non-additively accumulated ribosomal proteins showed high or above high parent expression in seminal roots. These results imply that an increased protein synthesis rate in hybrids might be related to the early manifestation of hybrid vigor in seminal roots. In the present study a shot-gun proteomics approach allowed for the identification of 1917 proteins and analysis of 970 seminal root proteins of maize that were represented by at least 2 peptides. The comparison of proteome complexity of reciprocal hybrids and their parental inbred lines indicates an increased protein synthesis rate in hybrids that may contribute to the early manifestation of heterosis in seminal roots. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

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

Computational approaches to protein inference in shotgun proteomics

PubMed Central

2012-01-01

Shotgun proteomics has recently emerged as a powerful approach to characterizing proteomes in biological samples. Its overall objective is to identify the form and quantity of each protein in a high-throughput manner by coupling liquid chromatography with tandem mass spectrometry. As a consequence of its high throughput nature, shotgun proteomics faces challenges with respect to the analysis and interpretation of experimental data. Among such challenges, the identification of proteins present in a sample has been recognized as an important computational task. This task generally consists of (1) assigning experimental tandem mass spectra to peptides derived from a protein database, and (2) mapping assigned peptides to proteins and quantifying the confidence of identified proteins. Protein identification is fundamentally a statistical inference problem with a number of methods proposed to address its challenges. In this review we categorize current approaches into rule-based, combinatorial optimization and probabilistic inference techniques, and present them using integer programing and Bayesian inference frameworks. We also discuss the main challenges of protein identification and propose potential solutions with the goal of spurring innovative research in this area. PMID:23176300

Less label, more free: approaches in label-free quantitative mass spectrometry.

PubMed

Neilson, Karlie A; Ali, Naveid A; Muralidharan, Sridevi; Mirzaei, Mehdi; Mariani, Michael; Assadourian, Gariné; Lee, Albert; van Sluyter, Steven C; Haynes, Paul A

2011-02-01

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PAnalyzer: a software tool for protein inference in shotgun proteomics.

PubMed

Prieto, Gorka; Aloria, Kerman; Osinalde, Nerea; Fullaondo, Asier; Arizmendi, Jesus M; Matthiesen, Rune

2012-11-05

Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and

PAnalyzer: A software tool for protein inference in shotgun proteomics

PubMed Central

2012-01-01

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an

Label-free Quantitative Protein Profiling of vastus lateralis Muscle During Human Aging*

PubMed Central

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers. PMID:24217021

Label-free quantitative protein profiling of vastus lateralis muscle during human aging.

PubMed

Théron, Laëtitia; Gueugneau, Marine; Coudy, Cécile; Viala, Didier; Bijlsma, Astrid; Butler-Browne, Gillian; Maier, Andrea; Béchet, Daniel; Chambon, Christophe

2014-01-01

Sarcopenia corresponds to the loss of muscle mass occurring during aging, and is associated with a loss of muscle functionality. Proteomic links the muscle functional changes with protein expression pattern. To better understand the mechanisms involved in muscle aging, we performed a proteomic analysis of Vastus lateralis muscle in mature and older women. For this, a shotgun proteomic method was applied to identify soluble proteins in muscle, using a combination of high performance liquid chromatography and mass spectrometry. A label-free protein profiling was then conducted to quantify proteins and compare profiles from mature and older women. This analysis showed that 35 of the 366 identified proteins were linked to aging in muscle. Most of the proteins were under-represented in older compared with mature women. We built a functional interaction network linking the proteins differentially expressed between mature and older women. The results revealed that the main differences between mature and older women were defined by proteins involved in energy metabolism and proteins from the myofilament and cytoskeleton. This is the first time that label-free quantitative proteomics has been applied to study of aging mechanisms in human skeletal muscle. This approach highlights new elements for elucidating the alterations observed during aging and may lead to novel sarcopenia biomarkers.

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 shotgun proteomic analysis of wild and domesticated Opuntia spp. species shows a metabolic adaptation through domestication.

PubMed

Pichereaux, Carole; Hernández-Domínguez, Eric E; Santos-Diaz, Maria Del Socorro; Reyes-Agüero, Antonio; Astello-García, Marizel; Guéraud, Françoise; Negre-Salvayre, Anne; Schiltz, Odile; Rossignol, Michel; Barba de la Rosa, Ana Paulina

2016-06-30

The Opuntia genus is widely distributed in America, but the highest richness of wild species are found in Mexico, as well as the most domesticated Opuntia ficus-indica, which is the most domesticated species and an important crop in agricultural economies of arid and semiarid areas worldwide. During domestication process, the Opuntia morphological characteristics were favored, such as less and smaller spines in cladodes and less seeds in fruits, but changes at molecular level are almost unknown. To obtain more insights about the Opuntia molecular changes through domestication, a shotgun proteomic analysis and database-dependent searches by homology was carried out. >1000 protein species were identified and by using a label-free quantitation method, the Opuntia proteomes were compared in order to identify differentially accumulated proteins among wild and domesticated species. Most of the changes were observed in glucose, secondary, and 1C metabolism, which correlate with the observed protein, fiber and phenolic compounds accumulation in Opuntia cladodes. Regulatory proteins, ribosomal proteins, and proteins related with response to stress were also observed in differential accumulation. These results provide new valuable data that will help to the understanding of the molecular changes of Opuntia species through domestication. Opuntia species are well adapted to dry and warm conditions in arid and semiarid regions worldwide, and they are highly productive plants showing considerable promises as an alternative food source. However, there is a gap regarding Opuntia molecular mechanisms that enable them to grow in extreme environmental conditions and how the domestication processes has changed them. In the present study, a shotgun analysis was carried out to characterize the proteomes of five Opuntia species selected by its domestication degree. Our results will help to a better understanding of proteomic features underlying the selection and specialization under

[Progress in stable isotope labeled quantitative proteomics methods].

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2013-06-01

Quantitative proteomics is an important research field in post-genomics era. There are two strategies for proteome quantification: label-free methods and stable isotope labeling methods which have become the most important strategy for quantitative proteomics at present. In the past few years, a number of quantitative methods have been developed, which support the fast development in biology research. In this work, we discuss the progress in the stable isotope labeling methods for quantitative proteomics including relative and absolute quantitative proteomics, and then give our opinions on the outlook of proteome quantification methods.

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

Mspire-Simulator: LC-MS shotgun proteomic simulator for creating realistic gold standard data.

PubMed

Noyce, Andrew B; Smith, Rob; Dalgleish, James; Taylor, Ryan M; Erb, K C; Okuda, Nozomu; Prince, John T

2013-12-06

The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets.

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

PubMed

Lan, Jiayi; Núñez Galindo, Antonio; Doecke, James; Fowler, Christopher; Martins, Ralph N; Rainey-Smith, Stephanie R; Cominetti, Ornella; Dayon, Loïc

2018-04-06

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP 2 ). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP 2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

PubMed

Weisser, Hendrik; Choudhary, Jyoti S

2017-08-04

Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known

Functional analysis of proteins and protein species using shotgun proteomics and linear mathematics.

PubMed

Hoehenwarter, Wolfgang; Chen, Yanmei; Recuenco-Munoz, Luis; Wienkoop, Stefanie; Weckwerth, Wolfram

2011-07-01

Covalent post-translational modification of proteins is the primary modulator of protein function in the cell. It greatly expands the functional potential of the proteome compared to the genome. In the past few years shotgun proteomics-based research, where the proteome is digested into peptides prior to mass spectrometric analysis has been prolific in this area. It has determined the kinetics of tens of thousands of sites of covalent modification on an equally large number of proteins under various biological conditions and uncovered a transiently active regulatory network that extends into diverse branches of cellular physiology. In this review, we discuss this work in light of the concept of protein speciation, which emphasizes the entire post-translationally modified molecule and its interactions and not just the modification site as the functional entity. Sometimes, particularly when considering complex multisite modification, all of the modified molecular species involved in the investigated condition, the protein species must be completely resolved for full understanding. We present a mathematical technique that delivers a good approximation for shotgun proteomics data.

Comparative shotgun proteomic analysis of Clostridium acetobutylicum from butanol fermentation using glucose and xylose

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

Sivagnanam, Kumaran; Raghavan, Vijaya G. S.; Shah, Manesh B

2011-01-01

Background: Butanol is a second generation biofuel produced by Clostridium acetobutylicum through acetonebutanol- ethanol (ABE) fermentation process. Shotgun proteomics provides a direct approach to study the whole proteome of an organism in depth. This paper focuses on shotgun proteomic profiling of C. acetobutylicum from ABE fermentation using glucose and xylose to understand the functional mechanisms of C. acetobutylicum proteins involved in butanol production. Results: We identified 894 different proteins in C. acetobutylicum from ABE fermentation process by two dimensional - liquid chromatography - tandem mass spectrometry (2D-LC-MS/MS) method. This includes 717 proteins from glucose and 826 proteins from the xylosemore » substrate. A total of 649 proteins were found to be common and 22 significantly differentially expressed proteins were identified between glucose and xylose substrates. Conclusion: Our results demonstrate that flagellar proteins are highly up-regulated with glucose compared to xylose substrate during ABE fermentation. Chemotactic activity was also found to be lost with the xylose substrate due to the absence of CheW and CheV proteins. This is the first report on the shotgun proteomic analysis of C. acetobutylicum ATCC 824 in ABE fermentation between glucose and xylose substrate from a single time data point and the number of proteins identified here is more than any other study performed on this organism up to this report.« less

A Bioinformatics Workflow for Variant Peptide Detection in Shotgun Proteomics*

PubMed Central

Li, Jing; Su, Zengliu; Ma, Ze-Qiang; Slebos, Robbert J. C.; Halvey, Patrick; Tabb, David L.; Liebler, Daniel C.; Pao, William; Zhang, Bing

2011-01-01

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics. PMID:21389108

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data.

PubMed

Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C

2009-02-24

Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.

Data from quantitative label free proteomics analysis of rat spleen.

PubMed

Dudekula, Khadar; Le Bihan, Thierry

2016-09-01

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

Targeted Feature Detection for Data-Dependent Shotgun Proteomics

PubMed Central

2017-01-01

Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards

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

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum—Phytophthora capsici Phytopathosystem

PubMed Central

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G.; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset

Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum-Phytophthora capsici Phytopathosystem.

PubMed

Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset

Comparison of the Membrane Proteome of Virulent Mycobacterium tuberculosis and the Attenuated Mycobacterium bovis BCG Vaccine Strain by Label-free Quantitative Proteomics

PubMed Central

Gunawardena, Harsha P.; Feltcher, Meghan E.; Wrobel, John A.; Gu, Sheng; Braunstein, Miriam; Chen, Xian

2015-01-01

The Mycobacterium tuberculosis (MTB) membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative (LFQ) proteomics, utilizing the area-under-curve (AUC) of the extracted ion chromatograms (XIC) of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2,203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least 2 fold, in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge we have generated the first comprehensive and high coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen. PMID:24093440

How to talk about protein-level false discovery rates in shotgun proteomics.

PubMed

The, Matthew; Tasnim, Ayesha; Käll, Lukas

2016-09-01

A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for errors in such lists is to enforce a preset threshold for the false discovery rate (FDR). Many consider protein-level FDRs a difficult and vague concept, as the measurement entities, spectra, are manifestations of peptides and not proteins. Here, we argue that this confusion is unnecessary and provide a framework on how to think about protein-level FDRs, starting from its basic principle: the null hypothesis. Specifically, we point out that two competing null hypotheses are used concurrently in today's protein inference methods, which has gone unnoticed by many. Using simulations of a shotgun proteomics experiment, we show how confusing one null hypothesis for the other can lead to serious discrepancies in the FDR. Furthermore, we demonstrate how the same simulations can be used to verify FDR estimates of protein inference methods. In particular, we show that, for a simple protein inference method, decoy models can be used to accurately estimate protein-level FDRs for both competing null hypotheses. © 2016 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics.

PubMed

Muth, Thilo; Rapp, Erdmann; Berven, Frode S; Barsnes, Harald; Vaudel, Marc

2016-01-01

Protein identification via database searches has become the gold standard in mass spectrometry based shotgun proteomics. However, as the quality of tandem mass spectra improves, direct mass spectrum sequencing gains interest as a database-independent alternative. In this chapter, the general principle of this so-called de novo sequencing is introduced along with pitfalls and challenges of the technique. The main tools available are presented with a focus on user friendly open source software which can be directly applied in everyday proteomic workflows.

Differential Cysteine Labeling and Global Label-Free Proteomics Reveals an Altered Metabolic State in Skeletal Muscle Aging

PubMed Central

2014-01-01

The molecular mechanisms underlying skeletal muscle aging and associated sarcopenia have been linked to an altered oxidative status of redox-sensitive proteins. Reactive oxygen and reactive nitrogen species (ROS/RNS) generated by contracting skeletal muscle are necessary for optimal protein function, signaling, and adaptation. To investigate the redox proteome of aging gastrocnemius muscles from adult and old male mice, we developed a label-free quantitative proteomic approach that includes a differential cysteine labeling step. The approach allows simultaneous identification of up- and downregulated proteins between samples in addition to the identification and relative quantification of the reversible oxidation state of susceptible redox cysteine residues. Results from muscles of adult and old mice indicate significant changes in the content of chaperone, glucose metabolism, and cytoskeletal regulatory proteins, including Protein DJ-1, cAMP-dependent protein kinase type II, 78 kDa glucose regulated protein, and a reduction in the number of redox-responsive proteins identified in muscle of old mice. Results demonstrate skeletal muscle aging causes a reduction in redox-sensitive proteins involved in the generation of precursor metabolites and energy metabolism, indicating a loss in the flexibility of the redox energy response. Data is available via ProteomeXchange with identifier PXD001054. PMID:25181601

Label-free quantitative proteomics to investigate strawberry fruit proteome changes under controlled atmosphere and low temperature storage.

PubMed

Li, Li; Luo, Zisheng; Huang, Xinhong; Zhang, Lu; Zhao, Pengyu; Ma, Hongyuan; Li, Xihong; Ban, Zhaojun; Liu, Xia

2015-04-29

To elucidate the mechanisms contributing to fruit responses to senescence and stressful environmental stimuli under low temperature (LT) and controlled atmosphere (CA) storage, a label-free quantitative proteomic investigation was conducted in strawberry (Fragaria ananassa, Duch. cv. 'Akihime'). Postharvest physiological quality traits including firmness, total soluble solids, total acidity, ascorbic acid and volatile production were characterized following storage under different conditions. The observed post-storage protein expression profiles may be associated with delayed senescence features in strawberry. A total of 454 proteins were identified in differentially treated strawberry fruits. Quantitative analysis, using normalized spectral counts, revealed 73 proteins common to all treatments, which formed three clusters in a hierarchical clustering analysis. The proteins spanned a range of functions in various metabolic pathways and networks involved in carbohydrate and energy metabolism, volatile biosynthesis, phenylpropanoid activity, stress response and protein synthesis, degradation and folding. After CA and LT storage, 16 (13) and 11 (17) proteins, respectively, were significantly increased (decreased) in abundance, while expression profile of 12 proteins was significantly changed by both CA and LT. To summarize, the differential variability of abundance in strawberry proteome, working in a cooperative manner, provided an overview of the biological processes that occurred during CA and LT storage. Controlled atmosphere storage at an optimal temperature is regarded to be an effective postharvest technology to delay fruit senescence and maintain fruit quality during shelf life. Nonetheless, little information on fruit proteomic changes under controlled atmosphere and/or low temperature storage is available. The significance of this paper is that it is the first study employing a label-free approach in the investigation of strawberry fruit response to

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation.

PubMed

Woo, Jongmin; Han, Dohyun; Wang, Joseph Injae; Park, Joonho; Kim, Hyunsoo; Kim, Youngsoo

2017-09-01

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for

Shotgun proteomics approach to characterizing the embryonic proteome of the silkworm, Bombyx mori, at labrum appearance stage.

PubMed

Li, J-Y; Chen, X; Hosseini Moghaddam, S H; Chen, M; Wei, H; Zhong, B-X

2009-10-01

The shotgun approach has gained considerable acknowledgement in recent years as a dominant strategy in proteomics. We observed a dramatic increase of specific protein spots in two-dimensional electrophoresis (2-DE) gels of the silkworm (Bombyx mori) embryo at labrum appearance, a characteristic stage during embryonic development of silkworm which is involved with temperature increase by silkworm raiser. We employed shotgun liquid chromatography tandem mass spectrometry (LC-MS/MS) technology to analyse the proteome of B. mori embryos at this stage. A total of 2168 proteins were identified with an in-house database. Approximately 47% of them had isoelectric point (pI) values distributed theoretically in the range pI 5-7 and approximately 60% of them had molecular weights of 15-45 kDa. Furthermore, 111 proteins had an pI greater than 10 and were difficult to separate by 2-DE. Many important functional proteins related to embryonic development, stress response, DNA transcription/translation, cell growth, proliferation and differentiation, organogenesis and reproduction were identified. Among them proteins related to nervous system development were noticeable. All known heat shock proteins (HSPs) were detected in this developmental stage of B. mori embryo. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed energetic metabolism at this stage. These results were expected to provide more information for proteomic monitoring of the insect embryo and better understanding of the spatiotemporal expression of genes during embryonic developmental processes.

A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2017-05-31

Label-free mass spectrometry (MS) has developed into an important tool applied in various fields of biological and life sciences. Several software exist to process the raw MS data into quantified protein abundances, including open source and commercial solutions. Each software includes a set of unique algorithms for different tasks of the MS data processing workflow. While many of these algorithms have been compared separately, a thorough and systematic evaluation of their overall performance is missing. Moreover, systematic information is lacking about the amount of missing values produced by the different proteomics software and the capabilities of different data imputation methods to account for them.In this study, we evaluated the performance of five popular quantitative label-free proteomics software workflows using four different spike-in data sets. Our extensive testing included the number of proteins quantified and the number of missing values produced by each workflow, the accuracy of detecting differential expression and logarithmic fold change and the effect of different imputation and filtering methods on the differential expression results. We found that the Progenesis software performed consistently well in the differential expression analysis and produced few missing values. The missing values produced by the other software decreased their performance, but this difference could be mitigated using proper data filtering or imputation methods. Among the imputation methods, we found that the local least squares (lls) regression imputation consistently increased the performance of the software in the differential expression analysis, and a combination of both data filtering and local least squares imputation increased performance the most in the tested data sets. © The Author 2017. Published by Oxford University Press.

How to talk about protein‐level false discovery rates in shotgun proteomics

PubMed Central

The, Matthew; Tasnim, Ayesha

2016-01-01

A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for errors in such lists is to enforce a preset threshold for the false discovery rate (FDR). Many consider protein‐level FDRs a difficult and vague concept, as the measurement entities, spectra, are manifestations of peptides and not proteins. Here, we argue that this confusion is unnecessary and provide a framework on how to think about protein‐level FDRs, starting from its basic principle: the null hypothesis. Specifically, we point out that two competing null hypotheses are used concurrently in today's protein inference methods, which has gone unnoticed by many. Using simulations of a shotgun proteomics experiment, we show how confusing one null hypothesis for the other can lead to serious discrepancies in the FDR. Furthermore, we demonstrate how the same simulations can be used to verify FDR estimates of protein inference methods. In particular, we show that, for a simple protein inference method, decoy models can be used to accurately estimate protein‐level FDRs for both competing null hypotheses. PMID:27503675

The temporal analysis of yeast exponential phase using shotgun proteomics as a fermentation monitoring technique

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

Huang, Eric L.; Orsat, Valerie; Shah, Manesh B

2012-01-01

System biology and bioprocess technology can be better understood using shotgun proteomics as a monitoring system during the fermentation. We demonstrated a shotgun proteomic method to monitor the temporal yeast proteome in early, middle and late exponential phases. Our study identified a total of 1389 proteins combining all 2D-LC-MS/MS runs. The temporal Saccharomyces cerevisiae proteome was enriched with proteolysis, radical detoxification, translation, one-carbon metabolism, glycolysis and TCA cycle. Heat shock proteins and proteins associated with oxidative stress response were found throughout the exponential phase. The most abundant proteins observed were translation elongation factors, ribosomal proteins, chaperones and glycolytic enzymes. Themore » high abundance of the H-protein of the glycine decarboxylase complex (Gcv3p) indicated the availability of glycine in the environment. We observed differentially expressed proteins and the induced proteins at mid-exponential phase were involved in ribosome biogenesis, mitochondria DNA binding/replication and transcriptional activator. Induction of tryptophan synthase (Trp5p) indicated the abundance of tryptophan during the fermentation. As fermentation progressed toward late exponential phase, a decrease in cell proliferation was implied from the repression of ribosomal proteins, transcription coactivators, methionine aminopeptidase and translation-associated proteins.« less

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.

RAPID AND AUTOMATED PROCESSING OF MALDI-FTICR/MS DATA FOR N-METABOLIC LABELING IN A SHOTGUN PROTEOMICS ANALYSIS.

PubMed

Jing, Li; Amster, I Jonathan

2009-10-15

Offline high performance liquid chromatography combined with matrix assisted laser desorption and Fourier transform ion cyclotron resonance mass spectrometry (HPLC-MALDI-FTICR/MS) provides the means to rapidly analyze complex mixtures of peptides, such as those produced by proteolytic digestion of a proteome. This method is particularly useful for making quantitative measurements of changes in protein expression by using (15)N-metabolic labeling. Proteolytic digestion of combined labeled and unlabeled proteomes produces complex mixtures that with many mass overlaps when analyzed by HPLC-MALDI-FTICR/MS. A significant challenge to data analysis is the matching of pairs of peaks which represent an unlabeled peptide and its labeled counterpart. We have developed an algorithm and incorporated it into a compute program which significantly accelerates the interpretation of (15)N metabolic labeling data by automating the process of identifying unlabeled/labeled peak pairs. The algorithm takes advantage of the high resolution and mass accuracy of FTICR mass spectrometry. The algorithm is shown to be able to successfully identify the (15)N/(14)N peptide pairs and calculate peptide relative abundance ratios in highly complex mixtures from the proteolytic digest of a whole organism protein extract.

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

Directed shotgun proteomics guided by saturated RNA-seq identifies a complete expressed prokaryotic proteome

PubMed Central

Omasits, Ulrich; Quebatte, Maxime; Stekhoven, Daniel J.; Fortes, Claudia; Roschitzki, Bernd; Robinson, Mark D.; Dehio, Christoph; Ahrens, Christian H.

2013-01-01

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ∼90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. PMID:23878158

Directed Shotgun Proteomics Guided by Saturated RNA-seq Identifies a Complete Expressed Prokaryotic Proteome

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

Omasits, U.; Quebatte, Maxime; Stekhoven, Daniel J.

2013-11-01

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, wemore » could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ~90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.« less

Data on xylem sap proteins from Mn- and Fe-deficient tomato plants obtained using shotgun proteomics.

PubMed

Ceballos-Laita, Laura; Gutierrez-Carbonell, Elain; Takahashi, Daisuke; Abadía, Anunciación; Uemura, Matsuo; Abadía, Javier; López-Millán, Ana Flor

2018-04-01

This article contains consolidated proteomic data obtained from xylem sap collected from tomato plants grown in Fe- and Mn-sufficient control, as well as Fe-deficient and Mn-deficient conditions. Data presented here cover proteins identified and quantified by shotgun proteomics and Progenesis LC-MS analyses: proteins identified with at least two peptides and showing changes statistically significant (ANOVA; p ≤ 0.05) and above a biologically relevant selected threshold (fold ≥ 2) between treatments are listed. The comparison between Fe-deficient, Mn-deficient and control xylem sap samples using a multivariate statistical data analysis (Principal Component Analysis, PCA) is also included. Data included in this article are discussed in depth in the research article entitled "Effects of Fe and Mn deficiencies on the protein profiles of tomato ( Solanum lycopersicum) xylem sap as revealed by shotgun analyses" [1]. This dataset is made available to support the cited study as well to extend analyses at a later stage.

A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.

PubMed

Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E

2013-12-16

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

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.

Label-free proteome profiling reveals developmental-dependent patterns in young barley grains.

PubMed

Kaspar-Schoenefeld, Stephanie; Merx, Kathleen; Jozefowicz, Anna Maria; Hartmann, Anja; Seiffert, Udo; Weschke, Winfriede; Matros, Andrea; Mock, Hans-Peter

2016-06-30

Due to its importance as a cereal crop worldwide, high interest in the determination of factors influencing barley grain quality exists. This study focusses on the elucidation of protein networks affecting early grain developmental processes. NanoLC-based separation coupled to label-free MS detection was applied to gain insights into biochemical processes during five different grain developmental phases (pre-storage until storage phase, 3days to 16days after flowering). Multivariate statistics revealed two distinct developmental patterns during the analysed grain developmental phases: proteins showed either highest abundance in the middle phase of development - in the transition phase - or at later developmental stages - within the storage phase. Verification of developmental patterns observed by proteomic analysis was done by applying hypothesis-driven approaches, namely Western Blot analysis and enzyme assays. High general metabolic activity of the grain with regard to protein synthesis, cell cycle regulation, defence against oxidative stress, and energy production via photosynthesis was observed in the transition phase. Proteins upregulated in the storage phase are related towards storage protein accumulation, and interestingly to the defence of storage reserves against pathogens. A mixed regulatory pattern for most enzymes detected in our study points to regulatory mechanisms at the level of protein isoforms. In-depth understanding of early grain developmental processes of cereal caryopses is of high importance as they influence final grain weight and quality. Our knowledge about these processes is still limited, especially on proteome level. To identify key mechanisms in early barley grain development, a label-free data-independent proteomics acquisition approach has been applied. Our data clearly show, that proteins either exhibit highest expression during cellularization and the switch to the storage phase (transition phase, 5-7 DAF), or during storage

Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function

PubMed Central

Grobei, Monica A.; Qeli, Ermir; Brunner, Erich; Rehrauer, Hubert; Zhang, Runxuan; Roschitzki, Bernd; Basler, Konrad; Ahrens, Christian H.; Grossniklaus, Ueli

2009-01-01

Pollen, the male gametophyte of flowering plants, represents an ideal biological system to study developmental processes, such as cell polarity, tip growth, and morphogenesis. Upon hydration, the metabolically quiescent pollen rapidly switches to an active state, exhibiting extremely fast growth. This rapid switch requires relevant proteins to be stored in the mature pollen, where they have to retain functionality in a desiccated environment. Using a shotgun proteomics approach, we unambiguously identified ∼3500 proteins in Arabidopsis pollen, including 537 proteins that were not identified in genetic or transcriptomic studies. To generate this comprehensive reference data set, which extends the previously reported pollen proteome by a factor of 13, we developed a novel deterministic peptide classification scheme for protein inference. This generally applicable approach considers the gene model–protein sequence–protein accession relationships. It allowed us to classify and eliminate ambiguities inherently associated with any shotgun proteomics data set, to report a conservative list of protein identifications, and to seamlessly integrate data from previous transcriptomics studies. Manual validation of proteins unambiguously identified by a single, information-rich peptide enabled us to significantly reduce the false discovery rate, while keeping valuable identifications of shorter and lower abundant proteins. Bioinformatic analyses revealed a higher stability of pollen proteins compared to those of other tissues and implied a protein family of previously unknown function in vesicle trafficking. Interestingly, the pollen proteome is most similar to that of seeds, indicating physiological similarities between these developmentally distinct tissues. PMID:19546170

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

PubMed

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gel-free/label-free proteomic, photosynthetic, and biochemical analysis of cowpea (Vigna unguiculata [L.] Walp.) resistance against Cowpea severe mosaic virus (CPSMV).

PubMed

Varela, Anna Lidia N; Komatsu, Setsuko; Wang, Xin; Silva, Rodolpho G G; Souza, Pedro Filho N; Lobo, Ana Karla M; Vasconcelos, Ilka M; Silveira, Joaquim A G; Oliveira, Jose T A

2017-06-23

Cowpea severe mosaic virus (CPSMV) causes significant losses in cowpea (Vigna unguiculata) production. In this present study biochemical, physiological, and proteomic analysis were done to identify pathways and defense proteins that are altered during the incompatible interaction between the cowpea genotype BRS-Marataoã and CPSMV. The leaf protein extracts from mock- (MI) and CPSMV-inoculated plantlets (V) were evaluated at 2 and 6days post-inoculation (DPI). Data support the assumptions that increases in biochemical (high hydrogen peroxide, antioxidant enzymes, and secondary compounds) and physiological responses (high photosynthesis index and chlorophyll content), confirmed by label-free comparative proteomic approach, in which quantitative changes in proteasome proteins, proteins related to photosynthesis, redox homeostasis, regulation factors/RNA processing proteins were observed may be implicated in the resistance of BRS-Marataoã to CPSMV. This pioneering study provides information for the selection of specific pathways and proteins, altered in this incompatible relationship, which could be chosen as targets for detailed studies to advance our understanding of the molecular, physiological, and biochemistry basis of the resistance mechanism of cowpea and design approachs to engineer plants that are more productive. This is a pioneering study in which an incompatible relationship between a resistant cowpea and Cowpea severe mosaic virus (CPSMV) was conducted to comparatively evaluate proteomic profiles by Gel-free/label-free methodology and some physiological and biochemical parameters to shed light on how a resistant cowpea cultivar deals with the virus attack. Specific proteins and associated pathways were altered in the cowpea plants challenged with CPSMV and will contribute to our knowledge on the biological process tailored by cowpea in response to CPSMV. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

NASA Astrophysics Data System (ADS)

Großerueschkamp, Frederik; Bracht, Thilo; Diehl, Hanna C.; Kuepper, Claus; Ahrens, Maike; Kallenbach-Thieltges, Angela; Mosig, Axel; Eisenacher, Martin; Marcus, Katrin; Behrens, Thomas; Brüning, Thomas; Theegarten, Dirk; Sitek, Barbara; Gerwert, Klaus

2017-03-01

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics.

PubMed

Großerueschkamp, Frederik; Bracht, Thilo; Diehl, Hanna C; Kuepper, Claus; Ahrens, Maike; Kallenbach-Thieltges, Angela; Mosig, Axel; Eisenacher, Martin; Marcus, Katrin; Behrens, Thomas; Brüning, Thomas; Theegarten, Dirk; Sitek, Barbara; Gerwert, Klaus

2017-03-30

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information

PubMed Central

2013-01-01

Background The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples. Results We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Conclusions Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. PMID:24341404

LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer.

PubMed

Veit, Johannes; Sachsenberg, Timo; Chernev, Aleksandar; Aicheler, Fabian; Urlaub, Henning; Kohlbacher, Oliver

2016-09-02

Modern mass spectrometry setups used in today's proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNP(xl) for UV-induced peptide-RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark ( Ramus, C.; J. Proteomics 2016 , 132 , 51 - 62 ). The second workflow, RNP(xl), represents the first software solution to date for identification of peptide-RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.

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.

Label-Free Proteomic Identification of Endogenous, Insulin-Stimulated Interaction Partners of Insulin Receptor Substrate-1

NASA Astrophysics Data System (ADS)

Geetha, Thangiah; Langlais, Paul; Luo, Moulun; Mapes, Rebekka; Lefort, Natalie; Chen, Shu-Chuan; Mandarino, Lawrence J.; Yi, Zhengping

2011-03-01

Protein-protein interactions are key to most cellular processes. Tandem mass spectrometry (MS/MS)-based proteomics combined with co-immunoprecipitation (CO-IP) has emerged as a powerful approach for studying protein complexes. However, a majority of systematic proteomics studies on protein-protein interactions involve the use of protein overexpression and/or epitope-tagged bait proteins, which might affect binding stoichiometry and lead to higher false positives. Here, we report an application of a straightforward, label-free CO-IP-MS/MS method, without the use of protein overexpression or protein tags, to the investigation of changes in the abundance of endogenous proteins associated with a bait protein, which is in this case insulin receptor substrate-1 (IRS-1), under basal and insulin stimulated conditions. IRS-1 plays a central role in the insulin signaling cascade. Defects in the protein-protein interactions involving IRS-1 may lead to the development of insulin resistance and type 2 diabetes. HPLC-ESI-MS/MS analyses identified eleven novel endogenous insulin-stimulated IRS-1 interaction partners in L6 myotubes reproducibly, including proteins play an important role in protein dephosphorylation [protein phosphatase 1 regulatory subunit 12A, (PPP1R12A)], muscle contraction and actin cytoskeleton rearrangement, endoplasmic reticulum stress, and protein folding, as well as protein synthesis. This novel application of label-free CO-IP-MS/MS quantification to assess endogenous interaction partners of a specific protein will prove useful for understanding how various cell stimuli regulate insulin signal transduction.

Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.

PubMed

Keich, Uri; Kertesz-Farkas, Attila; Noble, William Stafford

2015-08-07

Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications.

Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics

PubMed Central

2016-01-01

Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications. PMID:26152888

Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline

PubMed Central

Schilling, Birgit; Rardin, Matthew J.; MacLean, Brendan X.; Zawadzka, Anna M.; Frewen, Barbara E.; Cusack, Michael P.; Sorensen, Dylan J.; Bereman, Michael S.; Jing, Enxuan; Wu, Christine C.; Verdin, Eric; Kahn, C. Ronald; MacCoss, Michael J.; Gibson, Bradford W.

2012-01-01

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models. PMID:22454539

Growth phase-dependent proteomes of the Malaysian isolated Lactococcus lactis dairy strain M4 using label-free qualitative shotgun proteomics analysis.

PubMed

Yap, Theresa Wan Chen; Rabu, Amir; Abu Bakar, Farah Diba; Rahim, Raha Abdul; Mahadi, Nor Muhammad; Illias, Rosli Md; Murad, Abdul Munir Abdul

2014-01-01

Lactococcus lactis is the most studied mesophilic fermentative lactic acid bacterium. It is used extensively in the food industry and plays a pivotal role as a cell factory and also as vaccine delivery platforms. The proteome of the Malaysian isolated L. lactis M4 dairy strain, obtained from the milk of locally bred cows, was studied to elucidate the physiological changes occurring between the growth phases of this bacterium. In this study, ultraperformance liquid chromatography nanoflow electrospray ionization tandem mass spectrometry (UPLC- nano-ESI-MS(E)) approach was used for qualitative proteomic analysis. A total of 100 and 121 proteins were identified from the midexponential and early stationary growth phases, respectively, of the L. lactis strain M4. During the exponential phase, the most important reaction was the generation of sufficient energy, whereas, in the early stationary phase, the metabolic energy pathways decreased and the biosynthesis of proteins became more important. Thus, the metabolism of the cells shifted from energy production in the exponential phase to the synthesis of macromolecules in the stationary phase. The resultant proteomes are essential in providing an improved view of the cellular machinery of L. lactis during the transition of growth phases and hence provide insight into various biotechnological applications.

In-Source Fragmentation and the Sources of Partially Tryptic Peptides in Shotgun Proteomics

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

Kim, Jong-Seo; Monroe, Matthew E.; Camp, David G.

2013-02-01

Partially tryptic peptides are often identified in shotgun proteomics using trypsin as the proteolytic enzyme; however, it has been controversial regarding the sources of such partially tryptic peptides. Herein we investigate the impact of in-source fragmentation on shotgun proteomics using three biological samples, including a standard protein mixture, a mouse brain tissue homogenate, and a mouse plasma sample. Since the in-source fragments of a peptide retain the same elution time with its parent fully tryptic peptide, the partially tryptic peptides from in-source fragmentation can be distinguished from the other partially tryptic peptides by plotting the observed retention times against themore » computationally predicted retention times. Most partially tryptic in-source fragmentation artifacts were misaligned from the linear distribution of fully tryptic peptides. The impact of in-source fragmentation on peptide identifications was clearly significant in a less complex sample such as a standard protein digest, where ~60 % of unique peptides were observed as partially tryptic peptides from in-source fragmentation. In mouse brain or mouse plasma samples, in-source fragmentation contributed to 1-3 % of all identified peptides. The other major source of partially tryptic peptides in complex biological samples is presumably proteolytic processing by endogenous proteases in the samples. By filtering out the in-source fragmentation artifacts from the identified partially tryptic or non-tryptic peptides, it is possible to directly survey in-vivo proteolytic processing in biological samples such as blood plasma.« less

Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis.

PubMed

Dai, Peng; Wang, Qin; Wang, Weihua; Jing, Ruirui; Wang, Wei; Wang, Fengqin; Azadzoi, Kazem M; Yang, Jing-Hua; Yan, Zhen

2016-01-21

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients' tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

Salt stress induces changes in the proteomic profile of micropropagated sugarcane shoots

PubMed Central

Reis, Ricardo S.; Heringer, Angelo S.; Rangel, Patricia L.; Santa-Catarina, Claudete; Grativol, Clícia; Veiga, Carlos F. M.; Souza-Filho, Gonçalo A.

2017-01-01

Salt stress is one of the most common stresses in agricultural regions worldwide. In particular, sugarcane is affected by salt stress conditions, and no sugarcane cultivar presently show high productivity accompanied by a tolerance to salt stress. Proteomic analysis allows elucidation of the important pathways involved in responses to various abiotic stresses at the biochemical and molecular levels. Thus, this study aimed to analyse the proteomic effects of salt stress in micropropagated shoots of two sugarcane cultivars (CB38-22 and RB855536) using a label-free proteomic approach. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD006075. The RB855536 cultivar is more tolerant to salt stress than CB38-22. A quantitative label-free shotgun proteomic analysis identified 1172 non-redundant proteins, and 1160 of these were observed in both cultivars in the presence or absence of NaCl. Compared with CB38-22, the RB855536 cultivar showed a greater abundance of proteins involved in non-enzymatic antioxidant mechanisms, ion transport, and photosynthesis. Some proteins, such as calcium-dependent protein kinase, photosystem I, phospholipase D, and glyceraldehyde-3-phosphate dehydrogenase, were more abundant in the RB855536 cultivar under salt stress. Our results provide new insights into the response of sugarcane to salt stress, and the changes in the abundance of these proteins might be important for the acquisition of ionic and osmotic homeostasis during exposure to salt stress. PMID:28419154

Gel-free/label-free proteomic analysis of developing rice grains under heat stress.

PubMed

Timabud, Tarinee; Yin, Xiaojian; Pongdontri, Paweena; Komatsu, Setsuko

2016-02-05

High temperature markedly reduces the yields and quality of rice grains. To identify the mechanisms underlying heat stress-induced responses in rice grains, proteomic technique was used. Developing Khao Dawk Mali 105 rice grains at the milky, dough, and mature stages were treated at 40 °C for 3 days. Aromatic compounds were decreased in rice grains under heat stress. The protein abundance involved in glycolysis and tricarboxylic acid cycle, including glyceraldehyde 3-phosphate dehydrogenase and citrate synthase, was changed in milky and dough grains after heat treatment; however, none changes in mature grains. The abundance involved in amino acid metabolism was increased in dough grains, but decreased in milky grains. In addition, the abundance involved in starch and sucrose metabolism, such as starch synthase, ADP-glucose pyrophosphorylase, granule-bound starch synthase, and alpha amylase, was decreased in milky grains, but increased in dough grains. A number of redox homeostasis-related proteins, such as ascorbate peroxidase and peroxiredoxin, were increased in developing rice grains treated with heat stress. These results suggest that in response to heat stress, the abundance of numerous proteins involved in redox homeostasis and carbohydrate biosynthetic pathways may play a major role in the development of KDML105 rice grains. Yield of Khao Dawk Mali 105 rice, which is an economical aromatic rice, was disrupted by environmental stress. Rice grains developed under heat stress caused loss of aroma compound. To identify the mechanism of heat response in rice grain, gel-free/label-free proteomic technique was used. The abundance of proteins involved in glycolysis and tricarboxylic acid cycle was disrupted by heat stress. High temperature limited starch biosynthesis; however, it enhanced sugar biosynthesis in developing rice grains. Redox homeostasis related proteins were disrupted by heat stress. These results suggest that proteins involved in redox homeostasis

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

PubMed

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated selected reaction monitoring software for accurate label-free protein quantification.

PubMed

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

Highly abundant defense proteins in human sweat as revealed by targeted proteomics and label-free quantification mass spectrometry.

PubMed

Csősz, É; Emri, G; Kalló, G; Tsaprailis, G; Tőzsér, J

2015-10-01

The healthy human skin with its effective antimicrobial defense system forms an efficient barrier against invading pathogens. There is evidence suggesting that the composition of this chemical barrier varies between diseases, making the easily collected sweat an ideal candidate for biomarker discoveries. Our aim was to provide information about the normal composition of the sweat, and to study the chemical barrier found at the surface of skin. Sweat samples from healthy individuals were collected during sauna bathing, and the global protein panel was analysed by label-free mass spectrometry. SRM-based targeted proteomic methods were designed and stable isotope labelled reference peptides were used for method validation. Ninety-five sweat proteins were identified, 20 of them were novel proteins. It was shown that dermcidin is the most abundant sweat protein, and along with apolipoprotein D, clusterin, prolactin-inducible protein and serum albumin, they make up 91% of secreted sweat proteins. The roles of these highly abundant proteins were reviewed; all of which have protective functions, highlighting the importance of sweat glands in composing the first line of innate immune defense system, and maintaining the epidermal barrier integrity. Our findings with regard to the proteins forming the chemical barrier of the skin as determined by label-free quantification and targeted proteomics methods are in accordance with previous studies, and can be further used as a starting point for non-invasive sweat biomarker research. © 2015 European Academy of Dermatology and Venereology.

The sheep (Ovis aries) muscle proteome: Decoding the mechanisms of tolerance to Seasonal Weight Loss using label-free proteomics.

PubMed

Ferreira, Ana M; Grossmann, Jonas; Fortes, Claudia; Kilminster, Tanya; Scanlon, Tim; Milton, John; Greeff, Johan; Oldham, Chris; Nanni, Paolo; Almeida, André M

2017-05-24

Seasonal Weight Loss (SWL) is one of the most pressing issues in animal production in the tropics and Mediterranean. This work aims to characterize muscle proteome changes as a consequence of SWL in meat producing sheep, using a label-free proteomics approach. We compare three breeds: the Australian Merino (SWL susceptible), the Damara (SWL tolerant) and the Dorper (SWL intermediate tolerance). We identified 668 proteins of the sheep proteome, 95 with differential regulation. Also we observe that the more vulnerable to SWL a breed is, the more differential abundance proteins we find. Protein binding was the most frequently altered molecular function identified. We suggest 6 putative markers for restricted nutritional conditions independently of breed: ferritin heavy-chain; immunoglobulin V lambda chain; transgelin; fatty acid synthase; glutathione S-transferase A2; dihydrodiol dehydrogenase 3-like. Moreover, we suggest as related to SWL tolerance: S100-A10 Serpin A3-5-like and Catalase, subject however to necessary validation assays. The identification of SWL-tolerance related proteins using proteomics will lead to increased stock productivity of relevant interest to animal production, particularly if identified at the muscle level, the tissue of economic importance in meat production. Seasonal Weight Loss (SWL) is the most pressing issue in animal production in the tropics and the Mediterranean. To counter SWL, farmers often use animal breeds that have a natural ability to withstand pasture scarcity. Here we study the sheep muscle proteome at the muscle level, the tissue of economic importance in meat production. Furthermore, the identification of proteins that change their abundance in response to SWL using proteomics can contribute to increased stock productivity of relevant interest to animal production. We identified 668 proteins of the sheep proteome. We demonstrate that the following proteins are affected by restricted nutritional conditions: ferritin heavy

Large-scale label-free quantitative proteomics of the pea aphid-Buchnera symbiosis.

PubMed

Poliakov, Anton; Russell, Calum W; Ponnala, Lalit; Hoops, Harold J; Sun, Qi; Douglas, Angela E; van Wijk, Klaas J

2011-06-01

Many insects are nutritionally dependent on symbiotic microorganisms that have tiny genomes and are housed in specialized host cells called bacteriocytes. The obligate symbiosis between the pea aphid Acyrthosiphon pisum and the γ-proteobacterium Buchnera aphidicola (only 584 predicted proteins) is particularly amenable for molecular analysis because the genomes of both partners have been sequenced. To better define the symbiotic relationship between this aphid and Buchnera, we used large-scale, high accuracy tandem mass spectrometry (nanoLC-LTQ-Orbtrap) to identify aphid and Buchnera proteins in the whole aphid body, purified bacteriocytes, isolated Buchnera cells and the residual bacteriocyte fraction. More than 1900 aphid and 400 Buchnera proteins were identified. All enzymes in amino acid metabolism annotated in the Buchnera genome were detected, reflecting the high (68%) coverage of the proteome and supporting the core function of Buchnera in the aphid symbiosis. Transporters mediating the transport of predicted metabolites were present in the bacteriocyte. Label-free spectral counting combined with hierarchical clustering, allowed to define the quantitative distribution of a subset of these proteins across both symbiotic partners, yielding no evidence for the selective transfer of protein among the partners in either direction. This is the first quantitative proteome analysis of bacteriocyte symbiosis, providing a wealth of information about molecular function of both the host cell and bacterial symbiont.

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.

Evaluation of "shotgun" proteomics for identification of biological threat agents in complex environmental matrixes: experimental simulations.

PubMed

Verberkmoes, Nathan C; Hervey, W Judson; Shah, Manesh; Land, Miriam; Hauser, Loren; Larimer, Frank W; Van Berkel, Gary J; Goeringer, Douglas E

2005-02-01

There is currently a great need for rapid detection and positive identification of biological threat agents, as well as microbial species in general, directly from complex environmental samples. This need is most urgent in the area of homeland security, but also extends into medical, environmental, and agricultural sciences. Mass-spectrometry-based analysis is one of the leading technologies in the field with a diversity of different methodologies for biothreat detection. Over the past few years, "shotgun"proteomics has become one method of choice for the rapid analysis of complex protein mixtures by mass spectrometry. Recently, it was demonstrated that this methodology is capable of distinguishing a target species against a large database of background species from a single-component sample or dual-component mixtures with relatively the same concentration. Here, we examine the potential of shotgun proteomics to analyze a target species in a background of four contaminant species. We tested the capability of a common commercial mass-spectrometry-based shotgun proteomics platform for the detection of the target species (Escherichia coli) at four different concentrations and four different time points of analysis. We also tested the effect of database size on positive identification of the four microbes used in this study by testing a small (13-species) database and a large (261-species) database. The results clearly indicated that this technology could easily identify the target species at 20% in the background mixture at a 60, 120, 180, or 240 min analysis time with the small database. The results also indicated that the target species could easily be identified at 20% or 6% but could not be identified at 0.6% or 0.06% in either a 240 min analysis or a 30 h analysis with the small database. The effects of the large database were severe on the target species where detection above the background at any concentration used in this study was impossible, though the three

An Informatics-assisted Label-free Approach for Personalized Tissue Membrane Proteomics: Case Study on Colorectal Cancer*

PubMed Central

Han, Chia-Li; Chen, Jinn-Shiun; Chan, Err-Cheng; Wu, Chien-Peng; Yu, Kun-Hsing; Chen, Kuei-Tien; Tsou, Chih-Chiang; Tsai, Chia-Feng; Chien, Chih-Wei; Kuo, Yung-Bin; Lin, Pei-Yi; Yu, Jau-Song; Hsueh, Chuen; Chen, Min-Chi; Chan, Chung-Chuan; Chang, Yu-Sun; Chen, Yu-Ju

2011-01-01

We developed a multiplexed label-free quantification strategy, which integrates an efficient gel-assisted digestion protocol, high-performance liquid chromatography tandem MS analysis, and a bioinformatics alignment method to determine personalized proteomic profiles for membrane proteins in human tissues. This strategy provided accurate (6% error) and reproducible (34% relative S.D.) quantification of three independently purified membrane fractions from the same human colorectal cancer (CRC) tissue. Using CRC as a model, we constructed the personalized membrane protein atlas of paired tumor and adjacent normal tissues from 28 patients with different stages of CRC. Without fractionation, this strategy confidently quantified 856 proteins (≥2 unique peptides) across different patients, including the first and robust detection (Mascot score: 22,074) of the well-documented CRC marker, carcinoembryonic antigen 5 by a discovery-type proteomics approach. Further validation of a panel of proteins, annexin A4, neutrophils defensin A1, and claudin 3, confirmed differential expression levels and high occurrences (48–70%) in 60 CRC patients. The most significant discovery is the overexpression of stomatin-like 2 (STOML2) for early diagnostic and prognostic potential. Increased expression of STOML2 was associated with decreased CRC-related survival; the mean survival period was 34.77 ± 2.03 months in patients with high STOML2 expression, whereas 53.67 ± 3.46 months was obtained for patients with low STOML2 expression. Further analysis by ELISA verified that plasma concentrations of STOML2 in early-stage CRC patients were elevated as compared with those of healthy individuals (p < 0.001), suggesting that STOML2 may be a noninvasive serological biomarker for early CRC diagnosis. The overall sensitivity of STOML2 for CRC detection was 71%, which increased to 87% when combined with CEA measurements. This study demonstrated a sensitive, label-free strategy for differential

Boron nitride as desalting material in combination with phosphopeptide enrichment in shotgun proteomics.

PubMed

Furuhashi, Takeshi; Nukarinen, Ella; Ota, Shigenori; Weckwerth, Wolfram

2014-05-01

Hydrophilic peptides in shotgun proteomics have been shown to be problematic in conventional chromatography. Typically, C18 solid phase extraction or peptide traps are used for desalting the sample prior to mass spectrometry analysis, but the capacity to retain hydrophilic peptides is not very high, causing a bias toward more hydrophobic peptides. This is particularly problematic in phosphoproteomic studies. We tested the compatibility of commercially available boron nitride as a novel material for peptide desalting. Boron nitride can be used to recover a wide range of peptides with different physicochemical properties comparable to combined C18 and graphite carbon material. Copyright © 2014. Published by Elsevier Inc.

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 data from label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.

PubMed

Murugaiyan, Jayaseelan; Eravci, Murat; Weise, Christoph; Roesler, Uwe

2017-06-01

Here, we provide the dataset associated with our research article 'label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.' (Murugaiyan et al., 2017) [1]. This dataset describes liquid chromatography-mass spectrometry (LC-MS)-based protein identification and quantification of a non-infectious strain, Prototheca zopfii genotype 1 and two strains associated with severe and mild infections, respectively, P. zopfii genotype 2 and Prototheca blaschkeae . Protein identification and label-free quantification was carried out by analysing MS raw data using the MaxQuant-Andromeda software suit. The expressional level differences of the identified proteins among the strains were computed using Perseus software and the results were presented in [1]. This DiB provides the MaxQuant output file and raw data deposited in the PRIDE repository with the dataset identifier PXD005305.

Shotgun proteomics reveals physiological response to ocean acidification in Crassostrea gigas.

PubMed

Timmins-Schiffman, Emma; Coffey, William D; Hua, Wilber; Nunn, Brook L; Dickinson, Gary H; Roberts, Steven B

2014-11-03

Ocean acidification as a result of increased anthropogenic CO2 emissions is occurring in marine and estuarine environments worldwide. The coastal ocean experiences additional daily and seasonal fluctuations in pH that can be lower than projected end-of-century open ocean pH reductions. In order to assess the impact of ocean acidification on marine invertebrates, Pacific oysters (Crassostrea gigas) were exposed to one of four different p CO2 levels for four weeks: 400 μatm (pH 8.0), 800 μatm (pH 7.7), 1000 μatm (pH 7.6), or 2800 μatm (pH 7.3). At the end of the four week exposure period, oysters in all four p CO2 environments deposited new shell, but growth rate was not different among the treatments. However, micromechanical properties of the new shell were compromised by elevated p CO2. Elevated p CO2 affected neither whole body fatty acid composition, nor glycogen content, nor mortality rate associated with acute heat shock. Shotgun proteomics revealed that several physiological pathways were significantly affected by ocean acidification, including antioxidant response, carbohydrate metabolism, and transcription and translation. Additionally, the proteomic response to a second stress differed with p CO2, with numerous processes significantly affected by mechanical stimulation at high versus low p CO2 (all proteomics data are available in the ProteomeXchange under the identifier PXD000835). Oyster physiology is significantly altered by exposure to elevated p CO2, indicating changes in energy resource use. This is especially apparent in the assessment of the effects of p CO2 on the proteomic response to a second stress. The altered stress response illustrates that ocean acidification may impact how oysters respond to other changes in their environment. These data contribute to an integrative view of the effects of ocean acidification on oysters as well as physiological trade-offs during environmental stress.

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

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics.

PubMed

Chahrour, Osama; Cobice, Diego; Malone, John

2015-09-10

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison between Procedures using Sodium Dodecyl Sulfate for Shotgun Proteomic Analyses of Complex Samples

PubMed Central

Bereman, Michael S.; Egertson, Jarrett D.; MacCoss, Michael J.

2012-01-01

Filter aided sample preparation (FASP) and a new sample preparation method using a modified commercial SDS removal spin column are quantitatively compared in terms of their performance for shotgun proteomic experiments in three complex proteomic samples: a Saccharomyces cerevisiae lysate (insoluble fraction), a Caenorhabditis elegans lysate (soluble fraction), and a human embryonic kidney cell line (HEK293T). The characteristics and total number of peptides and proteins identified are compared between the two procedures. The SDS spin column procedure affords a conservative 4-fold improvement in throughput, is more reproducible, less expensive (i.e., requires less materials), and identifies between 30–107% more peptides at a q≤0.01, than the FASP procedure. The peptides identified by SDS spin column are more hydrophobic than species identified by the FASP procedure as indicated by the distribution of GRAVY scores. Ultimately, these improvements correlate to as great as a 50% increase in protein identifications with 2 or more peptides. PMID:21656683

Label free quantitative proteomics analysis on the cisplatin resistance in ovarian cancer cells.

PubMed

Wang, F; Zhu, Y; Fang, S; Li, S; Liu, S

2017-05-20

Quantitative proteomics has been made great progress in recent years. Label free quantitative proteomics analysis based on the mass spectrometry is widely used. Using this technique, we determined the differentially expressed proteins in the cisplatin-sensitive ovarian cancer cells COC1 and cisplatin-resistant cells COC1/DDP before and after the application of cisplatin. Using the GO analysis, we classified those proteins into different subgroups bases on their cellular component, biological process, and molecular function. We also used KEGG pathway analysis to determine the key signal pathways that those proteins were involved in. There are 710 differential proteins between COC1 and COC1/DDP cells, 783 between COC1 and COC1/DDP cells treated with cisplatin, 917 between the COC1/DDP cells and COC1/DDP cells treated with LaCl3, 775 between COC1/DDP cells treated with cisplatin and COC1/DDP cells treated with cisplatin and LaCl3. Among the same 411 differentially expressed proteins in cisplatin-sensitive COC1 cells and cisplain-resistant COC1/DDP cells before and after cisplatin treatment, 14% of them were localized on the cell membrane. According to the KEGG results, differentially expressed proteins were classified into 21 groups. The most abundant proteins were involved in spliceosome. This study lays a foundation for deciphering the mechanism for drug resistance in ovarian tumor.

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

Unraveling proteome changes of Holstein beef M. semitendinosus and its relationship to meat discoloration during post-mortem storage analyzed by label-free mass spectrometry.

PubMed

Yu, Qianqian; Wu, Wei; Tian, Xiaojing; Hou, Man; Dai, Ruitong; Li, Xingmin

2017-02-10

Label-free proteomics was applied to characterize the effect of post-mortem storage time (0, 4, and 9days at 4°C±1°C) on the proteome changes of M. semitendinosus (SM) in Holstein cattle, and correlations between differentially abundant proteins and meat color traits were investigated. The redness (a*) value decreased significantly (P<0.05) during post-mortem storage, meanwhile, the relative proportion of metmyoglobin increased significantly (P<0.05) from 16.99% at day 0 to 40.26% at day 9. A total of 118 proteins with significant changes (fold change>1.5, P<0.05) was identified by comparisons of day 4 vs. day 0, day 9 vs. day 0, and day 9 vs. day 4. Principal component and hierarchical cluster analyses of these proteins were performed, and results exhibited clear distinctions among samples from different storage times. Eighteen differentially abundant proteins were correlated closely with the a* value of meat. Bioinformatics analyses revealed that most of these proteins were involved in glycolysis and energy metabolism, electron-transfer processes, and the antioxidation function, which implied an underlying connection between meat discoloration and these biological processes. It is always a challenge for scientists to improve the stability of meat color during post-mortem storage and retail display. However, the mechanism involved in meat discoloration has not been unraveled completely, and the application of label-free proteomics in studying meat discoloration has not been reported. Our work discovers some key proteins in SM muscle of Holstein cattle that were correlated with a* value of meat via label-free proteomics. Bioinformatics analyses revealed that some of these differentially abundant proteins were involved in glycolysis and energy metabolism, electron-transfer processes, and the antioxidation function, which implied an underlying connection between meat discoloration and these biological processes. These results provide the theoretic basis on

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.

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

Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

PubMed

Trudgian, David C; Mirzaei, Hamid

2012-12-07

We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

PSEA-Quant: a protein set enrichment analysis on label-free and label-based protein quantification data.

PubMed

Lavallée-Adam, Mathieu; Rauniyar, Navin; McClatchy, Daniel B; Yates, John R

2014-12-05

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights.

PSEA-Quant: A Protein Set Enrichment Analysis on Label-Free and Label-Based Protein Quantification Data

PubMed Central

2015-01-01

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights. PMID:25177766

Identifying potential markers in Breast Cancer subtypes using plasma label-free proteomics.

PubMed

Corrêa, Stephany; Panis, Carolina; Binato, Renata; Herrera, Ana Cristina; Pizzatti, Luciana; Abdelhay, Eliana

2017-01-16

Breast Cancer (BC) is the most common neoplasia among women and has a high mortality rate worldwide. Over the past several decades, increasing molecular knowledge of BC has resulted in its stratification into 4 major molecular subtypes according to hormonal receptor expression. Unfortunately, although the data accumulated thus far has improved BC prognosis and treatment, there have been few achievements in its diagnosis. In this study, we applied a Label-free Nano-LC/MSMS approach to reveal systemic molecular features and possible plasma markers for BC patients. Compared to healthy control plasma donors, we identified 191, 166, 182, and 186 differentially expressed proteins in the Luminal, Lumina-HER2, HER2, and TN subtypes. In silico analysis demonstrated an overall downregulation of cellular basal machinery and, more importantly, brought new focus to the known pathways and signaling molecules in BC that are related to immune system alterations. Moreover, using western blot analysis, we verified high levels of BCAS3, IRX1, IRX4 and IRX5 in BC plasma samples, thus highlighting the potential use of plasma proteomics in investigations into cancer biomarkers. The results of this study provide new insight into Breast Cancer (BC). We determined the plasma proteomic profile of BC subtypes. Furthermore, we report that the signaling pathways correlating with late processes in BC already exhibit plasma alterations in less aggressive subtypes. Additionally, we validated the high levels of particular proteins in patient samples, which suggests the use of these proteins as potential disease markers.

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.

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.

Targeted proteomics guided by label-free global proteome analysis in saliva reveal transition signatures from health to periodontal disease.

PubMed

Bostanci, Nagihan; Selevsek, Nathalie; Wolski, Witold; Grossmann, Jonas; Bao, Kai; Wahlander, Asa; Trachsel, Christian; Schlapbach, Ralph; Özturk, Veli Özgen; Afacan, Beral; Emingil, Gulnur; Belibasakis, Georgios N

2018-04-02

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. We carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n=67, health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n=82). The LFQ platform led to the discovery of 119 proteins with at least two-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1), with maximum area under the receiver operating curve >0.97. This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

PubMed

Lazar, Cosmin; Gatto, Laurent; Ferro, Myriam; Bruley, Christophe; Burger, Thomas

2016-04-01

Missing values are a genuine issue in label-free quantitative proteomics. Recent works have surveyed the different statistical methods to conduct imputation and have compared them on real or simulated data sets and recommended a list of missing value imputation methods for proteomics application. Although insightful, these comparisons do not account for two important facts: (i) depending on the proteomics data set, the missingness mechanism may be of different natures and (ii) each imputation method is devoted to a specific type of missingness mechanism. As a result, we believe that the question at stake is not to find the most accurate imputation method in general but instead the most appropriate one. We describe a series of comparisons that support our views: For instance, we show that a supposedly "under-performing" method (i.e., giving baseline average results), if applied at the "appropriate" time in the data-processing pipeline (before or after peptide aggregation) on a data set with the "appropriate" nature of missing values, can outperform a blindly applied, supposedly "better-performing" method (i.e., the reference method from the state-of-the-art). This leads us to formulate few practical guidelines regarding the choice and the application of an imputation method in a proteomics context.

Mechanism of Arachidonic Acid Accumulation during Aging in Mortierella alpina: A Large-Scale Label-Free Comparative Proteomics Study.

PubMed

Yu, Yadong; Li, Tao; Wu, Na; Ren, Lujing; Jiang, Ling; Ji, Xiaojun; Huang, He

2016-11-30

Arachidonic acid (ARA) is an important polyunsaturated fatty acid having various beneficial physiological effects on the human body. The aging of Mortierella alpina has long been known to significantly improve ARA yield, but the exact mechanism is still elusive. Herein, multiple approaches including large-scale label-free comparative proteomics were employed to systematically investigate the mechanism mentioned above. Upon ultrastructural observation, abnormal mitochondria were found to aggregate around shrunken lipid droplets. Proteomics analysis revealed a total of 171 proteins with significant alterations of expression during aging. Pathway analysis suggested that reactive oxygen species (ROS) were accumulated and stimulated the activation of the malate/pyruvate cycle and isocitrate dehydrogenase, which might provide additional NADPH for ARA synthesis. EC 4.2.1.17-hydratase might be a key player in ARA accumulation during aging. These findings provide a valuable resource for efforts to further improve the ARA content in the oil produced by aging M. alpina.

Tiered Human Integrated Sequence Search Databases for Shotgun Proteomics.

PubMed

Deutsch, Eric W; Sun, Zhi; Campbell, David S; Binz, Pierre-Alain; Farrah, Terry; Shteynberg, David; Mendoza, Luis; Omenn, Gilbert S; Moritz, Robert L

2016-11-04

The results of analysis of shotgun proteomics mass spectrometry data can be greatly affected by the selection of the reference protein sequence database against which the spectra are matched. For many species there are multiple sources from which somewhat different sequence sets can be obtained. This can lead to confusion about which database is best in which circumstances-a problem especially acute in human sample analysis. All sequence databases are genome-based, with sequences for the predicted gene and their protein translation products compiled. Our goal is to create a set of primary sequence databases that comprise the union of sequences from many of the different available sources and make the result easily available to the community. We have compiled a set of four sequence databases of varying sizes, from a small database consisting of only the ∼20,000 primary isoforms plus contaminants to a very large database that includes almost all nonredundant protein sequences from several sources. This set of tiered, increasingly complete human protein sequence databases suitable for mass spectrometry proteomics sequence database searching is called the Tiered Human Integrated Search Proteome set. In order to evaluate the utility of these databases, we have analyzed two different data sets, one from the HeLa cell line and the other from normal human liver tissue, with each of the four tiers of database complexity. The result is that approximately 0.8%, 1.1%, and 1.5% additional peptides can be identified for Tiers 2, 3, and 4, respectively, as compared with the Tier 1 database, at substantially increasing computational cost. This increase in computational cost may be worth bearing if the identification of sequence variants or the discovery of sequences that are not present in the reviewed knowledge base entries is an important goal of the study. We find that it is useful to search a data set against a simpler database, and then check the uniqueness of the

Tiered Human Integrated Sequence Search Databases for Shotgun Proteomics

PubMed Central

Deutsch, Eric W.; Sun, Zhi; Campbell, David S.; Binz, Pierre-Alain; Farrah, Terry; Shteynberg, David; Mendoza, Luis; Omenn, Gilbert S.; Moritz, Robert L.

2016-01-01

The results of analysis of shotgun proteomics mass spectrometry data can be greatly affected by the selection of the reference protein sequence database against which the spectra are matched. For many species there are multiple sources from which somewhat different sequence sets can be obtained. This can lead to confusion about which database is best in which circumstances – a problem especially acute in human sample analysis. All sequence databases are genome-based, with sequences for the predicted gene and their protein translation products compiled. Our goal is to create a set of primary sequence databases that comprise the union of sequences from many of the different available sources and make the result easily available to the community. We have compiled a set of four sequence databases of varying sizes, from a small database consisting of only the ~20,000 primary isoforms plus contaminants to a very large database that includes almost all non-redundant protein sequences from several sources. This set of tiered, increasingly complete human protein sequence databases suitable for mass spectrometry proteomics sequence database searching is called the Tiered Human Integrated Search Proteome set. In order to evaluate the utility of these databases, we have analyzed two different data sets, one from the HeLa cell line and the other from normal human liver tissue, with each of the four tiers of database complexity. The result is that approximately 0.8%, 1.1%, and 1.5% additional peptides can be identified for Tiers 2, 3, and 4, respectively, as compared with the Tier 1 database, at substantially increasing computational cost. This increase in computational cost may be worth bearing if the identification of sequence variants or the discovery of sequences that are not present in the reviewed knowledge base entries is an important goal of the study. We find that it is useful to search a data set against a simpler database, and then check the uniqueness of the

Gel-free/label-free proteomic analysis of root tip of soybean over time under flooding and drought stresses.

PubMed

Wang, Xin; Oh, MyeongWon; Sakata, Katsumi; Komatsu, Setsuko

2016-01-01

Growth in the early stage of soybean is markedly inhibited under flooding and drought stresses. To explore the responsive mechanisms of soybean, temporal protein profiles of root tip under flooding and drought stresses were analyzed using gel-free/label-free proteomic technique. Root tip was analyzed because it was the most sensitive organ against flooding, and it was beneficial to root penetration under drought. UDP glucose: glycoprotein glucosyltransferase was decreased and increased in soybean root under flooding and drought, respectively. Temporal protein profiles indicated that fermentation and protein synthesis/degradation were essential in root tip under flooding and drought, respectively. In silico protein-protein interaction analysis revealed that the inductive and suppressive interactions between S-adenosylmethionine synthetase family protein and B-S glucosidase 44 under flooding and drought, respectively, which are related to carbohydrate metabolism. Furthermore, biotin/lipoyl attachment domain containing protein and Class II aminoacyl tRNA/biotin synthetases superfamily protein were repressed in the root tip during time-course stresses. These results suggest that biotin and biotinylation might be involved in energy management to cope with flooding and drought in early stage of soybean-root tip. Copyright © 2015 Elsevier B.V. All rights reserved.

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

PubMed Central

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J.; Li, Ming

2013-01-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables. PMID:22552787

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

PubMed

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J; Li, Ming; Tabb, David L

2012-09-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

A Shotgun Proteomic Approach Reveals That Fe Deficiency Causes Marked Changes in the Protein Profiles of Plasma Membrane and Detergent-Resistant Microdomain Preparations from Beta vulgaris Roots.

PubMed

Gutierrez-Carbonell, Elain; Takahashi, Daisuke; Lüthje, Sabine; González-Reyes, José Antonio; Mongrand, Sébastien; Contreras-Moreira, Bruno; Abadía, Anunciación; Uemura, Matsuo; Abadía, Javier; López-Millán, Ana Flor

2016-08-05

In the present study we have used label-free shotgun proteomic analysis to examine the effects of Fe deficiency on the protein profiles of highly pure sugar beet root plasma membrane (PM) preparations and detergent-resistant membranes (DRMs), the latter as an approach to study microdomains. Altogether, 545 proteins were detected, with 52 and 68 of them changing significantly with Fe deficiency in PM and DRM, respectively. Functional categorization of these proteins showed that signaling and general and vesicle-related transport accounted for approximately 50% of the differences in both PM and DRM, indicating that from a qualitative point of view changes induced by Fe deficiency are similar in both preparations. Results indicate that Fe deficiency has an impact in phosphorylation processes at the PM level and highlight the involvement of signaling proteins, especially those from the 14-3-3 family. Lipid profiling revealed Fe-deficiency-induced decreases in phosphatidic acid derivatives, which may impair vesicle formation, in agreement with the decreases measured in proteins related to intracellular trafficking and secretion. The modifications induced by Fe deficiency in the relative enrichment of proteins in DRMs revealed the existence of a group of cytoplasmic proteins that appears to be more attached to the PM in conditions of Fe deficiency.

Evaluation of Normalization Methods on GeLC-MS/MS Label-Free Spectral Counting Data to Correct for Variation during Proteomic Workflows

NASA Astrophysics Data System (ADS)

Gokce, Emine; Shuford, Christopher M.; Franck, William L.; Dean, Ralph A.; Muddiman, David C.

2011-12-01

Normalization of spectral counts (SpCs) in label-free shotgun proteomic approaches is important to achieve reliable relative quantification. Three different SpC normalization methods, total spectral count (TSpC) normalization, normalized spectral abundance factor (NSAF) normalization, and normalization to selected proteins (NSP) were evaluated based on their ability to correct for day-to-day variation between gel-based sample preparation and chromatographic performance. Three spectral counting data sets obtained from the same biological conidia sample of the rice blast fungus Magnaporthe oryzae were analyzed by 1D gel and liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Equine myoglobin and chicken ovalbumin were spiked into the protein extracts prior to 1D-SDS- PAGE as internal protein standards for NSP. The correlation between SpCs of the same proteins across the different data sets was investigated. We report that TSpC normalization and NSAF normalization yielded almost ideal slopes of unity for normalized SpC versus average normalized SpC plots, while NSP did not afford effective corrections of the unnormalized data. Furthermore, when utilizing TSpC normalization prior to relative protein quantification, t-testing and fold-change revealed the cutoff limits for determining real biological change to be a function of the absolute number of SpCs. For instance, we observed the variance decreased as the number of SpCs increased, which resulted in a higher propensity for detecting statistically significant, yet artificial, change for highly abundant proteins. Thus, we suggest applying higher confidence level and lower fold-change cutoffs for proteins with higher SpCs, rather than using a single criterion for the entire data set. By choosing appropriate cutoff values to maintain a constant false positive rate across different protein levels (i.e., SpC levels), it is expected this will reduce the overall false negative rate, particularly for proteins with

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation.

PubMed

Schilling, Birgit; Rardin, Matthew J; MacLean, Brendan X; Zawadzka, Anna M; Frewen, Barbara E; Cusack, Michael P; Sorensen, Dylan J; Bereman, Michael S; Jing, Enxuan; Wu, Christine C; Verdin, Eric; Kahn, C Ronald; Maccoss, Michael J; Gibson, Bradford W

2012-05-01

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Constructing Proteome Reference Map of the Porcine Jejunal Cell Line (IPEC-J2) by Label-Free Mass Spectrometry.

PubMed

Kim, Sang Hoon; Pajarillo, Edward Alain B; Balolong, Marilen P; Lee, Ji Yoon; Kang, Dae-Kyung

2016-06-28

In this study, the global proteome of the IPEC-J2 cell line was evaluated using ultra-high performance liquid chromatography coupled to a quadrupole Q Exactive™ Orbitrap mass spectrometer. Proteins were isolated from highly confluent IPEC-J2 cells in biological replicates and analyzed by label-free mass spectrometry prior to matching against a porcine genomic dataset. The results identified 1,517 proteins, accounting for 7.35% of all genes in the porcine genome. The highly abundant proteins detected, such as actin, annexin A2, and AHNAK nucleoprotein, are involved in structural integrity, signaling mechanisms, and cellular homeostasis. The high abundance of heat shock proteins indicated their significance in cellular defenses, barrier function, and gut homeostasis. Pathway analysis and annotation using the Kyoto Encyclopedia of Genes and Genomes database resulted in a putative protein network map of the regulation of immunological responses and structural integrity in the cell line. The comprehensive proteome analysis of IPEC-J2 cells provides fundamental insights into overall protein expression and pathway dynamics that might be useful in cell adhesion studies and immunological applications.

Label-free protein profiling of formalin-fixed paraffin-embedded (FFPE) heart tissue reveals immediate mitochondrial impairment after ionising radiation.

PubMed

Azimzadeh, Omid; Scherthan, Harry; Yentrapalli, Ramesh; Barjaktarovic, Zarko; Ueffing, Marius; Conrad, Marcus; Neff, Frauke; Calzada-Wack, Julia; Aubele, Michaela; Buske, Christian; Atkinson, Michael J; Hauck, Stefanie M; Tapio, Soile

2012-04-18

Qualitative proteome profiling of formalin-fixed, paraffin-embedded (FFPE) tissue is advancing the field of clinical proteomics. However, quantitative proteome analysis of FFPE tissue is hampered by the lack of an efficient labelling method. The usage of conventional protein labelling on FFPE tissue has turned out to be inefficient. Classical labelling targets lysine residues that are blocked by the formalin treatment. The aim of this study was to establish a quantitative proteomics analysis of FFPE tissue by combining the label-free approach with optimised protein extraction and separation conditions. As a model system we used FFPE heart tissue of control and exposed C57BL/6 mice after total body irradiation using a gamma ray dose of 3 gray. We identified 32 deregulated proteins (p≤0.05) in irradiated hearts 24h after the exposure. The proteomics data were further evaluated and validated by bioinformatics and immunoblotting investigation. In good agreement with our previous results using fresh-frozen tissue, the analysis indicated radiation-induced alterations in three main biological pathways: respiratory chain, lipid metabolism and pyruvate metabolism. The label-free approach enables the quantitative measurement of radiation-induced alterations in FFPE tissue and facilitates retrospective biomarker identification using clinical archives. Copyright © 2012 Elsevier B.V. All rights reserved.

Label-Free Quantitative Proteomic Analysis of Puccinia psidii Uredospores Reveals Differences of Fungal Populations Infecting Eucalyptus and Guava

PubMed Central

Bini, Andressa Peres; Regiani, Thais; Franceschini, Lívia Maria; Budzinski, Ilara Gabriela Frasson; Marques, Felipe Garbelini; Labate, Mônica Teresa Veneziano; Guidetti-Gonzalez, Simone; Moon, David Henry; Labate, Carlos Alberto

2016-01-01

Puccinia psidii sensu lato (s.l.) is the causal agent of eucalyptus and guava rust, but it also attacks a wide range of plant species from the myrtle family, resulting in a significant genetic and physiological variability among populations accessed from different hosts. The uredospores are crucial to P. psidii dissemination in the field. Although they are important for the fungal pathogenesis, their molecular characterization has been poorly studied. In this work, we report the first in-depth proteomic analysis of P. psidii s.l. uredospores from two contrasting populations: guava fruits (PpGuava) and eucalyptus leaves (PpEucalyptus). NanoUPLC-MSE was used to generate peptide spectra that were matched to the UniProt Puccinia genera sequences (UniProt database) resulting in the first proteomic analysis of the phytopathogenic fungus P. psidii. Three hundred and fourty proteins were detected and quantified using Label free proteomics. A significant number of unique proteins were found for each sample, others were significantly more or less abundant, according to the fungal populations. In PpGuava population, many proteins correlated with fungal virulence, such as malate dehydrogenase, proteossomes subunits, enolases and others were increased. On the other hand, PpEucalyptus proteins involved in biogenesis, protein folding and translocation were increased, supporting the physiological variability of the fungal populations according to their protein reservoirs and specific host interaction strategies. PMID:26731728

Label-Free Quantitative Proteomic Analysis of Puccinia psidii Uredospores Reveals Differences of Fungal Populations Infecting Eucalyptus and Guava.

PubMed

Quecine, Maria Carolina; Leite, Thiago Falda; Bini, Andressa Peres; Regiani, Thais; Franceschini, Lívia Maria; Budzinski, Ilara Gabriela Frasson; Marques, Felipe Garbelini; Labate, Mônica Teresa Veneziano; Guidetti-Gonzalez, Simone; Moon, David Henry; Labate, Carlos Alberto

2016-01-01

Puccinia psidii sensu lato (s.l.) is the causal agent of eucalyptus and guava rust, but it also attacks a wide range of plant species from the myrtle family, resulting in a significant genetic and physiological variability among populations accessed from different hosts. The uredospores are crucial to P. psidii dissemination in the field. Although they are important for the fungal pathogenesis, their molecular characterization has been poorly studied. In this work, we report the first in-depth proteomic analysis of P. psidii s.l. uredospores from two contrasting populations: guava fruits (PpGuava) and eucalyptus leaves (PpEucalyptus). NanoUPLC-MSE was used to generate peptide spectra that were matched to the UniProt Puccinia genera sequences (UniProt database) resulting in the first proteomic analysis of the phytopathogenic fungus P. psidii. Three hundred and fourty proteins were detected and quantified using Label free proteomics. A significant number of unique proteins were found for each sample, others were significantly more or less abundant, according to the fungal populations. In PpGuava population, many proteins correlated with fungal virulence, such as malate dehydrogenase, proteossomes subunits, enolases and others were increased. On the other hand, PpEucalyptus proteins involved in biogenesis, protein folding and translocation were increased, supporting the physiological variability of the fungal populations according to their protein reservoirs and specific host interaction strategies.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

An Overview of Advanced SILAC-Labeling Strategies for Quantitative Proteomics.

PubMed

Terzi, F; Cambridge, S

2017-01-01

Comparative, quantitative mass spectrometry of proteins provides great insight to protein abundance and function, but some molecular characteristics related to protein dynamics are not so easily obtained. Because the metabolic incorporation of stable amino acid isotopes allows the extraction of distinct temporal and spatial aspects of protein dynamics, the SILAC methodology is uniquely suited to be adapted for advanced labeling strategies. New SILAC strategies have emerged that allow deeper foraging into the complexity of cellular proteomes. Here, we review a few advanced SILAC-labeling strategies that have been published during last the years. Among them, different subsaturating-labeling as well as dual-labeling schemes are most prominent for a range of analyses including those of neuronal proteomes, secretion, or cell-cell-induced stimulations. These recent developments suggest that much more information can be gained from proteomic analyses if the labeling strategies are specifically tailored toward the experimental design. © 2017 Elsevier Inc. All rights reserved.

Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila.

PubMed

Di, Guilan; Li, Hui; Zhang, Chao; Zhao, Yanjing; Zhou, Chuanjiang; Naeem, Sajid; Li, Li; Kong, Xianghui

2017-07-01

Outbreaks of infectious diseases in common carp Cyprinus carpio, a major cultured fish in northern regions of China, constantly result in significant economic losses. Until now, information proteomic on immune defence remains limited. In the present study, a profile of intestinal mucosa immune response in Cyprinus carpio was investigated after 0, 12, 36 and 84 h after challenging tissues with Aeromonas hydrophila at a concentration of 1.4 × 10 8  CFU/mL. Proteomic profiles in different samples were compared using label-free quantitative proteomic approach. Based on MASCOT database search, 1149 proteins were identified in samples after normalisation of proteins. Treated groups 1 (T1) and 2 (T2) were first clustered together and then clustered with control (C group). The distance between C and treated group 3 (T3) represented the maxima according to hierarchical cluster analysis. Therefore, comparative analysis between C and T3 was selected in the following analysis. A total of 115 proteins with differential abundance were detected to show conspicuous expressing variances. A total of 52 up-regulated proteins and 63 down-regulated proteins were detected in T3. Gene ontology analysis showed that identified up-regulated differentially expressed proteins in T3 were mainly localised in the hemoglobin complex, and down-regulated proteins in T3 were mainly localised in the major histocompatibility complex II protein complex. Forty-six proteins of differential abundance (40% of 115) were involved in immune response, with 17 up-regulated and 29 down-regulated proteins detected in T3. This study is the first to report proteome response of carp intestinal mucosa against A. hydrophila infection; information obtained contribute to understanding defence mechanisms of carp intestinal mucosa. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shotgun proteomic monitoring of Clostridium acetobutylicum during stationary phase of butanol fermentation using xylose and comparison with the exponential phase

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

Sivagnanam, Kumaran; Raghavan, Vijaya G. S.; Shah, Manesh B

2012-01-01

Economically viable production of solvents through acetone butanol ethanol (ABE) fermentation requires a detailed understanding of Clostridium acetobutylicum. This study focuses on the proteomic profiling of C. acetobutylicum ATCC 824 from the stationary phase of ABE fermentation using xylose and compares with the exponential growth by shotgun proteomics approach. Comparative proteomic analysis revealed 22.9% of the C. acetobutylicum genome and 18.6% was found to be common in both exponential and stationary phases. The proteomic profile of C. acetobutylicum changed during the ABE fermentation such that 17 proteins were significantly differentially expressed between the two phases. Specifically, the expression of fivemore » proteins namely, CAC2873, CAP0164, CAP0165, CAC3298, and CAC1742 involved in the solvent production pathway were found to be significantly lower in the stationary phase compared to the exponential growth. Similarly, the expression of fucose isomerase (CAC2610), xylulose kinase (CAC2612), and a putative uncharacterized protein (CAC2611) involved in the xylose utilization pathway were also significantly lower in the stationary phase. These findings provide an insight into the metabolic behavior of C. acetobutylicum between different phases of ABE fermentation using xylose.« less

iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates*

PubMed Central

Shteynberg, David; Deutsch, Eric W.; Lam, Henry; Eng, Jimmy K.; Sun, Zhi; Tasman, Natalie; Mendoza, Luis; Moritz, Robert L.; Aebersold, Ruedi; Nesvizhskii, Alexey I.

2011-01-01

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments

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

Proteomic profiling of healthy and diseased hybrid soft corals Sinularia maxima × S. polydactyla.

PubMed

Gochfeld, Deborah J; Ankisetty, Sridevi; Slattery, Marc

2015-10-16

Emerging diseases of marine invertebrates have been implicated as one of the major causes of the continuing decline in coral reefs worldwide. To date, most of the focus on marine diseases has been aimed at hard (scleractinian) corals, which are the main reef builders worldwide. However, soft (alcyonacean) corals are also essential components of tropical reefs, representing food, habitat and the 'glue' that consolidates reefs, and they are subject to the same stressors as hard corals. Sinularia maxima and S. polydactyla are the dominant soft corals on the shallow reefs of Guam, where they hybridize. In addition to both parent species, the hybrid soft coral population in Guam is particularly affected by Sinularia tissue loss disease. Using label-free shotgun proteomics, we identified differences in protein expression between healthy and diseased colonies of the hybrid S. maxima × S. polydactyla. This study provided qualitative and quantitative data on specific proteins that were differentially expressed under the stress of disease. In particular, metabolic proteins were down-regulated, whereas proteins related to stress and to symbiont photosynthesis were up-regulated in the diseased soft corals. These results indicate that soft corals are responding to pathogenesis at the level of the proteome, and that this label-free approach can be used to identify and quantify protein biomarkers of sub-lethal stress in studies of marine disease.

IdentiPy: An Extensible Search Engine for Protein Identification in Shotgun Proteomics.

PubMed

Levitsky, Lev I; Ivanov, Mark V; Lobas, Anna A; Bubis, Julia A; Tarasova, Irina A; Solovyeva, Elizaveta M; Pridatchenko, Marina L; Gorshkov, Mikhail V

2018-06-18

We present an open-source, extensible search engine for shotgun proteomics. Implemented in Python programming language, IdentiPy shows competitive processing speed and sensitivity compared with the state-of-the-art search engines. It is equipped with a user-friendly web interface, IdentiPy Server, enabling the use of a single server installation accessed from multiple workstations. Using a simplified version of X!Tandem scoring algorithm and its novel "autotune" feature, IdentiPy outperforms the popular alternatives on high-resolution data sets. Autotune adjusts the search parameters for the particular data set, resulting in improved search efficiency and simplifying the user experience. IdentiPy with the autotune feature shows higher sensitivity compared with the evaluated search engines. IdentiPy Server has built-in postprocessing and protein inference procedures and provides graphic visualization of the statistical properties of the data set and the search results. It is open-source and can be freely extended to use third-party scoring functions or processing algorithms and allows customization of the search workflow for specialized applications.

Shotgun proteomics of the barley seed proteome

USDA-ARS?s Scientific Manuscript database

Barley seed proteins are of prime importance to the brewing industry, human and animal nutrition and in plant breeding for cultivar identification. To obtain comprehensive proteomic data from barley seeds, acetone precipitated proteins were in-solution digested and the resulting peptides were analyz...

Visualization of LC-MS/MS proteomics data in MaxQuant.

PubMed

Tyanova, Stefka; Temu, Tikira; Carlson, Arthur; Sinitcyn, Pavel; Mann, Matthias; Cox, Juergen

2015-04-01

Modern software platforms enable the analysis of shotgun proteomics data in an automated fashion resulting in high quality identification and quantification results. Additional understanding of the underlying data can be gained with the help of advanced visualization tools that allow for easy navigation through large LC-MS/MS datasets potentially consisting of terabytes of raw data. The updated MaxQuant version has a map navigation component that steers the users through mass and retention time-dependent mass spectrometric signals. It can be used to monitor a peptide feature used in label-free quantification over many LC-MS runs and visualize it with advanced 3D graphic models. An expert annotation system aids the interpretation of the MS/MS spectra used for the identification of these peptide features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Phage-Induced Expression of CRISPR-Associated Proteins is Revealed by Shotgun Proteomics in Streptococcus thermophilus

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

Young, Jacque C; Dill, Brian; Pan, Chongle

The CRISPR/Cas system, comprised of clustered regularly interspaced short palindromic repeats along with their associated (Cas) proteins, protects bacteria and archaea from viral predation and invading nucleic acids. While the mechanism of action for this acquired immunity is currently under investigation, the response of Cas protein expression to phage infection has yet to be elucidated. In this study, we employed shotgun proteomics to measure the global proteome expression in a model system for studying the CRISPR/Cas response: infection of S. thermophilus DGCC7710 with phage 2972. Host and viral proteins were simultaneously measured following inoculation at two different multiplicities of infectionmore » and across various time points using two-dimensional liquid chromatography tandem mass spectroscopy. Thirty-seven out of forty predicted viral proteins were detected, including all proteins of the structural virome and viral effector proteins. In total, 1,013 of 2,079 predicted S. thermophilus proteins were detected, facilitating the monitoring of host protein synthesis changes in response to virus infection. Importantly, Cas proteins from all four CRISPR loci in the S. thermophilus DGCC7710 genome were detected, including loci previously thought to be inactive. Many Cas proteins were found to be constitutively expressed, but several demonstrated increased abundance during peak infection, including the Cas9 proteins from the CRISPR1 and CRISPR3 loci, which are key players in the interference phase of the CRISPR/Cas response. Altogether, these results provide novel insights into the proteomic response of S. thermophilus, specifically CRISPR-associated proteins, upon phage 2972 infection.« less

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling.

PubMed

Puente-Marin, Sara; Nombela, Iván; Ciordia, Sergio; Mena, María Carmen; Chico, Verónica; Coll, Julio; Ortega-Villaizan, María Del Mar

2018-04-09

Nucleated red blood cells (RBCs) of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq) and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a) fractionation into cytosolic and membrane fractions, (b) hemoglobin removal of the cytosolic fraction, (c) protein digestion, and (d) a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII), leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic

Identification of indicator proteins associated with flooding injury in soybean seedlings using label-free quantitative proteomics.

PubMed

Nanjo, Yohei; Nakamura, Takuji; Komatsu, Setsuko

2013-11-01

Flooding injury is one of the abiotic constraints on soybean growth. An experimental system established for evaluating flooding injury in soybean seedlings indicated that the degree of injury is dependent on seedling density in floodwater. Dissolved oxygen levels in the floodwater were decreased by the seedlings and correlated with the degree of injury. To understand the molecular mechanism responsible for the injury, proteomic alterations in soybean seedlings that correlated with severity of stress were analyzed using label-free quantitative proteomics. The analysis showed that the abundance of proteins involved in cell wall modification, such as polygalacturonase inhibitor-like and expansin-like B1-like proteins, which may be associated with the defense system, increased dependence on stress at both the protein and mRNA levels in all organs during flooding. The manner of alteration in abundance of these proteins was distinct from those of other responsive proteins. Furthermore, proteins also showing specific changes in abundance in the root tip included protein phosphatase 2A subunit-like proteins, which are possibly involved in flooding-induced root tip cell death. Additionally, decreases in abundance of cell wall synthesis-related proteins, such as cinnamyl-alcohol dehydrogenase and cellulose synthase-interactive protein-like proteins, were identified in hypocotyls of seedlings grown for 3 days after flooding, and these proteins may be associated with suppression of growth after flooding. These flooding injury-associated proteins can be defined as indicator proteins for severity of flooding stress in soybean.

Sequential protein extraction as an efficient method for improved proteome coverage in larvae of Atlantic salmon (Salmo salar).

PubMed

Nuez-Ortín, Waldo G; Carter, Chris G; Nichols, Peter D; Wilson, Richard

2016-07-01

Understanding diet- and environmentally induced physiological changes in fish larvae is a major goal for the aquaculture industry. Proteomic analysis of whole fish larvae comprising multiple tissues offers considerable potential but is challenging due to the very large dynamic range of protein abundance. To extend the coverage of the larval phase of the Atlantic salmon (Salmo salar) proteome, we applied a two-step sequential extraction (SE) method, based on differential protein solubility, using a nondenaturing buffer containing 150 mM NaCl followed by a denaturing buffer containing 7 M urea and 2 M thiourea. Extracts prepared using SE and one-step direct extraction were characterized via label-free shotgun proteomics using nanoLC-MS/MS (LTQ-Orbitrap). SE partitioned the proteins into two fractions of approximately equal amounts, but with very distinct protein composition, leading to identification of ∼40% more proteins than direct extraction. This fractionation strategy enabled the most detailed characterization of the salmon larval proteome to date and provides a platform for greater understanding of physiological changes in whole fish larvae. The MS data are available via the ProteomeXchange Consortium PRIDE partner repository, dataset PXD003366. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic analysis of the dorsal and ventral hippocampus of rats maintained on a high fat and refined sugar diet.

PubMed

Francis, Heather M; Mirzaei, Mehdi; Pardey, Margery C; Haynes, Paul A; Cornish, Jennifer L

2013-10-01

The typical Western diet, rich in high saturated fat and refined sugar (HFS), has been shown to increase cognitive decline with aging and Alzheimer's disease, and to affect cognitive functions that are dependent on the hippocampus, including memory processes and reversal learning. To investigate neurophysiological changes underlying these impairments, we employed a proteomic approach to identify differentially expressed proteins in the rat dorsal and ventral hippocampus following maintenance on an HFS diet. Rats maintained on the HFS diet for 8 weeks were impaired on a novel object recognition task that assesses memory and on a Morris Water Maze task assessing reversal learning. Quantitative label-free shotgun proteomic analysis was conducted on biological triplicates for each group. For the dorsal hippocampus, 59 proteins were upregulated and 36 downregulated in the HFS group compared to controls. Pathway ana-lysis revealed changes to proteins involved in molecular transport and cellular and molecular signaling, and changes to signaling pathways including calcium signaling, citrate cycle, and oxidative phosphorylation. For the ventral hippocampus, 25 proteins were upregulated and 27 downregulated in HFS fed rats. Differentially expressed proteins were involved in cell-to-cell signaling and interaction, and cellular and molecular function. Changes to signaling pathways included protein ubiquitination, ubiquinone biosynthesis, oxidative phosphorylation, and mitochondrial dysfunction. This is the first shotgun proteomics study to examine protein changes in the hippocampus following long-term consumption of a HFS diet, identifying changes to a large number of proteins including those involved in synaptic plasticity and energy metabolism. All MS data have been deposited in the ProteomeXchange with identifier PXD000028. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics.

PubMed

Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C; McNeilly, Tom N; Weidt, Stefan K; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P David; Zadoks, Ruth N

2016-08-16

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously.

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.

Label-Free Proteomic Analysis of Protein Changes in the Striatum during Chronic Ethanol Use and Early Withdrawal

PubMed Central

Ayers-Ringler, Jennifer R.; Oliveros, Alfredo; Qiu, Yanyan; Lindberg, Daniel M.; Hinton, David J.; Moore, Raymond M.; Dasari, Surendra; Choi, Doo-Sup

2016-01-01

The molecular mechanisms underlying the neuronal signaling changes in alcohol addiction and withdrawal are complex and multifaceted. The cortico-striatal circuit is highly implicated in these processes, and the striatum plays a significant role not only in the early stages of addiction, but in the developed-addictive state as well, including withdrawal symptoms. Transcriptional analysis is a useful method for determining changes in gene expression, however, the results do not always accurately correlate with protein levels. In this study, we employ label-free proteomic analysis to determine changes in protein expression within the striatum during chronic ethanol use and early withdrawal. The striatum, composed primarily of medium spiny GABAergic neurons, glutamatergic and dopaminergic nerve terminals and astrocytes, is relatively homogeneous for proteomic analysis. We were able to analyze more than 5000 proteins from both the dorsal (caudate and putamen) and ventral (nucleus accumbens) striatum and identified significant changes following chronic intermittent ethanol exposure and acute (8 h) withdrawal compared to ethanol naïve and ethanol exposure groups respectively. Our results showed significant changes in proteins involved in glutamate and opioid peptide signaling, and also uncovered novel pathways including mitochondrial function and lipid/cholesterol metabolism, as revealed by changes in electron transport chain proteins and RXR activation pathways. These results will be useful in the development of novel treatments for alcohol withdrawal and thereby aid in recovery from alcohol use disorder. PMID:27014007

15N-metabolic labeling for comparative plasma membrane proteomics in Arabidopsis cells.

PubMed

Lanquar, Viviane; Kuhn, Lauriane; Lelièvre, Françoise; Khafif, Mehdi; Espagne, Christelle; Bruley, Christophe; Barbier-Brygoo, Hélène; Garin, Jérôme; Thomine, Sébastien

2007-03-01

An important goal for proteomic studies is the global comparison of proteomes from different genotypes, tissues, or physiological conditions. This has so far been mostly achieved by densitometric comparison of spot intensities after protein separation by 2-DE. However, the physicochemical properties of membrane proteins preclude the use of 2-DE. Here, we describe the use of in vivo labeling by the stable isotope 15N as an alternative approach for comparative membrane proteomic studies in plant cells. We confirm that 15N-metabolic labeling of proteins is possible and efficient in Arabidopsis suspension cells. Quantification of 14N versus 15N MS signals reflects the relative abundance of 14N and 15N proteins in the sample analyzed. We describe the use of 15N-metabolic labeling to perform a partial comparative analysis of Arabidopsis cells following cadmium exposure. By focusing our attention on plasma membrane proteins, we were able to confidently identify proteins showing up to 5-fold regulation compared to unexposed cells. This study provides a proof of principle that 15N-metabolic labeling is a useful technique for comparative membrane proteome studies.

Label-Free Differential Proteomics and Quantification of Exoenzymes from Isolates of the Entomopathogenic Fungus Beauveria bassiana

PubMed Central

Dionisio, Giuseppe; Kryger, Per; Steenberg, Tove

2016-01-01

Beauveria bassiana is an entomopathogenic fungus that grows both in vivo and in vitro. In vivo it can colonize live insect hosts, and tissue digestion occurs by secreted hydrolytic exoenzymes. It can also colonize dead insect tissue provided this is free from competing microorganisms. Depending on whether the host is alive or dead the expression (quality/quantity) of the exoenzymes may vary. We have grown several isolates of B. bassiana in shaking flasks for 120 h at 25 °C in order to evaluate the maximal exoenzyme production using two diet regimes. As sole carbon, nitrogen, and phosphate sources we used 1% shrimp chitin and either 0.5% w/v of dead intact American cockroach (Periplaneta americana) or their isolated cuticles. This is the first report of a differential proteomics of B. bassiana exoenzymes performed by label-free nano-LC MS/MS. Total proteolytic enzyme activity was mainly due to Pr1A or Pr1B depending on the isolate and the diet regime. The most differentially secreted enzymes were: the cuticle-degrading subtilisin Pr1A, GH13 alpha-glycosidase, glucan endo-1,3-beta-glucosidase, subtilisin-like proteinase Spm1, lipase 1, beta-1,3 exoglucanase, and endo-1,3-beta-glucosidase. Among the B. bassiana isolates analyzed, Bb 678 and Bb BG were the most active in Pr1A secretion. PMID:27754403

Label-Free Differential Proteomics and Quantification of Exoenzymes from Isolates of the Entomopathogenic Fungus Beauveria bassiana.

PubMed

Dionisio, Giuseppe; Kryger, Per; Steenberg, Tove

2016-10-14

Beauveria bassiana is an entomopathogenic fungus that grows both in vivo and in vitro. In vivo it can colonize live insect hosts, and tissue digestion occurs by secreted hydrolytic exoenzymes. It can also colonize dead insect tissue provided this is free from competing microorganisms. Depending on whether the host is alive or dead the expression (quality/quantity) of the exoenzymes may vary. We have grown several isolates of B. bassiana in shaking flasks for 120 h at 25 °C in order to evaluate the maximal exoenzyme production using two diet regimes. As sole carbon, nitrogen, and phosphate sources we used 1% shrimp chitin and either 0.5% w / v of dead intact American cockroach ( Periplaneta americana ) or their isolated cuticles. This is the first report of a differential proteomics of B. bassiana exoenzymes performed by label-free nano-LC MS/MS. Total proteolytic enzyme activity was mainly due to Pr1A or Pr1B depending on the isolate and the diet regime. The most differentially secreted enzymes were: the cuticle-degrading subtilisin Pr1A, GH13 alpha-glycosidase, glucan endo-1,3-beta-glucosidase, subtilisin-like proteinase Spm1, lipase 1, beta-1,3 exoglucanase, and endo-1,3-beta-glucosidase. Among the B. bassiana isolates analyzed, Bb 678 and Bb BG were the most active in Pr1A secretion.

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling

PubMed Central

Puente-Marin, Sara; Ciordia, Sergio; Mena, María Carmen; Chico, Verónica; Coll, Julio

2018-01-01

Nucleated red blood cells (RBCs) of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq) and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a) fractionation into cytosolic and membrane fractions, (b) hemoglobin removal of the cytosolic fraction, (c) protein digestion, and (d) a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII), leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation. PMID:29642539

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

PubMed

Braaksma, Machtelt; Martens-Uzunova, Elena S; Punt, Peter J; Schaap, Peter J

2010-10-19

The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

PubMed Central

2010-01-01

Background The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. Results A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. Conclusions We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions. PMID:20959013

Quantitative proteome analysis using isobaric peptide termini labeling (IPTL).

PubMed

Arntzen, Magnus O; Koehler, Christian J; Treumann, Achim; Thiede, Bernd

2011-01-01

The quantitative comparison of proteome level changes across biological samples has become an essential feature in proteomics that remains challenging. We have recently introduced isobaric peptide termini labeling (IPTL), a novel strategy for isobaric quantification based on the derivatization of peptide termini with complementary isotopically labeled reagents. Unlike non-isobaric quantification methods, sample complexity at the MS level is not increased, providing improved sensitivity and protein coverage. The distinguishing feature of IPTL when comparing it to more established isobaric labeling methods (iTRAQ and TMT) is the presence of quantification signatures in all sequence-determining ions in MS/MS spectra, not only in the low mass reporter ion region. This makes IPTL a quantification method that is accessible to mass spectrometers with limited capabilities in the low mass range. Also, the presence of several quantification points in each MS/MS spectrum increases the robustness of the quantification procedure.

Current Challenges in Detecting Food Allergens by Shotgun and Targeted Proteomic Approaches: A Case Study on Traces of Peanut Allergens in Baked Cookies

PubMed Central

Pedreschi, Romina; Nørgaard, Jørgen; Maquet, Alain

2012-01-01

There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 μg peanut g−1 matrix) in baked cookies. PMID:22413066

Label-Free Quantitative Proteomic Analysis of Chitosan Oligosaccharide-Treated Rice Infected with Southern Rice Black-Streaked Dwarf Virus.

PubMed

Yang, Anming; Yu, Lu; Chen, Zhuo; Zhang, Shanxue; Shi, Jing; Zhao, Xiaozhen; Yang, Yuanyou; Hu, Deyu; Song, Baoan

2017-05-18

Southern rice black-streaked dwarf virus (SRBSDV) has spread from thesouth of China to the north of Vietnam in the past few years and severelyinfluenced rice production. Its long incubation period and early symptoms are not evident; thus, controlling it is difficult. Chitosan oligosaccharide (COS) is a green plant immunomodulator. Early studies showed that preventing and controlling SRBSDV have a certain effect and reduce disease infection rate, but its underlying controlling and preventing mechanism is unclear. In this study, label-free proteomics was used to analyze differentially expressed proteins in rice after COS treatment. The results showed that COS can up-regulate the plant defense-related proteins and down-regulate the protein expression levels of SRBSDV. Meanwhile, quantitative real-time PCR test results showed that COS can improve defense gene expression in rice. Moreover, COS can enhance the defense enzymatic activities of peroxidase, superoxide dismutase and catalase through mitogen-activated protein kinase signaling cascade pathway, and enhance the rice disease resistance.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644970

A Straightforward and Highly Efficient Precipitation/On-pellet Digestion Procedure Coupled to a Long Gradient Nano-LC Separation and Orbitrap Mass Spectrometry for Label-free Expression Profiling of the Swine Heart Mitochondrial Proteome

PubMed Central

Duan, Xiaotao; Young, Rebecca; Straubinger, Robert M.; Page, Brian J.; Cao, Jin; Wang, Hao; Yu, Haoying; Canty, John M.; Qu, Jun

2009-01-01

For label-free expression profiling of tissue proteomes, efficient protein extraction, thorough and quantitative sample cleanup and digestion procedures, as well as sufficient and reproducible chromatographic separation, are highly desirable but remain challenging. However, optimal methodology has remained elusive, especially for proteomes that are rich in membrane proteins, such as the mitochondria. Here we describe a straightforward and reproducible sample preparation procedure, coupled with a highly selective and sensitive nano-LC/Orbitrap analysis, which enables reliable and comprehensive expression profiling of tissue mitochondria. The mitochondrial proteome of swine heart was selected as a test system. Efficient protein extraction was accomplished using a strong buffer containing both ionic and non-ionic detergents. Overnight precipitation was used for cleanup of the extract, and the sample was subjected to an optimized 2-step, on-pellet digestion approach. In the first step, the protein pellet was dissolved via a 4 h tryptic digestion under vigorous agitation, which nano-LC/LTQ/ETD showed to produce large and incompletely cleaved tryptic peptides. The mixture was then reduced, alkylated, and digested into its full complement of tryptic peptides with additional trypsin. This solvent precipitation/on-pellet digestion procedure achieved significantly higher and more reproducible peptide recovery of the mitochondrial preparation, than observed using a prevalent alternative procedure for label-free expression profiling, SDS-PAGE/in-gel digestion (87% vs. 54%). Furthermore, uneven peptide losses were lower than observed with SDS-PAGE/in-gel digestion. The resulting peptides were sufficiently resolved by a 5 h gradient using a nano-LC configuration that features a low-void-volume, high chromatographic reproducibility, and an LTQ/Orbitrap analyzer for protein identification and quantification. The developed method was employed for label-free comparison of the

Lipid raft proteome reveals that oxidative phosphorylation system is associated with the plasma membrane.

PubMed

Kim, Bong-Woo; Lee, Chang Seok; Yi, Jae-Sung; Lee, Joo-Hyung; Lee, Joong-Won; Choo, Hyo-Jung; Jung, Soon-Young; Kim, Min-Sik; Lee, Sang-Won; Lee, Myung-Shik; Yoon, Gyesoon; Ko, Young-Gyu

2010-12-01

Although accumulating proteomic analyses have supported the fact that mitochondrial oxidative phosphorylation (OXPHOS) complexes are localized in lipid rafts, which mediate cell signaling, immune response and host-pathogen interactions, there has been no in-depth study of the physiological functions of lipid-raft OXPHOS complexes. Here, we show that many subunits of OXPHOS complexes were identified from the lipid rafts of human adipocytes, C2C12 myotubes, Jurkat cells and surface biotin-labeled Jurkat cells via shotgun proteomic analysis. We discuss the findings of OXPHOS complexes in lipid rafts, the role of the surface ATP synthase complex as a receptor for various ligands and extracellular superoxide generation by plasma membrane oxidative phosphorylation complexes.

Extracellular protein analysis of activated sludge and their functions in wastewater treatment plant by shotgun proteomics.

PubMed

Zhang, Peng; Shen, Yu; Guo, Jin-Song; Li, Chun; Wang, Han; Chen, You-Peng; Yan, Peng; Yang, Ji-Xiang; Fang, Fang

2015-07-10

In this work, proteins in extracellular polymeric substances extracted from anaerobic, anoxic and aerobic sludges of wastewater treatment plant (WWTP) were analyzed to probe their origins and functions. Extracellular proteins in WWTP sludges were identified using shotgun proteomics, and 130, 108 and 114 proteins in anaerobic, anoxic and aerobic samples were classified, respectively. Most proteins originated from cell and cell part, and their most major molecular functions were catalytic activity and binding activity. The results exhibited that the main roles of extracellular proteins in activated sludges were multivalence cations and organic molecules binding, as well as in catalysis and degradation. The catalytic activity proteins were more widespread in anaerobic sludge compared with those in anoxic and aerobic sludges. The structure difference between anaerobic and aerobic sludges could be associated with their catalytic activities proteins. The results also put forward a relation between the macro characteristics of activated sludges and micro functions of extracellular proteins in biological wastewater treatment process.

Quantitative proteomics reveals the kinetics of trypsin-catalyzed protein digestion.

PubMed

Pan, Yanbo; Cheng, Kai; Mao, Jiawei; Liu, Fangjie; Liu, Jing; Ye, Mingliang; Zou, Hanfa

2014-10-01

Trypsin is the popular protease to digest proteins into peptides in shotgun proteomics, but few studies have attempted to systematically investigate the kinetics of trypsin-catalyzed protein digestion in proteome samples. In this study, we applied quantitative proteomics via triplex stable isotope dimethyl labeling to investigate the kinetics of trypsin-catalyzed cleavage. It was found that trypsin cleaves the C-terminal to lysine (K) and arginine (R) residues with higher rates for R. And the cleavage sites surrounded by neutral residues could be quickly cut, while those with neighboring charged residues (D/E/K/R) or proline residue (P) could be slowly cut. In a proteome sample, a huge number of proteins with different physical chemical properties coexists. If any type of protein could be preferably digested, then limited digestion could be applied to reduce the sample complexity. However, we found that protein abundance and other physicochemical properties, such as molecular weight (Mw), grand average of hydropathicity (GRAVY), aliphatic index, and isoelectric point (pI) have no notable correlation with digestion priority of proteins.

Analytical performance of reciprocal isotope labeling of proteome digests for quantitative proteomics and its application for comparative studies of aerobic and anaerobic Escherichia coli proteomes.

PubMed

Lo, Andy; Weiner, Joel H; Li, Liang

2013-09-17

Due to limited sample amounts, instrument time considerations, and reagent costs, only a small number of replicate experiments are typically performed for quantitative proteome analyses. Generation of reproducible data that can be readily assessed for consistency within a small number of datasets is critical for accurate quantification. We report our investigation of a strategy using reciprocal isotope labeling of two comparative samples as a tool for determining proteome changes. Reciprocal labeling was evaluated to determine the internal consistency of quantified proteome changes from Escherichia coli grown under aerobic and anaerobic conditions. Qualitatively, the peptide overlap between replicate analyses of the same sample and reverse labeled samples were found to be within 8%. Quantitatively, reciprocal analyses showed only a slight increase in average overall inconsistency when compared with replicate analyses (1.29 vs. 1.24-fold difference). Most importantly, reverse labeling was successfully used to identify spurious values resulting from incorrect peptide identifications and poor peak fitting. After removal of 5% of the peptide data with low reproducibility, a total of 275 differentially expressed proteins (>1.50-fold difference) were consistently identified and were then subjected to bioinformatics analysis. General considerations and guidelines for reciprocal labeling experimental design and biological significance of obtained results are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Bioaffinity magnetic reactor for peptide digestion followed by analysis using bottom-up shotgun proteomics strategy.

PubMed

Korecká, Lucie; Jankovicová, Barbora; Krenková, Jana; Hernychová, Lenka; Slováková, Marcela; Le-Nell, Anne; Chmelik, Josef; Foret, Frantisek; Viovy, Jean-Louis; Bilková, Zusana

2008-02-01

We report an efficient and streamlined way to improve the analysis and identification of peptides and proteins in complex mixtures of soluble proteins, cell lysates, etc. By using the shotgun proteomics methodology combined with bioaffinity purification we can remove or minimize the interference contamination of a complex tryptic digest and so avoid the time-consuming separation steps before the final MS analysis. We have proved that by means of enzymatic fragmentation (endoproteinases with Arg-C or/and Lys-C specificity) connected with the isolation of specific peptides we can obtain a simplified peptide mixture for easier identification of the entire protein. A new bioaffinity sorbent was developed for this purpose. Anhydrotrypsin (AHT), an inactive form of trypsin with an affinity for peptides with arginine (Arg) or lysine (Lys) at the C-terminus, was immobilized onto micro/nanoparticles with superparamagnetic properties (silica magnetite particles (SiMAG)-Carboxyl, Chemicell, Germany). This AHT carrier with a determined binding capacity (26.8 nmol/mg of carrier) was tested with a model peptide, human neurotensin, and the resulting MS spectra confirmed the validity of this approach.

Modified filter-aided sample preparation (FASP) method increases peptide and protein identifications for shotgun proteomics.

PubMed

Ni, Mao-Wei; Wang, Lu; Chen, Wei; Mou, Han-Zhou; Zhou, Jie; Zheng, Zhi-Guo

2017-01-30

Mass spectrometry (MS)-based protein identification depends mainly on protein extraction and digestion. Although sodium dodecyl sulfate (SDS) can preclude enzymatic digestion and interfere with MS analysis, it is still the most widely used surfactant in these steps. To overcome these disadvantages, a SDS-compatible proteomic technique for SDS removal prior to MS-based analyses was developed, namely filter-aided sample preparation (FASP). Herein, based on the effectiveness of sodium deoxycholate and a detergent removal spin column, we developed a modified FASP (mFASP) method and compared its overall performance, total number of peptides and proteins identified for shotgun proteomic experiments with that of the FASP method. Identification of 4570 ± 392 and 9139 ± 317 peptides and description of 862 ± 46 and 1377 ± 33 protein groups with two or more peptides from the ovarian cancer cell line A2780 was accomplished by FASP and mFASP methods, respectively. The mFASP method (21.2 ± 0.2%) had higher average peptide to protein coverage than FASP method (13.2 ± 0.5%). More hydrophobic peptides were identified by mFASP than by FASP, as indicated by the GRAVY score distribution. The reported method enables reliable and efficient identification of proteins and peptides in whole-cell extracts containing SDS. The new approach allows for higher throughput (the simultaneous identification of more proteins), a more comprehensive investigation of proteins, and potentially the discovery of new biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

PubMed

The, Matthew; Käll, Lukas

2016-03-04

Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).

Proteome Characterization of Leaves in Common Bean

PubMed Central

Robison, Faith M.; Heuberger, Adam L.; Brick, Mark A.; Prenni, Jessica E.

2015-01-01

Dry edible bean (Phaseolus vulgaris L.) is a globally relevant food crop. The bean genome was recently sequenced and annotated allowing for proteomics investigations aimed at characterization of leaf phenotypes important to agriculture. The objective of this study was to utilize a shotgun proteomics approach to characterize the leaf proteome and to identify protein abundance differences between two bean lines with known variation in their physiological resistance to biotic stresses. Overall, 640 proteins were confidently identified. Among these are proteins known to be involved in a variety of molecular functions including oxidoreductase activity, binding peroxidase activity, and hydrolase activity. Twenty nine proteins were found to significantly vary in abundance (p-value < 0.05) between the two bean lines, including proteins associated with biotic stress. To our knowledge, this work represents the first large scale shotgun proteomic analysis of beans and our results lay the groundwork for future studies designed to investigate the molecular mechanisms involved in pathogen resistance. PMID:28248269

Deciphering Multifactorial Resistance Phenotypes in Acinetobacter baumannii by Genomics and Targeted Label-free Proteomics.

PubMed

Cecchini, Tiphaine; Yoon, Eun-Jeong; Charretier, Yannick; Bardet, Chloé; Beaulieu, Corinne; Lacoux, Xavier; Docquier, Jean-Denis; Lemoine, Jerome; Courvalin, Patrice; Grillot-Courvalin, Catherine; Charrier, Jean-Philippe

2018-03-01

Resistance to β-lactams in Acinetobacter baumannii involves various mechanisms. To decipher them, whole genome sequencing (WGS) and real-time quantitative polymerase chain reaction (RT-qPCR) were complemented by mass spectrometry (MS) in selected reaction monitoring mode (SRM) in 39 clinical isolates. The targeted label-free proteomic approach enabled, in one hour and using a single method, the quantitative detection of 16 proteins associated with antibiotic resistance: eight acquired β-lactamases ( i.e. GES, NDM-1, OXA-23, OXA-24, OXA-58, PER, TEM-1, and VEB), two resident β-lactamases ( i.e. ADC and OXA-51-like) and six components of the two major efflux systems ( i.e. AdeABC and AdeIJK). Results were normalized using "bacterial quantotypic peptides," i.e. peptide markers of the bacterial quantity, to obtain precise protein quantitation (on average 8.93% coefficient of variation for three biological replicates). This allowed to correlate the levels of resistance to β-lactam with those of the production of acquired as well as resident β-lactamases or of efflux systems. SRM detected enhanced ADC or OXA-51-like production and absence or increased efflux pump production. Precise protein quantitation was particularly valuable to detect resistance mechanisms mediated by regulated genes or by overexpression of chromosomal genes. Combination of WGS and MS, two orthogonal and complementary techniques, allows thereby interpretation of the resistance phenotypes at the molecular level. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue.

PubMed

Röwer, Claudia; Vissers, Johannes P C; Koy, Cornelia; Kipping, Marc; Hecker, Michael; Reimer, Toralf; Gerber, Bernd; Thiesen, Hans-Jürgen; Glocker, Michael O

2009-12-01

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

Proteomic profiling of ATM kinase proficient and deficient cell lines upon blockage of proteasome activity☆

PubMed Central

Marzano, Valeria; Santini, Simonetta; Rossi, Claudia; Zucchelli, Mirco; D'Alessandro, Annamaria; Marchetti, Carlo; Mingardi, Michele; Stagni, Venturina; Barilà, Daniela; Urbani, Andrea

2012-01-01

Ataxia Telangiectasia Mutated (ATM) protein kinase is a key effector in the modulation of the functionality of some important stress responses, including DNA damage and oxidative stress response, and its deficiency is the hallmark of Ataxia Telangiectasia (A-T), a rare genetic disorder. ATM modulates the activity of hundreds of target proteins, essential for the correct balance between proliferation and cell death. The aim of this study is to evaluate the phenotypic adaptation at the protein level both in basal condition and in presence of proteasome blockage in order to identify the molecules whose level and stability are modulated through ATM expression. We pursued a comparative analysis of ATM deficient and proficient lymphoblastoid cells by label-free shotgun proteomic experiments comparing the panel of proteins differentially expressed. Through a non-supervised comparative bioinformatic analysis these data provided an insight on the functional role of ATM deficiency in cellular carbohydrate metabolism's regulation. This hypothesis has been demonstrated by targeted metabolic fingerprint analysis SRM (Selected Reaction Monitoring) on specific thermodynamic checkpoints of glycolysis. This article is part of a Special Issue entitled: Translational Proteomics. PMID:22641158

A linear programming model for protein inference problem in shotgun proteomics.

PubMed

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Quantitative Proteomics by Metabolic Labeling of Model Organisms*

PubMed Central

Gouw, Joost W.; Krijgsveld, Jeroen; Heck, Albert J. R.

2010-01-01

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life. PMID:19955089

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

PubMed

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

A Framework for Intelligent Data Acquisition and Real-Time Database Searching for Shotgun Proteomics*

PubMed Central

Graumann, Johannes; Scheltema, Richard A.; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-01-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides “on-the-fly” within 30 ms, well within the time constraints of a shotgun fragmentation “topN” method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available. PMID:22171319

Shotgun proteomics reveals specific modulated protein patterns in tears of patients with primary open angle glaucoma naïve to therapy.

PubMed

Pieragostino, Damiana; Agnifili, Luca; Fasanella, Vincenzo; D'Aguanno, Simona; Mastropasqua, Rodolfo; Di Ilio, Carmine; Sacchetta, Paolo; Urbani, Andrea; Del Boccio, Piero

2013-06-01

Primary open angle glaucoma (POAG) is one of the main causes of irreversible blindness worldwide. The pathogenesis of POAG is still unclear. Alteration and sclerosis of trabecular meshwork with changes in aqueous humor molecular composition seem to play the key role. Increased intraocular pressure is widely known to be the main risk factor for the onset and progression of the disease. Unfortunately, the early diagnosis of POAG still remains the main challenge. In order to provide insight into the patho-physiology of glaucoma, here we report a shotgun proteomics approach to tears of patients with POAG naïve to therapy. Our proteomics results showed 27 differential tear proteins in POAG vs. CTRL comparison (25 up regulated proteins in the POAG group and two unique proteins in the CTRL group), 16 of which were associated with inflammatory response, free radical scavenging, cell-to-cell signaling and interaction. Overall the protein modulation shown in POAG tears proves the involvement of biochemical networks linked to inflammation. Among all regulated proteins, a sub-group of 12 up-regulated proteins in naïve POAG patients were found to be down-regulated in medically controlled POAG patients treated with prostanoid analogues (PGA), as reported in our previous work (i.e., lipocalin-1, lysozyme C, lactotransferrin, proline-rich-protein 4, prolactin-inducible protein, zinc-alpha-2-glycoprotein, polymeric immunoglobulin receptor, cystatin S, Ig kappa chain C region, Ig alpha-2 chain C region, immunoglobulin J chain, Ig alpha-1 chain C region). In summary, our findings indicate that the POAG tears protein expression is a mixture of increased inflammatory proteins that could be potential biomarkers of the disease, and their regulation may be involved in the mechanism by which PGA are able to decrease the intraocular pressure in glaucoma patients.

Uncertainty estimation of predictions of peptides' chromatographic retention times in shotgun proteomics.

PubMed

Maboudi Afkham, Heydar; Qiu, Xuanbin; The, Matthew; Käll, Lukas

2017-02-15

Liquid chromatography is frequently used as a means to reduce the complexity of peptide-mixtures in shotgun proteomics. For such systems, the time when a peptide is released from a chromatography column and registered in the mass spectrometer is referred to as the peptide's retention time . Using heuristics or machine learning techniques, previous studies have demonstrated that it is possible to predict the retention time of a peptide from its amino acid sequence. In this paper, we are applying Gaussian Process Regression to the feature representation of a previously described predictor E lude . Using this framework, we demonstrate that it is possible to estimate the uncertainty of the prediction made by the model. Here we show how this uncertainty relates to the actual error of the prediction. In our experiments, we observe a strong correlation between the estimated uncertainty provided by Gaussian Process Regression and the actual prediction error. This relation provides us with new means for assessment of the predictions. We demonstrate how a subset of the peptides can be selected with lower prediction error compared to the whole set. We also demonstrate how such predicted standard deviations can be used for designing adaptive windowing strategies. lukas.kall@scilifelab.se. Our software and the data used in our experiments is publicly available and can be downloaded from https://github.com/statisticalbiotechnology/GPTime . © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Label-free quantitative proteomic analysis of pre-flowering PMeV-infected Carica papaya L.

PubMed

Soares, Eduardo de A; Werth, Emily G; Madroñero, Leidy J; Ventura, José A; Rodrigues, Silas P; Hicks, Leslie M; Fernandes, Patricia M B

2017-01-16

Papaya meleira virus (PMeV) infects papaya (Carica papaya L.) and leads to Papaya Sticky Disease (PSD) or "Meleira", characterized by a spontaneous exudation of latex from fruits and leaves only in the post-flowering developmental stage. The latex oxidizes in contact with air and accumulates as a sticky substance on the plant organs, impairing papaya fruit's marketing and exportation. To understand pre-flowering C. papaya resistance to PMeV, an LC-MS/MS-based label-free proteomics approach was used to assess the differential proteome of PMeV-infected pre-flowering C. papaya vs. uninfected (control) plants. In this study, 1333 proteins were identified, of which 111 proteins showed a significant abundance change (57 increased and 54 decreased) and supports the hypothesis of increased photosynthesis and reduction of 26S-proteassoma activity and cell-wall remodeling. All of these results suggest that increased photosynthetic activity has a positive effect on the induction of plant immunity, whereas the reduction of caspase-like activity and the observed changes in the cell-wall associated proteins impairs the full activation of defense response based on hypersensitive response and viral movement obstruction in pre-flowering C. papaya plants. The papaya (Carica papaya L.) fruit's production is severely limited by the occurrence of Papaya meleira virus (PMeV) infection, which causes Papaya Sticky Disease (PSD). Despite the efforts to understand key features involved with the plant×virus interaction, PSD management is still largely based on the observation of the first disease symptoms in the field, followed by the elimination of the diseased plants. However, C. papaya develops PSD only after flowering, i.e. about six-months after planting, and the virus inoculum sources are kept in field. The development of PMeV resistant genotypes is impaired by the limited knowledge about C. papaya resistance against viruses. The occurrence of a resistance/tolerance mechanism to PSD

Label-free Quantitative Proteomics of Mouse Cerebrospinal Fluid Detects β-Site APP Cleaving Enzyme (BACE1) Protease Substrates In Vivo*

PubMed Central

Dislich, Bastian; Wohlrab, Felix; Bachhuber, Teresa; Müller, Stephan A.; Kuhn, Peer-Hendrik; Hogl, Sebastian; Meyer-Luehmann, Melanie; Lichtenthaler, Stefan F.

2015-01-01

Analysis of murine cerebrospinal fluid (CSF) by quantitative mass spectrometry is challenging because of low CSF volume, low total protein concentration, and the presence of highly abundant proteins such as albumin. We demonstrate that the CSF proteome of individual mice can be analyzed in a quantitative manner to a depth of several hundred proteins in a robust and simple workflow consisting of single ultra HPLC runs on a benchtop mass spectrometer. The workflow is validated by a comparative analysis of BACE1−/− and wild-type mice using label-free quantification. The protease BACE1 cleaves the amyloid precursor protein (APP) as well as several other substrates and is a major drug target in Alzheimer's disease. We identified a total of 715 proteins with at least 2 unique peptides and quantified 522 of those proteins in CSF from BACE1−/− and wild-type mice. Several proteins, including the known BACE1 substrates APP, APLP1, CHL1 and contactin-2 showed lower abundance in the CSF of BACE1−/− mice, demonstrating that BACE1 substrate identification is possible from CSF. Additionally, ectonucleotide pyrophosphatase 5 was identified as a novel BACE1 substrate and validated in cells using immunoblots and by an in vitro BACE1 protease assay. Likewise, receptor-type tyrosine-protein phosphatase N2 and plexin domain-containing 2 were confirmed as BACE1 substrates by in vitro assays. Taken together, our study shows the deepest characterization of the mouse CSF proteome to date and the first quantitative analysis of the CSF proteome of individual mice. The BACE1 substrates identified in CSF may serve as biomarkers to monitor BACE1 activity in Alzheimer patients treated with BACE inhibitors. PMID:26139848

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Urine Sample Preparation in 96-Well Filter Plates for Quantitative Clinical Proteomics

PubMed Central

2015-01-01

Urine is an important, noninvasively collected body fluid source for the diagnosis and prognosis of human diseases. Liquid chromatography mass spectrometry (LC-MS) based shotgun proteomics has evolved as a sensitive and informative technique to discover candidate disease biomarkers from urine specimens. Filter-aided sample preparation (FASP) generates peptide samples from protein mixtures of cell lysate or body fluid origin. Here, we describe a FASP method adapted to 96-well filter plates, named 96FASP. Soluble urine concentrates containing ∼10 μg of total protein were processed by 96FASP and LC-MS resulting in 700–900 protein identifications at a 1% false discovery rate (FDR). The experimental repeatability, as assessed by label-free quantification and Pearson correlation analysis for shared proteins among replicates, was high (R ≥ 0.97). Application to urinary pellet lysates which is of particular interest in the context of urinary tract infection analysis was also demonstrated. On average, 1700 proteins (±398) were identified in five experiments. In a pilot study using 96FASP for analysis of eight soluble urine samples, we demonstrated that protein profiles of technical replicates invariably clustered; the protein profiles for distinct urine donors were very different from each other. Robust, highly parallel methods to generate peptide mixtures from urine and other body fluids are critical to increase cost-effectiveness in clinical proteomics projects. This 96FASP method has potential to become a gold standard for high-throughput quantitative clinical proteomics. PMID:24797144

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

Comparative evaluation of seven commercial products for human serum enrichment/depletion by shotgun proteomics.

PubMed

Pisanu, Salvatore; Biosa, Grazia; Carcangiu, Laura; Uzzau, Sergio; Pagnozzi, Daniela

2018-08-01

Seven commercial products for human serum depletion/enrichment were tested and compared by shotgun proteomics. Methods were based on four different capturing agents: antibodies (Qproteome Albumin/IgG Depletion kit, ProteoPrep Immunoaffinity Albumin and IgG Depletion Kit, Top 2 Abundant Protein Depletion Spin Columns, and Top 12 Abundant Protein Depletion Spin Columns), specific ligands (Albumin/IgG Removal), mixture of antibodies and ligands (Albumin and IgG Depletion SpinTrap), and combinatorial peptide ligand libraries (ProteoMiner beads), respectively. All procedures, to a greater or lesser extent, allowed an increase of identified proteins. ProteoMiner beads provided the highest number of proteins; Albumin and IgG Depletion SpinTrap and ProteoPrep Immunoaffinity Albumin and IgG Depletion Kit resulted the most efficient in albumin removal; Top 2 and Top 12 Abundant Protein Depletion Spin Columns decreased the overall immunoglobulin levels more than other procedures, whereas specifically gamma immunoglobulins were mostly removed by Albumin and IgG Depletion SpinTrap, ProteoPrep Immunoaffinity Albumin and IgG Depletion Kit, and Top 2 Abundant Protein Depletion Spin Columns. Albumin/IgG Removal, a resin bound to a mixture of protein A and Cibacron Blue, behaved less efficiently than the other products. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of Fe and Mn deficiencies on the protein profiles of tomato (Solanum lycopersicum) xylem sap as revealed by shotgun analyses

USDA-ARS?s Scientific Manuscript database

The aim of this work was to study the effects of Fe and Mn deficiencies on the xylem sap proteome of tomato using a shotgun proteomic approach, with the final goal of elucidating plant response mechanisms to these stresses. This approach yielded 643 proteins reliably identified and quantified with 7...

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.

Shotgun label-free quantitative proteomics of developing peanut (Arachis hypogaea L.) seed

USDA-ARS?s Scientific Manuscript database

Legume seeds and peanuts, in particular, are an inexpensive source of plant proteins and edible oil. Owing to their importance in global food security, it is necessary to understand the genetic, biochemical, and physiological mechanisms controlling seed quality and nutritive attributes. A comprehens...

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

Label-free proteomics assisted by affinity enrichment for elucidating the chemical reactivity of the liver mitochondrial proteome toward adduction by the lipid electrophile 4-hydroxy-2-nonenal (HNE)

NASA Astrophysics Data System (ADS)

Maier, Claudia

2016-03-01

The analysis of oxidative stress-induced post-translational modifications remains challenging due to the chemical diversity of these modifications, the possibility of the presence of positional isomers and the low stoichiometry of the modified proteins present in a cell or tissue proteome. Alcoholic liver disease (ALD) is a multifactorial disease in which mitochondrial dysfunction and oxidative stress have been identified as being critically involved in the progression of the disease from steatosis to cirrhosis. Ethanol metabolism leads to increased levels of reactive oxygen species (ROS), glutathione depletion and lipid peroxidation. Posttranslational modification of proteins by electrophilic products of lipid peroxidation has been associated with governing redox-associated signaling mechanisms, but also as contributing to protein dysfunction leading to organelle and liver injury. In particular the prototypical α,β-unsaturated aldehyde, 4-hydroxy-2-nonenal (HNE), has been extensively studied as marker of increased oxidative stress in hepatocytes. In this study, we combined a LC-MS label-free quantification method and affinity enrichment to assess the dose-dependent insult by HNE on the proteome of rat liver mitochondria. We used a carbonyl-selective probe, the ARP probe, to label HNE-protein adducts and to perform affinity capture at the protein level. Using LC-MS to obtain protein abundance estimates, a list of protein targets was obtained with increasing concentration of HNE used in the exposure studies. In parallel, we performed affinity capture at the peptide level to acquire site-specific information. Examining the concentration-dependence of the protein modifications, we observed distinct reactivity profiles for HNE-protein adduction. Pathway analysis indicated that proteins associated with metabolic processes, including amino acid, fatty acid and glyoxylate and dicarboxylate metabolism, bile acid synthesis and TCA cycle, showed enhanced reactivity to HNE

Studies of a biochemical factory: tomato trichome deep expressed sequence tag sequencing and proteomics.

PubMed

Schilmiller, Anthony L; Miner, Dennis P; Larson, Matthew; McDowell, Eric; Gang, David R; Wilkerson, Curtis; Last, Robert L

2010-07-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.

Single Cell Immuno-Laser Microdissection Coupled to Label-Free Proteomics to Reveal the Proteotypes of Human Brain Cells After Ischemia.

PubMed

García-Berrocoso, Teresa; Llombart, Víctor; Colàs-Campàs, Laura; Hainard, Alexandre; Licker, Virginie; Penalba, Anna; Ramiro, Laura; Simats, Alba; Bustamante, Alejandro; Martínez-Saez, Elena; Canals, Francesc; Sanchez, Jean-Charles; Montaner, Joan

2018-01-01

Cerebral ischemia entails rapid tissue damage in the affected brain area causing devastating neurological dysfunction. How each component of the neurovascular unit contributes or responds to the ischemic insult in the context of the human brain has not been solved yet. Thus, the analysis of the proteome is a straightforward approach to unraveling these cell proteotypes. In this study, post-mortem brain slices from ischemic stroke patients were obtained corresponding to infarcted (IC) and contralateral (CL) areas. By means of laser microdissection, neurons and blood brain barrier structures (BBB) were isolated and analyzed using label-free quantification. MS data are available via ProteomeXchange with identifier PXD003519. Ninety proteins were identified only in neurons, 260 proteins only in the BBB and 261 proteins in both cell types. Bioinformatics analyses revealed that repair processes, mainly related to synaptic plasticity, are outlined in microdissected neurons, with nonexclusive important functions found in the BBB. A total of 30 proteins showing p < 0.05 and fold-change> 2 between IC and CL areas were considered meaningful in this study: 13 in neurons, 14 in the BBB and 3 in both cell types. Twelve of these proteins were selected as candidates and analyzed by immunohistofluorescence in independent brains. The MS findings were completely verified for neuronal SAHH2 and SRSF1 whereas the presence in both cell types of GABT and EAA2 was only validated in neurons. In addition, SAHH2 showed its potential as a prognostic biomarker of neurological improvement when analyzed early in the plasma of ischemic stroke patients. Therefore, the quantitative proteomes of neurons and the BBB (or proteotypes) after human brain ischemia presented here contribute to increasing the knowledge regarding the molecular mechanisms of ischemic stroke pathology and highlight new proteins that might represent putative biomarkers of brain ischemia or therapeutic targets. © 2018 by The

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.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Saturation Fluorescence Labeling of Proteins for Proteomic Analyses

PubMed Central

Pretzer, Elizabeth; Wiktorowicz, John E.

2008-01-01

We present here an optimized and cost-effective approach to saturation fluorescence labeling of protein thiols for proteomic analysis. We investigated a number of conditions and reagent concentrations including a disulfide reducing agent (TCEP), pH, incubation time, linearity of labeling, and saturating dye: protein thiol ratio with protein standards to gauge specific and non-specific labeling. Efficacy of labeling under these conditions was quantified using specific fluorescence estimation, defined as the ratio of fluorescence pixel intensities and Coomassie-stained pixel intensities of bands after digital imaging. Factors leading to specific vs. non-specific labeling in the presence of thiourea are also discussed. We have found that reproducible saturation of available Cys residues of the proteins used as labeling standards (human carbonic anhydrase I, enolase, α-lactalbumin) is achieved at 50-100-fold excess of the uncharged maleimide-functionalized BODIPY™ dyes over Cys. We confirm our previous findings and those of others that the maleimide dyes are not impacted by the presence of 2M thiourea. Moreover, we establish that 2 mM TCEP used as reductant is optimal. We also establish further that labeling is optimal at pH 7.5 and complete after 30 min. Low non-specific labeling was gauged by the inclusion of non-Cys containing proteins (horse myoglobin, bovine carbonic anhydrase) to the labeling mixture. We also show that the dye exhibits little to no effect on the two dimensional mobilities of labeled proteins derived from cells. PMID:18191033

Label-free Proteomic Reveals that Cowpea Severe Mosaic Virus Transiently Suppresses the Host Leaf Protein Accumulation During the Compatible Interaction with Cowpea (Vigna unguiculata [L.] Walp.).

PubMed

Paiva, Ana L S; Oliveira, Jose T A; de Souza, Gustavo A; Vasconcelos, Ilka M

2016-12-02

Viruses are important plant pathogens that threaten diverse crops worldwide. Diseases caused by Cowpea severe mosaic virus (CPSMV) have drawn attention because of the serious damages they cause to economically important crops including cowpea. This work was undertaken to quantify and identify the responsive proteins of a susceptible cowpea genotype infected with CPSMV, in comparison with mock-inoculated controls, using label-free quantitative proteomics and databanks, aiming at providing insights on the molecular basis of this compatible interaction. Cowpea leaves were mock- or CPSMV-inoculated and 2 and 6 days later proteins were extracted and analyzed. More than 3000 proteins were identified (data available via ProteomeXchange, identifier PXD005025) and 75 and 55 of them differentially accumulated in response to CPSMV, at 2 and 6 DAI, respectively. At 2 DAI, 76% of the proteins decreased in amount and 24% increased. However, at 6 DAI, 100% of the identified proteins increased. Thus, CPSMV transiently suppresses the synthesis of proteins involved particularly in the redox homeostasis, protein synthesis, defense, stress, RNA/DNA metabolism, signaling, and other functions, allowing viral invasion and spread in cowpea tissues.

Robust Label-free, Quantitative Profiling of Circulating Plasma Microparticle (MP) Associated Proteins*

PubMed Central

Braga-Lagache, Sophie; Buchs, Natasha; Iacovache, Mircea-Ioan; Zuber, Benoît; Jackson, Christopher Benjamin

2016-01-01

Cells of the vascular system release spherical vesicles, called microparticles, in the size range of 0.1–1 μm induced by a variety of stress factors resulting in variable concentrations between health and disease. Furthermore, microparticles have intercellular communication/signaling properties and interfere with inflammation and coagulation pathways. Today's most used analytical technology for microparticle characterization, flow cytometry, is lacking sensitivity and specificity, which might have led to the publication of contradicting results in the past. We propose the use of nano-liquid chromatography two-stage mass spectrometry as a nonbiased tool for quantitative MP proteome analysis. For this, we developed an improved microparticle isolation protocol and quantified the microparticle protein composition of twelve healthy volunteers with a label-free, data-dependent and independent proteomics approach on a quadrupole orbitrap instrument. Using aliquots of 250 μl platelet-free plasma from one individual donor, we achieved excellent reproducibility with an interassay coefficient of variation of 2.7 ± 1.7% (mean ± 1 standard deviation) on individual peptide intensities across 27 acquisitions performed over a period of 3.5 months. We show that the microparticle proteome between twelve healthy volunteers were remarkably similar, and that it is clearly distinguishable from whole cell and platelet lysates. We propose the use of the proteome profile shown in this work as a quality criterion for microparticle purity in proteomics studies. Furthermore, one freeze thaw cycle damaged the microparticle integrity, articulated by a loss of cytoplasm proteins, encompassing a specific set of proteins involved in regulating dynamic structures of the cytoskeleton, and thrombin activation leading to MP clotting. On the other hand, plasma membrane protein composition was unaffected. Finally, we show that multiplexed data-independent acquisition can be used for relative

Species and tissues specific differentiation of processed animal proteins in aquafeeds using proteomics tools.

PubMed

Rasinger, J D; Marbaix, H; Dieu, M; Fumière, O; Mauro, S; Palmblad, M; Raes, M; Berntssen, M H G

2016-09-16

The rapidly growing aquaculture industry drives the search for sustainable protein sources in fish feed. In the European Union (EU) since 2013 non-ruminant processed animal proteins (PAP) are again permitted to be used in aquafeeds. To ensure that commercial fish feeds do not contain PAP from prohibited species, EU reference methods were established. However, due to the heterogeneous and complex nature of PAP complementary methods are required to guarantee the safe use of this fish feed ingredient. In addition, there is a need for tissue specific PAP detection to identify the sources (i.e. bovine carcass, blood, or meat) of illegal PAP use. In the present study, we investigated and compared different protein extraction, solubilisation and digestion protocols on different proteomics platforms for the detection and differentiation of prohibited PAP. In addition, we assessed if tissue specific PAP detection was feasible using proteomics tools. All work was performed independently in two different laboratories. We found that irrespective of sample preparation gel-based proteomics tools were inappropriate when working with PAP. Gel-free shotgun proteomics approaches in combination with direct spectral comparison were able to provide quality species and tissue specific data to complement and refine current methods of PAP detection and identification. To guarantee the safe use of processed animal protein (PAP) in aquafeeds efficient PAP detection and monitoring tools are required. The present study investigated and compared various proteomics workflows and shows that the application of shotgun proteomics in combination with direct comparison of spectral libraries provides for the desired species and tissue specific classification of this heat sterilized and pressure treated (≥133°C, at 3bar for 20min) protein feed ingredient. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of skin anti-aging clinical benefits of an association of ingredients from marine and maritime origins: Ex vivo evaluation using a label-free quantitative proteomic and customized data processing approach.

PubMed

Hameury, Sebastien; Borderie, Laurent; Monneuse, Jean-Marc; Skorski, Gilbert; Pradines, Dominique

2018-05-23

The application of ingredients from marine and maritime origins is increasingly common in skin care products, driven by consumer expectations for natural ingredients. However, these ingredients are typically studied for a few isolated in vitro activities. The purpose of this study was to carry out a comprehensive evaluation of the activity on the skin of an association of ingredients from marine and maritime origins using label-free quantitative proteomic analysis, in order to predict the clinical benefits if used in a skin care product. An aqueous gel containing 6.1% of ingredients from marine and maritime origins (amino acid-enriched giant kelp extract, trace element-enriched seawater, dedifferentiated sea fennel cells) was topically applied on human skin explants. The skin explants' proteome was analyzed in a label-free manner by high-performance liquid nano-chromatography coupled with tandem mass spectrometry. A specific data processing pipeline (CORAVALID) providing an objective and comprehensive interpretation of the statistically relevant biological activities processed the results. Compared to untreated skin explants, 64 proteins were significantly regulated by the gel treatment (q-value ≤ 0.05). Computer data processing revealed an activity of the ingredients on the epidermis and the dermis. These significantly regulated proteins are involved in gene expression, cell survival and metabolism, inflammatory processes, dermal extracellular matrix synthesis, melanogenesis and keratinocyte proliferation, migration, and differentiation. These results suggest that the tested ingredients could help to preserve a healthy epidermis and dermis, and possibly to prevent the visible signs of skin aging. © 2018 The Authors. Journal of Cosmetic Dermatology Published by Wiley Periodicals, Inc.

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.

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.

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

Label-free proteomic analysis to confirm the predicted proteome of Corynebacterium pseudotuberculosis under nitrosative stress mediated by nitric oxide.

PubMed

Silva, Wanderson M; Carvalho, Rodrigo D; Soares, Siomar C; Bastos, Isabela Fs; Folador, Edson L; Souza, Gustavo Hmf; Le Loir, Yves; Miyoshi, Anderson; Silva, Artur; Azevedo, Vasco

2014-12-04

Corynebacterium pseudotuberculosis biovar ovis is a facultative intracellular pathogen, and the etiological agent of caseous lymphadenitis in small ruminants. During the infection process, the bacterium is subjected to several stress conditions, including nitrosative stress, which is caused by nitric oxide (NO). In silico analysis of the genome of C. pseudotuberculosis ovis 1002 predicted several genes that could influence the resistance of this pathogen to nitrosative stress. Here, we applied high-throughput proteomics using high definition mass spectrometry to characterize the functional genome of C. pseudotuberculosis ovis 1002 in the presence of NO-donor Diethylenetriamine/nitric oxide adduct (DETA/NO), with the aim of identifying proteins involved in nitrosative stress resistance. We characterized 835 proteins, representing approximately 41% of the predicted proteome of C. pseudotuberculosis ovis 1002, following exposure to nitrosative stress. In total, 102 proteins were exclusive to the proteome of DETA/NO-induced cells, and a further 58 proteins were differentially regulated between the DETA/NO and control conditions. An interactomic analysis of the differential proteome of C. pseudotuberculosis in response to nitrosative stress was also performed. Our proteomic data set suggested the activation of both a general stress response and a specific nitrosative stress response, as well as changes in proteins involved in cellular metabolism, detoxification, transcriptional regulation, and DNA synthesis and repair. Our proteomic analysis validated previously-determined in silico data for C. pseudotuberculosis ovis 1002. In addition, proteomic screening performed in the presence of NO enabled the identification of a set of factors that can influence the resistance and survival of C. pseudotuberculosis during exposure to nitrosative stress.

Comparative Proteomic Analysis of Human Liver Tissue and Isolated Hepatocytes with a Focus on Proteins Determining Drug Exposure.

PubMed

Vildhede, Anna; Wiśniewski, Jacek R; Norén, Agneta; Karlgren, Maria; Artursson, Per

2015-08-07

Freshly isolated human hepatocytes are considered the gold standard for in vitro studies of liver functions, including drug transport, metabolism, and toxicity. For accurate predictions of the in vivo outcome, the isolated hepatocytes should reflect the phenotype of their in vivo counterpart, i.e., hepatocytes in human liver tissue. Here, we quantified and compared the membrane proteomes of freshly isolated hepatocytes and human liver tissue using a label-free shotgun proteomics approach. A total of 5144 unique proteins were identified, spanning over 6 orders of magnitude in abundance. There was a good global correlation in protein abundance. However, the expression of many plasma membrane proteins was lower in the isolated hepatocytes than in the liver tissue. This included transport proteins that determine hepatocyte exposure to many drugs and endogenous compounds. Pathway analysis of the differentially expressed proteins confirmed that hepatocytes are exposed to oxidative stress during isolation and suggested that plasma membrane proteins were degraded via the protein ubiquitination pathway. Finally, using pitavastatin as an example, we show how protein quantifications can improve in vitro predictions of in vivo liver clearance. We tentatively conclude that our data set will be a useful resource for improved hepatocyte predictions of the in vivo outcome.

NeuCode Labeling in Nematodes: Proteomic and Phosphoproteomic Impact of Ascaroside Treatment in Caenorhabditis elegans*

PubMed Central

Rhoads, Timothy W.; Prasad, Aman; Kwiecien, Nicholas W.; Merrill, Anna E.; Zawack, Kelson; Westphall, Michael S.; Schroeder, Frank C.; Kimble, Judith; Coon, Joshua J.

2015-01-01

The nematode Caenorhabditis elegans is an important model organism for biomedical research. We previously described NeuCode stable isotope labeling by amino acids in cell culture (SILAC), a method for accurate proteome quantification with potential for multiplexing beyond the limits of traditional stable isotope labeling by amino acids in cell culture. Here we apply NeuCode SILAC to profile the proteomic and phosphoproteomic response of C. elegans to two potent members of the ascaroside family of nematode pheromones. By consuming labeled E. coli as part of their diet, C. elegans nematodes quickly and easily incorporate the NeuCode heavy lysine isotopologues by the young adult stage. Using this approach, we report, at high confidence, one of the largest proteomic and phosphoproteomic data sets to date in C. elegans: 6596 proteins at a false discovery rate ≤ 1% and 6620 phosphorylation isoforms with localization probability ≥75%. Our data reveal a post-translational signature of pheromone sensing that includes many conserved proteins implicated in longevity and response to stress. PMID:26392051

Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry.

PubMed

Hmmier, Abduladim; O'Brien, Michael Emmet; Lynch, Vincent; Clynes, Martin; Morgan, Ross; Dowling, Paul

2017-06-01

Lung cancer is the leading cause of cancer-related mortality in both men and women throughout the world. The need to detect lung cancer at an early, potentially curable stage, is essential and may reduce mortality by 20%. The aim of this study was to identify distinct proteomic profiles in bronchoalveolar fluid (BALF) and plasma that are able to discriminate individuals with benign disease from those with non-small cell lung cancer (NSCLC). Using label-free mass spectrometry analysis of BALF during discovery-phase analysis, a significant number of proteins were found to have different abundance levels when comparing control to adenocarcinoma (AD) or squamous cell lung carcinoma (SqCC). Validation of candidate biomarkers identified in BALF was performed in a larger cohort of plasma samples by detection with enzyme-linked immunoassay. Four proteins (Cystatin-C, TIMP-1, Lipocalin-2 and HSP70/HSPA1A) were selected as a representative group from discovery phase mass spectrometry BALF analysis. Plasma levels of TIMP-1, Lipocalin-2 and Cystatin-C were found to be significantly elevated in AD and SqCC compared to control. The results presented in this study indicate that BALF is an important proximal biofluid for the discovery and identification of candidate lung cancer biomarkers. There is good correlation between the trend of protein abundance levels in BALF and that of plasma which validates this approach to develop a blood biomarker to aid lung cancer diagnosis, particularly in the era of lung cancer screening. The protein signatures identified also provide insight into the molecular mechanisms associated with lung malignancy.

Global analysis of the yeast lipidome by quantitative shotgun mass spectrometry.

PubMed

Ejsing, Christer S; Sampaio, Julio L; Surendranath, Vineeth; Duchoslav, Eva; Ekroos, Kim; Klemm, Robin W; Simons, Kai; Shevchenko, Andrej

2009-02-17

Although the transcriptome, proteome, and interactome of several eukaryotic model organisms have been described in detail, lipidomes remain relatively uncharacterized. Using Saccharomyces cerevisiae as an example, we demonstrate that automated shotgun lipidomics analysis enabled lipidome-wide absolute quantification of individual molecular lipid species by streamlined processing of a single sample of only 2 million yeast cells. By comparative lipidomics, we achieved the absolute quantification of 250 molecular lipid species covering 21 major lipid classes. This analysis provided approximately 95% coverage of the yeast lipidome achieved with 125-fold improvement in sensitivity compared with previous approaches. Comparative lipidomics demonstrated that growth temperature and defects in lipid biosynthesis induce ripple effects throughout the molecular composition of the yeast lipidome. This work serves as a resource for molecular characterization of eukaryotic lipidomes, and establishes shotgun lipidomics as a powerful platform for complementing biochemical studies and other systems-level approaches.

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

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

Gritsenko, Marina A.; Xu, Zhe; Liu, Tao

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification andmore » quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.« less

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS.

PubMed

Gritsenko, Marina A; Xu, Zhe; Liu, Tao; Smith, Richard D

2016-01-01

Comprehensive, quantitative information on abundances of proteins and their posttranslational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labeling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

Studies of a Biochemical Factory: Tomato Trichome Deep Expressed Sequence Tag Sequencing and Proteomics1[W][OA

PubMed Central

Schilmiller, Anthony L.; Miner, Dennis P.; Larson, Matthew; McDowell, Eric; Gang, David R.; Wilkerson, Curtis; Last, Robert L.

2010-01-01

Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces β-caryophyllene and α-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells. PMID:20431087

Proteomic analysis of protein interactions between Eimeria maxima sporozoites and chicken jejunal epithelial cells by shotgun LC-MS/MS.

PubMed

Huang, Jingwei; Liu, Tingqi; Li, Ke; Song, Xiaokai; Yan, Ruofeng; Xu, Lixin; Li, Xiangrui

2018-04-04

Eimeria maxima initiates infection by invading the jejunal epithelial cells of chicken. However, the proteins involved in invasion remain unknown. The research of the molecules that participate in the interactions between E. maxima sporozoites and host target cells will fill a gap in our understanding of the invasion system of this parasitic pathogen. In the present study, chicken jejunal epithelial cells were isolated and cultured in vitro. Western blot was employed to analyze the soluble proteins of E. maxima sporozoites that bound to chicken jejunal epithelial cells. Co-immunoprecipitation (co-IP) assay was used to separate the E. maxima proteins that bound to chicken jejunal epithelial cells. Shotgun LC-MS/MS technique was used for proteomics identification and Gene Ontology was employed for the bioinformatics analysis. The results of Western blot analysis showed that four proteins bands from jejunal epithelial cells co-cultured with soluble proteins of E. maxima sporozoites were recognized by the positive sera, with molecular weights of 70, 90, 95 and 130 kDa. The co-IP dilutions were analyzed by shotgun LC-MS/MS. A total of 204 proteins were identified in the E. maxima protein database using the MASCOT search engine. Thirty-five proteins including microneme protein 3 and 7 had more than two unique peptide counts and were annotated using Gene Ontology for molecular function, biological process and cellular localization. The results revealed that of the 35 annotated peptides, 22 (62.86%) were associated with binding activity and 15 (42.86%) were involved in catalytic activity. Our findings provide an insight into the interaction between E. maxima and the corresponding host cells and it is important for the understanding of molecular mechanisms underlying E. maxima invasion.

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues*

PubMed Central

Bruderer, Roland; Bernhardt, Oliver M.; Gandhi, Tejas; Miladinović, Saša M.; Cheng, Lin-Yang; Messner, Simon; Ehrenberger, Tobias; Zanotelli, Vito; Butscheid, Yulia; Escher, Claudia; Vitek, Olga; Rinner, Oliver; Reiter, Lukas

2015-01-01

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics. Utilizing HRM, we profiled acetaminophen (APAP)1-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD). Our findings imply that DIA should be the preferred method for quantitative protein profiling. PMID:25724911

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.

Proteome analysis of the Mycobacterium tuberculosis Beijing B0/W148 cluster

PubMed Central

Bespyatykh, Julia; Shitikov, Egor; Butenko, Ivan; Altukhov, Ilya; Alexeev, Dmitry; Mokrousov, Igor; Dogonadze, Marine; Zhuravlev, Viacheslav; Yablonsky, Peter; Ilina, Elena; Govorun, Vadim

2016-01-01

Beijing B0/W148, a “successful” clone of Mycobacterium tuberculosis, is widespread in the Russian Federation and some countries of the former Soviet Union. Here, we used label-free gel-LC-MS/MS shotgun proteomics to discover features of Beijing B0/W148 strains that could explain their success. Qualitative and quantitative proteome analyses of Beijing B0/W148 strains allowed us to identify 1,868 proteins, including 266 that were differentially abundant compared with the control strain H37Rv. To predict the biological effects of the observed differences in protein abundances, we performed Gene Ontology analysis together with analysis of protein-DNA interactions using a gene regulatory network. Our results demonstrate that Beijing B0/W148 strains have increased levels of enzymes responsible for long-chain fatty acid biosynthesis, along with a coincident decrease in the abundance of proteins responsible for their degradation. Together with high levels of HsaA (Rv3570c) protein, involved in steroid degradation, these findings provide a possible explanation for the increased transmissibility of Beijing B0/W148 strains and their survival in host macrophages. Among other, we confirmed a very low level of the SseA (Rv3283) protein in Beijing B0/W148 characteristic for all «modern» Beijing strains, which could lead to increased DNA oxidative damage, accumulation of mutations, and potentially facilitate the development of drug resistance. PMID:27356881

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.

Scaffold-free, label-free and nozzle-free biofabrication technology using magnetic levitational assembly.

PubMed

Parfenov, Vladislav A; Koudan, Elizaveta V; Bulanova, Elena A; Karalkin, Pavel A; Pereira, Frederico DAS; Norkin, Nikita E; Knyazeva, Alisa D; Gryadunova, Anna A; Petrov, Oleg F; Vasiliev, M M; Myasnikov, Maxim; Chernikov, Valery P; Kasyanov, Vladimir A; Marchenkov, Artem Yu; Brakke, Kenneth A; Khesuani, Yusef D; Demirci, Utkan; Mironov, Vladimir A

2018-05-31

Tissue spheroids have been proposed as building blocks in 3D biofabrication. Conventional magnetic force-driven 2D patterning of tissue spheroids requires prior cell labeling by magnetic nanoparticles, meanwhile a label-free approach for 3D magnetic levitational assembly has been introduced. Here we present first-time report on rapid assembly of 3D tissue construct using scaffold-free, nozzle-free and label-free magnetic levitation of tissue spheroids. Chondrospheres of standard size, shape and capable to fusion have been biofabricated from primary sheep chondrocytes using non-adhesive technology. Label-free magnetic levitation was performed using a prototype device equipped with permanent magnets in presence of gadolinium (Gd3+) in culture media, which enables magnetic levitation. Mathematical modeling and computer simulations were used for prediction of magnetic field and kinetics of tissue spheroids assembly into 3D tissue constructs. First, we used polystyrene beads to simulate the assembly of tissue spheroids and to determine the optimal settings for magnetic levitation in presence of Gd3+. Second, we proved the ability of chondrospheres to assemble rapidly into 3D tissue construct in the permanent magnetic field in the presence of Gd3+. Thus, scaffold- and label-free magnetic levitation of tissue spheroids is a promising approach for rapid 3D biofabrication and attractive alternative to label-based magnetic force-driven tissue engineering. . © 2018 IOP Publishing Ltd.

78 FR 47154 - Food Labeling; Gluten-Free Labeling of Foods

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-05

...The Food and Drug Administration (FDA or we) is issuing a final rule to define the term ``gluten-free'' for voluntary use in the labeling of foods. The final rule defines the term ``gluten-free'' to mean that the food bearing the claim does not contain an ingredient that is a gluten-containing grain (e.g., spelt wheat); an ingredient that is derived from a gluten-containing grain and that has not been processed to remove gluten (e.g., wheat flour); or an ingredient that is derived from a gluten-containing grain and that has been processed to remove gluten (e.g., wheat starch), if the use of that ingredient results in the presence of 20 parts per million (ppm) or more gluten in the food (i.e., 20 milligrams (mg) or more gluten per kilogram (kg) of food); or inherently does not contain gluten; and that any unavoidable presence of gluten in the food is below 20 ppm gluten (i.e., below 20 mg gluten per kg of food). A food that bears the claim ``no gluten,'' ``free of gluten,'' or ``without gluten'' in its labeling and fails to meet the requirements for a ``gluten-free'' claim will be deemed to be misbranded. In addition, a food whose labeling includes the term ``wheat'' in the ingredient list or in a separate ``Contains wheat'' statement as required by a section of the Federal Food, Drug, and Cosmetic Act (the FD&C Act) and also bears the claim ``gluten-free'' will be deemed to be misbranded unless its labeling also bears additional language clarifying that the wheat has been processed to allow the food to meet FDA requirements for a ``gluten-free'' claim. Establishing a definition of the term ``gluten-free'' and uniform conditions for its use in food labeling will help ensure that individuals with celiac disease are not misled and are provided with truthful and accurate information with respect to foods so labeled. We are issuing the final rule under the Food Allergen Labeling and Consumer Protection Act of 2004 (FALCPA).

Serum proteomic analysis identifies sex-specific differences in lipid metabolism and inflammation profiles in adults diagnosed with Asperger syndrome

PubMed Central

2014-01-01

Background The higher prevalence of Asperger Syndrome (AS) and other autism spectrum conditions in males has been known for many years. However, recent multiplex immunoassay profiling studies have shown that males and females with AS have distinct proteomic changes in serum. Methods Here, we analysed sera from adults diagnosed with AS (males = 14, females = 16) and controls (males = 13, females = 16) not on medication at the time of sample collection, using a combination of multiplex immunoassay and shotgun label-free liquid chromatography mass spectrometry (LC-MSE). The main objective was to identify sex-specific serum protein changes associated with AS. Results Multiplex immunoassay profiling led to identification of 16 proteins that were significantly altered in AS individuals in a sex-specific manner. Three of these proteins were altered in females (ADIPO, IgA, APOA1), seven were changed in males (BMP6, CTGF, ICAM1, IL-12p70, IL-16, TF, TNF-alpha) and six were changed in both sexes but in opposite directions (CHGA, EPO, IL-3, TENA, PAP, SHBG). Shotgun LC-MSE profiling led to identification of 13 serum proteins which had significant sex-specific changes in the AS group and, of these, 12 were altered in females (APOC2, APOE, ARMC3, CLC4K, FETUB, GLCE, MRRP1, PTPA, RN149, TLE1, TRIPB, ZC3HE) and one protein was altered in males (RGPD4). The free androgen index in females with AS showed an increased ratio of 1.63 compared to controls. Conclusion Taken together, the serum multiplex immunoassay and shotgun LC-MSE profiling results indicate that adult females with AS had alterations in proteins involved mostly in lipid transport and metabolism pathways, while adult males with AS showed changes predominantly in inflammation signalling. These results provide further evidence that the search for biomarkers or novel drug targets in AS may require stratification into male and female subgroups, and could lead to the development of novel targeted treatment

Characterization of Foodborne Strains of Staphylococcus aureus by Shotgun Proteomics: Functional Networks, Virulence Factors and Species-Specific Peptide Biomarkers

PubMed Central

Carrera, Mónica; Böhme, Karola; Gallardo, José M.; Barros-Velázquez, Jorge; Cañas, Benito; Calo-Mata, Pilar

2017-01-01

In the present work, we applied a shotgun proteomics approach for the fast and easy characterization of 20 different foodborne strains of Staphylococcus aureus (S. aureus), one of the most recognized foodborne pathogenic bacteria. A total of 644 non-redundant proteins were identified and analyzed via an easy and rapid protein sample preparation procedure. The results allowed the differentiation of several proteome datasets from the different strains (common, accessory, and unique datasets), which were used to determine relevant functional pathways and differentiate the strains into different Euclidean hierarchical clusters. Moreover, a predicted protein-protein interaction network of the foodborne S. aureus strains was created. The whole confidence network contains 77 nodes and 769 interactions. Most of the identified proteins were surface-associated proteins that were related to pathways and networks of energy, lipid metabolism and virulence. Twenty-seven virulence factors were identified, and most of them corresponded to autolysins, N-acetylmuramoyl-L-alanine amidases, phenol-soluble modulins, extracellular fibrinogen-binding proteins and virulence factor EsxA. Potential species-specific peptide biomarkers were screened. Twenty-one species-specific peptide biomarkers, belonging to eight different proteins (nickel-ABC transporter, N-acetylmuramoyl-L-alanine amidase, autolysin, clumping factor A, gram-positive signal peptide YSIRK, cysteine protease/staphopain, transcriptional regulator MarR, and transcriptional regulator Sar-A), were proposed to identify S. aureus. These results constitute the first major dataset of peptides and proteins of foodborne S. aureus strains. This repository may be useful for further studies, for the development of new therapeutic treatments for S. aureus food intoxications and for microbial source-tracking in foodstuffs. PMID:29312172

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

PubMed Central

Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

2016-01-01

Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

FSHD myotubes with different phenotypes exhibit distinct proteomes.

PubMed

Tassin, Alexandra; Leroy, Baptiste; Laoudj-Chenivesse, Dalila; Wauters, Armelle; Vanderplanck, Céline; Le Bihan, Marie-Catherine; Coppée, Frédérique; Wattiez, Ruddy; Belayew, Alexandra

2012-01-01

Facioscapulohumeral muscular dystrophy (FSHD) is a progressive muscle disorder linked to a contraction of the D4Z4 repeat array in the 4q35 subtelomeric region. This deletion induces epigenetic modifications that affect the expression of several genes located in the vicinity. In each D4Z4 element, we identified the double homeobox 4 (DUX4) gene. DUX4 expresses a transcription factor that plays a major role in the development of FSHD through the initiation of a large gene dysregulation cascade that causes myogenic differentiation defects, atrophy and reduced response to oxidative stress. Because miRNAs variably affect mRNA expression, proteomic approaches are required to define the dysregulated pathways in FSHD. In this study, we optimized a differential isotope protein labeling (ICPL) method combined with shotgun proteomic analysis using a gel-free system (2DLC-MS/MS) to study FSHD myotubes. Primary CD56(+) FSHD myoblasts were found to fuse into myotubes presenting various proportions of an atrophic or a disorganized phenotype. To better understand the FSHD myogenic defect, our improved proteomic procedure was used to compare predominantly atrophic or disorganized myotubes to the same matching healthy control. FSHD atrophic myotubes presented decreased structural and contractile muscle components. This phenotype suggests the occurrence of atrophy-associated proteolysis that likely results from the DUX4-mediated gene dysregulation cascade. The skeletal muscle myosin isoforms were decreased while non-muscle myosin complexes were more abundant. In FSHD disorganized myotubes, myosin isoforms were not reduced, and increased proteins were mostly involved in microtubule network organization and myofibrillar remodeling. A common feature of both FSHD myotube phenotypes was the disturbance of several caveolar proteins, such as PTRF and MURC. Taken together, our data suggest changes in trafficking and in the membrane microdomains of FSHD myotubes. Finally, the adjustment of a

FSHD Myotubes with Different Phenotypes Exhibit Distinct Proteomes

PubMed Central

Laoudj-Chenivesse, Dalila; Wauters, Armelle; Vanderplanck, Céline; Le Bihan, Marie-Catherine; Coppée, Frédérique; Wattiez, Ruddy; Belayew, Alexandra

2012-01-01

Facioscapulohumeral muscular dystrophy (FSHD) is a progressive muscle disorder linked to a contraction of the D4Z4 repeat array in the 4q35 subtelomeric region. This deletion induces epigenetic modifications that affect the expression of several genes located in the vicinity. In each D4Z4 element, we identified the double homeobox 4 (DUX4) gene. DUX4 expresses a transcription factor that plays a major role in the development of FSHD through the initiation of a large gene dysregulation cascade that causes myogenic differentiation defects, atrophy and reduced response to oxidative stress. Because miRNAs variably affect mRNA expression, proteomic approaches are required to define the dysregulated pathways in FSHD. In this study, we optimized a differential isotope protein labeling (ICPL) method combined with shotgun proteomic analysis using a gel-free system (2DLC-MS/MS) to study FSHD myotubes. Primary CD56+ FSHD myoblasts were found to fuse into myotubes presenting various proportions of an atrophic or a disorganized phenotype. To better understand the FSHD myogenic defect, our improved proteomic procedure was used to compare predominantly atrophic or disorganized myotubes to the same matching healthy control. FSHD atrophic myotubes presented decreased structural and contractile muscle components. This phenotype suggests the occurrence of atrophy-associated proteolysis that likely results from the DUX4-mediated gene dysregulation cascade. The skeletal muscle myosin isoforms were decreased while non-muscle myosin complexes were more abundant. In FSHD disorganized myotubes, myosin isoforms were not reduced, and increased proteins were mostly involved in microtubule network organization and myofibrillar remodeling. A common feature of both FSHD myotube phenotypes was the disturbance of several caveolar proteins, such as PTRF and MURC. Taken together, our data suggest changes in trafficking and in the membrane microdomains of FSHD myotubes. Finally, the adjustment of a

Differential quantitative proteomics of Porphyromonas gingivalis by linear ion trap mass spectrometry: non-label methods comparison, q-values and LOWESS curve fitting

PubMed Central

Xia, Qiangwei; Wang, Tiansong; Park, Yoonsuk; Lamont, Richard J.; Hackett, Murray

2009-01-01

Differential analysis of whole cell proteomes by mass spectrometry has largely been applied using various forms of stable isotope labeling. While metabolic stable isotope labeling has been the method of choice, it is often not possible to apply such an approach. Four different label free ways of calculating expression ratios in a classic “two-state” experiment are compared: signal intensity at the peptide level, signal intensity at the protein level, spectral counting at the peptide level, and spectral counting at the protein level. The quantitative data were mined from a dataset of 1245 qualitatively identified proteins, about 56% of the protein encoding open reading frames from Porphyromonas gingivalis, a Gram-negative intracellular pathogen being studied under extracellular and intracellular conditions. Two different control populations were compared against P. gingivalis internalized within a model human target cell line. The q-value statistic, a measure of false discovery rate previously applied to transcription microarrays, was applied to proteomics data. For spectral counting, the most logically consistent estimate of random error came from applying the locally weighted scatter plot smoothing procedure (LOWESS) to the most extreme ratios generated from a control technical replicate, thus setting upper and lower bounds for the region of experimentally observed random error. PMID:19337574

Shotgun protein sequencing: assembly of peptide tandem mass spectra from mixtures of modified proteins.

PubMed

Bandeira, Nuno; Clauser, Karl R; Pevzner, Pavel A

2007-07-01

Despite significant advances in the identification of known proteins, the analysis of unknown proteins by MS/MS still remains a challenging open problem. Although Klaus Biemann recognized the potential of MS/MS for sequencing of unknown proteins in the 1980s, low throughput Edman degradation followed by cloning still remains the main method to sequence unknown proteins. The automated interpretation of MS/MS spectra has been limited by a focus on individual spectra and has not capitalized on the information contained in spectra of overlapping peptides. Indeed the powerful shotgun DNA sequencing strategies have not been extended to automated protein sequencing. We demonstrate, for the first time, the feasibility of automated shotgun protein sequencing of protein mixtures by utilizing MS/MS spectra of overlapping and possibly modified peptides generated via multiple proteases of different specificities. We validate this approach by generating highly accurate de novo reconstructions of multiple regions of various proteins in western diamondback rattlesnake venom. We further argue that shotgun protein sequencing has the potential to overcome the limitations of current protein sequencing approaches and thus catalyze the otherwise impractical applications of proteomics methodologies in studies of unknown proteins.

High-resolution proteomic profiling of spider venom: expanding the toxin diversity of Phoneutria nigriventer venom.

PubMed

Liberato, Tarcísio; Troncone, Lanfranco Ranieri Paolo; Yamashiro, Edson T; Serrano, Solange M T; Zelanis, André

2016-03-01

Here we present a proteomic characterization of Phoneutria nigriventer venom. A shotgun proteomic approach allowed the identification, for the first time, of O-glycosyl hydrolases (chitinases) in P. nigriventer venom. The electrophoretic profiles under nonreducing and reducing conditions, and protein identification by mass spectrometry, indicated the presence of oligomeric toxin structures in the venom. Complementary proteomic approaches allowed for a qualitative and semi-quantitative profiling of P. nigriventer venom complexity, expanding its known venom proteome diversity.

Proteomics wants cRacker: automated standardized data analysis of LC-MS derived proteomic data.

PubMed

Zauber, Henrik; Schulze, Waltraud X

2012-11-02

The large-scale analysis of thousands of proteins under various experimental conditions or in mutant lines has gained more and more importance in hypothesis-driven scientific research and systems biology in the past years. Quantitative analysis by large scale proteomics using modern mass spectrometry usually results in long lists of peptide ion intensities. The main interest for most researchers, however, is to draw conclusions on the protein level. Postprocessing and combining peptide intensities of a proteomic data set requires expert knowledge, and the often repetitive and standardized manual calculations can be time-consuming. The analysis of complex samples can result in very large data sets (lists with several 1000s to 100,000 entries of different peptides) that cannot easily be analyzed using standard spreadsheet programs. To improve speed and consistency of the data analysis of LC-MS derived proteomic data, we developed cRacker. cRacker is an R-based program for automated downstream proteomic data analysis including data normalization strategies for metabolic labeling and label free quantitation. In addition, cRacker includes basic statistical analysis, such as clustering of data, or ANOVA and t tests for comparison between treatments. Results are presented in editable graphic formats and in list files.

Morphine biosynthesis in opium poppy involves two cell types: sieve elements and laticifers.

PubMed

Onoyovwe, Akpevwe; Hagel, Jillian M; Chen, Xue; Khan, Morgan F; Schriemer, David C; Facchini, Peter J

2013-10-01

Immunofluorescence labeling and shotgun proteomics were used to establish the cell type-specific localization of morphine biosynthesis in opium poppy (Papaver somniferum). Polyclonal antibodies for each of six enzymes involved in converting (R)-reticuline to morphine detected corresponding antigens in sieve elements of the phloem, as described previously for all upstream enzymes transforming (S)-norcoclaurine to (S)-reticuline. Validated shotgun proteomics performed on whole-stem and latex total protein extracts generated 2031 and 830 distinct protein families, respectively. Proteins corresponding to nine morphine biosynthetic enzymes were represented in the whole stem, whereas only four of the final five pathway enzymes were detected in the latex. Salutaridine synthase was detected in the whole stem, but not in the latex subproteome. The final three enzymes converting thebaine to morphine were among the most abundant active latex proteins despite a limited occurrence in laticifers suggested by immunofluorescence labeling. Multiple charge isoforms of two key O-demethylases in the latex were revealed by two-dimensional immunoblot analysis. Salutaridine biosynthesis appears to occur only in sieve elements, whereas conversion of thebaine to morphine is predominant in adjacent laticifers, which contain morphine-rich latex. Complementary use of immunofluorescence labeling and shotgun proteomics has substantially resolved the cellular localization of morphine biosynthesis in opium poppy.

A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics

PubMed Central

Nesvizhskii, Alexey I.

2010-01-01

This manuscript provides a comprehensive review of the peptide and protein identification process using tandem mass spectrometry (MS/MS) data generated in shotgun proteomic experiments. The commonly used methods for assigning peptide sequences to MS/MS spectra are critically discussed and compared, from basic strategies to advanced multi-stage approaches. A particular attention is paid to the problem of false-positive identifications. Existing statistical approaches for assessing the significance of peptide to spectrum matches are surveyed, ranging from single-spectrum approaches such as expectation values to global error rate estimation procedures such as false discovery rates and posterior probabilities. The importance of using auxiliary discriminant information (mass accuracy, peptide separation coordinates, digestion properties, and etc.) is discussed, and advanced computational approaches for joint modeling of multiple sources of information are presented. This review also includes a detailed analysis of the issues affecting the interpretation of data at the protein level, including the amplification of error rates when going from peptide to protein level, and the ambiguities in inferring the identifies of sample proteins in the presence of shared peptides. Commonly used methods for computing protein-level confidence scores are discussed in detail. The review concludes with a discussion of several outstanding computational issues. PMID:20816881

Shotgun proteomic analysis of Bombyx mori brain: emphasis on regulation of behavior and development of the nervous system.

PubMed

Wang, Guo-Bao; Zheng, Qin; Shen, Yun-Wang; Wu, Xiao-Feng

2016-02-01

The insect brain plays crucial roles in the regulation of growth and development and in all types of behavior. We used sodium dodecyl sulfate polyacrylamide gel electrophoresis and high-performance liquid chromatography - electron spray ionization tandem mass spectrometry (ESI-MS/MS) shotgun to identify the proteome of the silkworm brain, to investigate its protein composition and to understand their biological functions. A total of 2210 proteins with molecular weights in the range of 5.64-1539.82 kDa and isoelectric points in the range of 3.78-12.55 were identified. These proteins were annotated according to Gene Ontology Annotation into the categories of molecular function, biological process and cellular component. We characterized two categories of proteins: one includes behavior-related proteins involved in the regulation of behaviors, such as locomotion, reproduction and learning; the other consists of proteins related to the development or function of the nervous system. The identified proteins were classified into 283 different pathways according to KEGG analysis, including the PI3K-Akt signaling pathway which plays a crucial role in mediating survival signals in a wide range of neuronal cell types. This extensive protein profile provides a basis for further understanding of the physiological functions in the silkworm brain. © 2014 Institute of Zoology, Chinese Academy of Sciences.

The developmental proteome of Drosophila melanogaster

PubMed Central

Casas-Vila, Nuria; Bluhm, Alina; Sayols, Sergi; Dinges, Nadja; Dejung, Mario; Altenhein, Tina; Kappei, Dennis; Altenhein, Benjamin; Roignant, Jean-Yves; Butter, Falk

2017-01-01

Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface. PMID:28381612

Quantitative profiling of drug-associated proteomic alterations by combined 2-nitrobenzenesulfenyl chloride (NBS) isotope labeling and 2DE/MS identification.

PubMed

Ou, Keli; Kesuma, Djohan; Ganesan, Kumaresan; Yu, Kun; Soon, Sou Yen; Lee, Suet Ying; Goh, Xin Pei; Hooi, Michelle; Chen, Wei; Jikuya, Hiroyuki; Ichikawa, Tetsuo; Kuyama, Hiroki; Matsuo, Ei-ichi; Nishimura, Osamu; Tan, Patrick

2006-09-01

The identification of drug-responsive biomarkers in complex protein mixtures is an important goal of quantitative proteomics. Here, we describe a novel approach for identifying such drug-induced protein alterations, which combines 2-nitrobenzenesulfenyl chloride (NBS) tryptophan labeling with two-dimensional gel electrophoresis (2DE)/mass spectrometry (MS). Lysates from drug-treated and control samples are labeled with light or heavy NBS moiety and separated on a common 2DE gel, and protein alterations are identified by MS through the differential intensity of paired NBS peptide peaks. Using NBS/2DE/MS, we profiled the proteomic alterations induced by tamoxifen (TAM) in the estrogen receptor (ER) positive MCF-7 breast cancer cell line. Of 88 protein spots that significantly changed upon TAM treatment, 44 spots representing 23 distinct protein species were successfully identified with NBS-paired peptides. Of these 23 TAM-altered proteins, 16 (70%) have not been previously associated with TAM or ER activity. We found the NBS labeling procedure to be both technically and biologically reproducible, and the NBS/2DE/MS alterations exhibited good concordance with conventional 2DE differential protein quantitation, with discrepancies largely due to the comigration of distinct proteins in the regular 2DE gels. To validate the NBS/2DE/MS results, we used immunoblotting to confirm GRP78, CK19, and PA2G4 as bona fide TAM-regulated proteins. Furthermore, we demonstrate that PA2G4 expression can serve as a novel prognostic factor for disease-free survival in two independent breast cancer patient cohorts. To our knowledge, this is the first report describing the proteomic changes in breast cancer cells induced by TAM, the most commonly used selective estrogen receptor modulator (SERM). Our results indicate that NBS/2DE/MS may represent a more reliable approach for cellular protein quantitation than conventional 2DE approaches.

Quantitative proteomic analysis of cabernet sauvignon grape cells exposed to thermal stresses reveals alterations in sugar and phenylpropanoid metabolism.

PubMed

George, Iniga S; Pascovici, Dana; Mirzaei, Mehdi; Haynes, Paul A

2015-09-01

Grapes (Vitis vinifera) are a valuable fruit crop and wine production is a major industry. Global warming and expanded range of cultivation will expose grapes to more temperature stresses in future. Our study investigated protein level responses to abiotic stresses, with particular reference to proteomic changes induced by the impact of four different temperature stress regimes, including both hot and cold temperatures, on cultured grape cells. Cabernet Sauvignon cell suspension cultures grown at 26°C were subjected to 14 h of exposure to 34 and 42°C for heat stress, and 18 and 10°C for cold stress. Cells from the five temperatures were harvested in biological triplicates and label-free quantitative shotgun proteomic analysis was performed. A total of 2042 non-redundant proteins were identified from the five temperature points. Fifty-five proteins were only detected in extreme heat stress conditions (42°C) and 53 proteins were only detected at extreme cold stress conditions (10°C). Gene Ontology (GO) annotations of differentially expressed proteins provided insights into the metabolic pathways that are involved in temperature stress in grape cells. Sugar metabolism displayed switching between alternative and classical pathways during temperature stresses. Additionally, nine proteins involved in the phenylpropanoid pathway were greatly increased in abundance at extreme cold stress, and were thus found to be cold-responsive proteins. All MS data have been deposited in the ProteomeXchange with identifier PXD000977 (http://proteomecentral.proteomexchange.org/dataset/PXD000977). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Shotgun Proteomic Analysis of Plasma from Dairy Cattle Suffering from Footrot: Characterization of Potential Disease-Associated Factors

PubMed Central

Sun, Dongbo; Zhang, Hong; Guo, Donghua; Sun, Anguo; Wang, Hongbin

2013-01-01

The plasma proteome of healthy dairy cattle and those with footrot was investigated using a shotgun LC-MS/MS approach. In total, 648 proteins were identified in healthy plasma samples, of which 234 were non-redundant proteins and 123 were high-confidence proteins; 712 proteins were identified from footrot plasma samples, of which 272 were non-redundant proteins and 138 were high-confidence proteins. The high-confidence proteins showed significant differences between healthy and footrot plasma samples in molecular weight, isoelectric points and the Gene Ontology categories. 22 proteins were found that may differentiate between the two sets of plasma proteins, of which 16 potential differential expression (PDE) proteins from footrot plasma involved in immunoglobulins, innate immune recognition molecules, acute phase proteins, regulatory proteins, and cell adhesion and cytoskeletal proteins; 6 PDE proteins from healthy plasma involved in regulatory proteins, cytoskeletal proteins and coagulation factors. Of these PDE proteins, haptoglobin, SERPINA10 protein, afamin precursor, haptoglobin precursor, apolipoprotein D, predicted peptidoglycan recognition protein L (PGRP-L) and keratan sulfate proteoglycan (KS-PG) were suggested to be potential footrot-associated factors. The PDE proteins PGRP-L and KS-PG were highlighted as potential biomarkers of footrot in cattle. The resulting protein lists and potential differentially expressed proteins may provide valuable information to increase understanding of plasma protein profiles in cattle and to assist studies of footrot-associated factors. PMID:23418487

Insights from Proteomic Studies into Plant Somatic Embryogenesis.

PubMed

Heringer, Angelo Schuabb; Santa-Catarina, Claudete; Silveira, Vanildo

2018-03-01

Somatic embryogenesis is a biotechnological approach mainly used for the clonal propagation of different plants worldwide. In somatic embryogenesis, embryos arise from somatic cells under appropriate culture conditions. This plasticity in plants is a demonstration of true cellular totipotency and is the best approach among the genetic transformation protocols used for plant regeneration. Despite the importance of somatic embryogenesis, knowledge regarding the control of the somatic embryogenesis process is limited. Therefore, the elucidation of both the biochemical and molecular processes is important for understanding the mechanisms by which a single somatic cell becomes a whole plant. Modern proteomic techniques rely on an alternative method for the identification and quantification of proteins with different abundances in embryogenic cell cultures or somatic embryos and enable the identification of specific proteins related to somatic embryogenesis development. This review focuses on somatic embryogenesis studies that use gel-free shotgun proteomic analyses to categorize proteins that could enhance our understanding of particular aspects of the somatic embryogenesis process and identify possible targets for future studies. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Shotgun metaproteomics of the human distal gut microbiota

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

VerBerkmoes, N.C.; Russell, A.L.; Shah, M.

2008-10-15

The human gut contains a dense, complex and diverse microbial community, comprising the gut microbiome. Metagenomics has recently revealed the composition of genes in the gut microbiome, but provides no direct information about which genes are expressed or functioning. Therefore, our goal was to develop a novel approach to directly identify microbial proteins in fecal samples to gain information about the genes expressed and about key microbial functions in the human gut. We used a non-targeted, shotgun mass spectrometry-based whole community proteomics, or metaproteomics, approach for the first deep proteome measurements of thousands of proteins in human fecal samples, thusmore » demonstrating this approach on the most complex sample type to date. The resulting metaproteomes had a skewed distribution relative to the metagenome, with more proteins for translation, energy production and carbohydrate metabolism when compared to what was earlier predicted from metagenomics. Human proteins, including antimicrobial peptides, were also identified, providing a non-targeted glimpse of the host response to the microbiota. Several unknown proteins represented previously undescribed microbial pathways or host immune responses, revealing a novel complex interplay between the human host and its associated microbes.« less

Bacterial membrane proteomics.

PubMed

Poetsch, Ansgar; Wolters, Dirk

2008-10-01

About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.

Applicability of a high-throughput shotgun plasma protein screening approach in understanding maternal biological pathways relevant to infant birth weight outcome.

PubMed

Kumarathasan, P; Vincent, R; Das, D; Mohottalage, S; Blais, E; Blank, K; Karthikeyan, S; Vuong, N Q; Arbuckle, T E; Fraser, W D

2014-04-04

There are reports linking maternal nutritional status, smoking and environmental chemical exposures to adverse pregnancy outcomes. However, biological bases for association between some of these factors and birth outcomes are yet to be established. The objective of this preliminary work is to test the capability of a new high-throughput shotgun plasma proteomic screening in identifying maternal changes relevant to pregnancy outcome. A subset of third trimester plasma samples (N=12) associated with normal and low-birth weight infants were fractionated, tryptic-digested and analyzed for global proteomic changes using a MALDI-TOF-TOF-MS methodology. Mass spectral data were mined for candidate biomarkers using bioinformatic and statistical tools. Maternal plasma profiles of cytokines (e.g. IL8, TNF-α), chemokines (e.g. MCP-1) and cardiovascular endpoints (e.g. ET-1, MMP-9) were analyzed by a targeted approach using multiplex protein array and HPLC-Fluorescence methods. Target and global plasma proteomic markers were used to identify protein interaction networks and maternal biological pathways relevant to low infant birth weight. Our results exhibited the potential to discriminate specific maternal physiologies relevant to risk of adverse birth outcomes. This proteomic approach can be valuable in understanding the impacts of maternal factors such as environmental contaminant exposures and nutrition on birth outcomes in future work. We demonstrate here the fitness of mass spectrometry-based shot-gun proteomics for surveillance of biological changes in mothers, and for adverse pathway analysis in combination with target biomarker information. This approach has potential for enabling early detection of mothers at risk for low infant birth weight and preterm birth, and thus early intervention for mitigation and prevention of adverse pregnancy outcomes. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes? Copyright

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

2015-10-02

As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

Comparative proteomic analysis using samples obtained with laser microdissection and saturation dye labelling.

PubMed

Wilson, Kate E; Marouga, Rita; Prime, John E; Pashby, D Paul; Orange, Paul R; Crosier, Steven; Keith, Alexander B; Lathe, Richard; Mullins, John; Estibeiro, Peter; Bergling, Helene; Hawkins, Edward; Morris, Christopher M

2005-10-01

Comparative proteomic methods are rapidly being applied to many different biological systems including complex tissues. One pitfall of these methods is that in some cases, such as oncology and neuroscience, tissue complexity requires isolation of specific cell types and sample is limited. Laser microdissection (LMD) is commonly used for obtaining such samples for proteomic studies. We have combined LMD with sensitive thiol-reactive saturation dye labelling of protein samples and 2-D DIGE to identify protein changes in a test system, the isolated CA1 pyramidal neurone layer of a transgenic (Tg) rat carrying a human amyloid precursor protein transgene. Saturation dye labelling proved to be extremely sensitive with a spot map of over 5,000 proteins being readily produced from 5 mug total protein, with over 100 proteins being significantly altered at p < 0.0005. Of the proteins identified, all showed coherent changes associated with transgene expression. It was, however, difficult to identify significantly different proteins using PMF and MALDI-TOF on gels containing less than 500 mug total protein. The use of saturation dye labelling of limiting samples will therefore require the use of highly sensitive MS techniques to identify the significantly altered proteins isolated using methods such as LMD.

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).

Identification of aldolase A as a potential diagnostic biomarker for colorectal cancer based on proteomic analysis using formalin-fixed paraffin-embedded tissue.

PubMed

Yamamoto, Tetsushi; Kudo, Mitsuhiro; Peng, Wei-Xia; Takata, Hideyuki; Takakura, Hideki; Teduka, Kiyoshi; Fujii, Takenori; Mitamura, Kuniko; Taga, Atsushi; Uchida, Eiji; Naito, Zenya

2016-10-01

Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.

A proteomic insight into vitellogenesis during tick ovary maturation.

PubMed

Xavier, Marina Amaral; Tirloni, Lucas; Pinto, Antônio F M; Diedrich, Jolene K; Yates, John R; Mulenga, Albert; Logullo, Carlos; da Silva Vaz, Itabajara; Seixas, Adriana; Termignoni, Carlos

2018-03-16

Ticks are arthropod ectoparasites of importance for public and veterinary health. The understanding of tick oogenesis and embryogenesis could contribute to the development of novel control methods. However, to date, studies on the temporal dynamics of proteins during ovary development were not reported. In the present study we followed protein profile during ovary maturation. Proteomic analysis of ovary extracts was performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using shotgun strategy, in addition to dimethyl labelling-based protein quantification. A total of 3,756 proteins were identified, which were functionally annotated into 30 categories. Circa 80% of the annotated proteins belong to categories related to basal metabolism, such as protein synthesis and modification machineries, nuclear regulation, cytoskeleton, proteasome machinery, transcriptional machinery, energetic metabolism, extracellular matrix/cell adhesion, immunity, oxidation/detoxification metabolism, signal transduction, and storage. The abundance of selected proteins involved in yolk uptake and degradation, as well as vitellin accumulation during ovary maturation, was assessed using dimethyl-labelling quantification. In conclusion, proteins identified in this study provide a framework for future studies to elucidate tick development and validate candidate targets for novel control methods.

Interleukin-6 Induced "Acute" Phenotypic Microenvironment Promotes Th1 Anti-Tumor Immunity in Cryo-Thermal Therapy Revealed By Shotgun and Parallel Reaction Monitoring Proteomics.

PubMed

Xue, Ting; Liu, Ping; Zhou, Yong; Liu, Kun; Yang, Li; Moritz, Robert L; Yan, Wei; Xu, Lisa X

2016-01-01

Cryo-thermal therapy has been emerged as a promising novel therapeutic strategy for advanced breast cancer, triggering higher incidence of tumor regression and enhanced remission of metastasis than routine treatments. To better understand its anti-tumor mechanism, we utilized a spontaneous metastatic mouse model and quantitative proteomics to compare N-glycoproteome changes in 94 serum samples with and without treatment. We quantified 231 highly confident N-glycosylated proteins using iTRAQ shotgun proteomics. Among them, 53 showed significantly discriminated regulatory patterns over the time course, in which the acute phase response emerged as the most enhanced pathway. The anti-tumor feature of the acute response was further investigated using parallel reaction monitoring target proteomics and flow cytometry on 23 of the 53 significant proteins. We found that cryo-thermal therapy reset the tumor chronic inflammation to an "acute" phenotype, with up-regulation of acute phase proteins including IL-6 as a key regulator. The IL-6 mediated "acute" phenotype transformed IL-4 and Treg-promoting ICOSL expression to Th1-promoting IFN-γ and IL-12 production, augmented complement system activation and CD86(+)MHCII(+) dendritic cells maturation and enhanced the proliferation of Th1 memory cells. In addition, we found an increased production of tumor progression and metastatic inhibitory proteins under such "acute" environment, favoring the anti-metastatic effect. Moreover, cryo-thermal on tumors induced the strongest "acute" response compared to cryo/hyperthermia alone or cryo-thermal on healthy tissues, accompanying by the most pronounced anti-tumor immunological effect. In summary, we demonstrated that cryo-thermal therapy induced, IL-6 mediated "acute" microenvironment shifted the tumor chronic microenvironment from Th2 immunosuppressive and pro-tumorigenic to Th1 immunostimulatory and tumoricidal state. Moreover, the magnitude of "acute" and "danger" signals play a key

Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

PubMed

Matafora, Vittoria; Corno, Andrea; Ciliberto, Andrea; Bachi, Angela

2017-04-07

In global proteomic analysis, it is estimated that proteins span from millions to less than 100 copies per cell. The challenge of protein quantitation by classic shotgun proteomic techniques relies on the presence of missing values in peptides belonging to low-abundance proteins that lowers intraruns reproducibility affecting postdata statistical analysis. Here, we present a new analytical workflow MvM (missing value monitoring) able to recover quantitation of missing values generated by shotgun analysis. In particular, we used confident data-dependent acquisition (DDA) quantitation only for proteins measured in all the runs, while we filled the missing values with data-independent acquisition analysis using the library previously generated in DDA. We analyzed cell cycle regulated proteins, as they are low abundance proteins with highly dynamic expression levels. Indeed, we found that cell cycle related proteins are the major components of the missing values-rich proteome. Using the MvM workflow, we doubled the number of robustly quantified cell cycle related proteins, and we reduced the number of missing values achieving robust quantitation for proteins over ∼50 molecules per cell. MvM allows lower quantification variance among replicates for low abundance proteins with respect to DDA analysis, which demonstrates the potential of this novel workflow to measure low abundance, dynamically regulated proteins.

Differential label-free quantitative proteomic analysis of avian eggshell matrix and uterine fluid proteins associated with eggshell mechanical property.

PubMed

Sun, Congjiao; Xu, Guiyun; Yang, Ning

2013-12-01

Eggshell strength is a crucial economic trait for table egg production. During the process of eggshell formation, uncalcified eggs are bathed in uterine fluid that plays regulatory roles in eggshell calcification. In this study, a label-free MS-based protein quantification technology was used to detect differences in protein abundance between eggshell matrix from strong and weak eggs (shell matrix protein from strong eggshells and shell matrix protein from weak eggshells) and between the corresponding uterine fluids bathing strong and weak eggs (uterine fluid bathing strong eggs and uterine fluid bathing weak eggs) in a chicken population. Here, we reported the first global proteomic analysis of uterine fluid. A total of 577 and 466 proteins were identified in uterine fluid and eggshell matrix, respectively. Of 447 identified proteins in uterine fluid bathing strong eggs, up to 357 (80%) proteins were in common with proteins in uterine fluid bathing weak eggs. Similarly, up to 83% (328/396) of the proteins in shell matrix protein from strong eggshells were in common with the proteins in shell matrix protein from weak eggshells. The large amount of common proteins indicated that the difference in protein abundance should play essential roles in influencing eggshell strength. Ultimately, 15 proteins mainly relating to eggshell matrix specific proteins, calcium binding and transportation, protein folding and sorting, bone development or diseases, and thyroid hormone activity were considered to have closer association with the formation of strong eggshell. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

18O-labeled proteome reference as global internal standards for targeted quantification by selected reaction monitoring-mass spectrometry.

PubMed

Kim, Jong-Seo; Fillmore, Thomas L; Liu, Tao; Robinson, Errol; Hossain, Mahmud; Champion, Boyd L; Moore, Ronald J; Camp, David G; Smith, Richard D; Qian, Wei-Jun

2011-12-01

Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.

Abdominal shotgun trauma: A case report

PubMed Central

Toutouzas, Konstantinos G; Larentzakis, Andreas; Drimousis, Panagiotis; Riga, Maria; Theodorou, Dimitrios; Katsaragakis, Stylianos

2008-01-01

Introduction One of the most lethal mechanisms of injury is shotgun wound and particularly the abdominal one. Case presentation We report a case of a 45 years old male suffering abdominal shotgun trauma, who survived his injuries. Conclusion The management of the abdominal shotgun wounds is mainly dependent on clinical examination and clinical judgment, while requires advanced surgical skills. PMID:18625076

Controlled viable release of selectively captured label-free cells in microchannels.

PubMed

Gurkan, Umut Atakan; Anand, Tarini; Tas, Huseyin; Elkan, David; Akay, Altug; Keles, Hasan Onur; Demirci, Utkan

2011-12-07

Selective capture of cells from bodily fluids in microchannels has broadly transformed medicine enabling circulating tumor cell isolation, rapid CD4(+) cell counting for HIV monitoring, and diagnosis of infectious diseases. Although cell capture methods have been demonstrated in microfluidic systems, the release of captured cells remains a significant challenge. Viable retrieval of captured label-free cells in microchannels will enable a new era in biological sciences by allowing cultivation and post-processing. The significant challenge in release comes from the fact that the cells adhere strongly to the microchannel surface, especially when immuno-based immobilization methods are used. Even though fluid shear and enzymes have been used to detach captured cells in microchannels, these methods are known to harm cells and affect cellular characteristics. This paper describes a new technology to release the selectively captured label-free cells in microchannels without the use of fluid shear or enzymes. We have successfully released the captured CD4(+) cells (3.6% of the mononuclear blood cells) from blood in microfluidic channels with high specificity (89% ± 8%), viability (94% ± 4%), and release efficiency (59% ± 4%). We have further validated our system by specifically capturing and controllably releasing the CD34(+) stem cells from whole blood, which were quantified to be 19 cells per million blood cells in the blood samples used in this study. Our results also indicated that both CD4(+) and CD34(+) cells released from the microchannels were healthy and amenable for in vitro culture. Manual flow based microfluidic method utilizes inexpensive, easy to fabricate microchannels allowing selective label-free cell capture and release in less than 10 minutes, which can also be used at the point-of-care. The presented technology can be used to isolate and purify a broad spectrum of cells from mixed populations offering widespread applications in applied biological

The speciation of the proteome

PubMed Central

Jungblut, Peter R; Holzhütter, Hermann G; Apweiler, Rolf; Schlüter, Hartmut

2008-01-01

Introduction In proteomics a paradox situation developed in the last years. At one side it is basic knowledge that proteins are post-translationally modified and occur in different isoforms. At the other side the protein expression concept disclaims post-translational modifications by connecting protein names directly with function. Discussion Optimal proteome coverage is today reached by bottom-up liquid chromatography/mass spectrometry. But quantification at the peptide level in shotgun or bottom-up approaches by liquid chromatography and mass spectrometry is completely ignoring that a special peptide may exist in an unmodified form and in several-fold modified forms. The acceptance of the protein species concept is a basic prerequisite for meaningful quantitative analyses in functional proteomics. In discovery approaches only top-down analyses, separating the protein species before digestion, identification and quantification by two-dimensional gel electrophoresis or protein liquid chromatography, allow the correlation between changes of a biological situation and function. Conclusion To obtain biological relevant information kinetics and systems biology have to be performed at the protein species level, which is the major challenge in proteomics today. PMID:18638390

Progress of new label-free techniques for biosensors: a review.

PubMed

Sang, Shengbo; Wang, Yajun; Feng, Qiliang; Wei, Ye; Ji, Jianlong; Zhang, Wendong

2016-01-01

The detection techniques used in biosensors can be broadly classified into label-based and label-free. Label-based detection relies on the specific properties of labels for detecting a particular target. In contrast, label-free detection is suitable for the target molecules that are not labeled or the screening of analytes which are not easy to tag. Also, more types of label-free biosensors have emerged with developments in biotechnology. The latest developed techniques in label-free biosensors, such as field-effect transistors-based biosensors including carbon nanotube field-effect transistor biosensors, graphene field-effect transistor biosensors and silicon nanowire field-effect transistor biosensors, magnetoelastic biosensors, optical-based biosensors, surface stress-based biosensors and other type of biosensors based on the nanotechnology are discussed. The sensing principles, configurations, sensing performance, applications, advantages and restriction of different label-free based biosensors are considered and discussed in this review. Most concepts included in this survey could certainly be applied to the development of this kind of biosensor in the future.

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

Large-scale label-free comparative proteomics analysis of polo-like kinase 1 inhibition via the small-molecule inhibitor BI 6727 (Volasertib) in BRAF(V600E) mutant melanoma cells.

PubMed

Cholewa, Brian D; Pellitteri-Hahn, Molly C; Scarlett, Cameron O; Ahmad, Nihal

2014-11-07

Polo-like kinase 1 (Plk1) is a serine/threonine kinase that plays a key role during the cell cycle by regulating mitotic entry, progression, and exit. Plk1 is overexpressed in a variety of human cancers and is essential to sustained oncogenic proliferation, thus making Plk1 an attractive therapeutic target. However, the clinical efficacy of Plk1 inhibition has not emulated the preclinical success, stressing an urgent need for a better understanding of Plk1 signaling. This study addresses that need by utilizing a quantitative proteomics strategy to compare the proteome of BRAF(V600E) mutant melanoma cells following treatment with the Plk1-specific inhibitor BI 6727. Employing label-free nano-LC-MS/MS technology on a Q-exactive followed by SIEVE processing, we identified more than 20 proteins of interest, many of which have not been previously associated with Plk1 signaling. Here we report the down-regulation of multiple metabolic proteins with an associated decrease in cellular metabolism, as assessed by lactate and NAD levels. Furthermore, we have also identified the down-regulation of multiple proteasomal subunits, resulting in a significant decrease in 20S proteasome activity. Additionally, we have identified a novel association between Plk1 and p53 through heterogeneous ribonucleoprotein C1/C2 (hnRNPC), thus providing valuable insight into Plk1's role in cancer cell survival.

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.

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide

PubMed Central

Lima, D. C.; Duarte, F. T.; Medeiros, V. K. S.; Carvalho, P. C.; Nogueira, F. C. S.; Araujo, G. D. T.; Domont, G. B.; Batistuzzo de Medeiros, S. R.

2016-01-01

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism. PMID:27321545

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide.

PubMed

Lima, D C; Duarte, F T; Medeiros, V K S; Carvalho, P C; Nogueira, F C S; Araujo, G D T; Domont, G B; Batistuzzo de Medeiros, S R

2016-06-20

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism.

Evaluation of a High Intensity Focused Ultrasound-Immobilized Trypsin Digestion and 18O-Labeling Method for Quantitative Proteomics

PubMed Central

López-Ferrer, Daniel; Hixson, Kim K.; Smallwood, Heather; Squier, Thomas C.; Petritis, Konstantinos; Smith, Richard D.

2009-01-01

A new method that uses immobilized trypsin concomitant with ultrasonic irradiation results in ultra-rapid digestion and thorough 18O labeling for quantitative protein comparisons. The reproducible and highly efficient method provided effective digestions in <1 min with a minimized amount of enzyme required compared to traditional methods. This method was demonstrated for digestion of both simple and complex protein mixtures, including bovine serum albumin, a global proteome extract from the bacteria Shewanella oneidensis, and mouse plasma, as well as 18O labeling of such complex protein mixtures, which validated the application of this method for differential proteomic measurements. This approach is simple, reproducible, cost effective, rapid, and thus well-suited for automation. PMID:19555078

An accurate proteomic quantification method: fluorescence labeling absolute quantification (FLAQ) using multidimensional liquid chromatography and tandem mass spectrometry.

PubMed

Liu, Junyan; Liu, Yang; Gao, Mingxia; Zhang, Xiangmin

2012-08-01

A facile proteomic quantification method, fluorescent labeling absolute quantification (FLAQ), was developed. Instead of using MS for quantification, the FLAQ method is a chromatography-based quantification in combination with MS for identification. Multidimensional liquid chromatography (MDLC) with laser-induced fluorescence (LIF) detection with high accuracy and tandem MS system were employed for FLAQ. Several requirements should be met for fluorescent labeling in MS identification: Labeling completeness, minimum side-reactions, simple MS spectra, and no extra tandem MS fragmentations for structure elucidations. A fluorescence dye, 5-iodoacetamidofluorescein, was finally chosen to label proteins on all cysteine residues. The fluorescent dye was compatible with the process of the trypsin digestion and MALDI MS identification. Quantitative labeling was achieved with optimization of reacting conditions. A synthesized peptide and model proteins, BSA (35 cysteines), OVA (five cysteines), were used for verifying the completeness of labeling. Proteins were separated through MDLC and quantified based on fluorescent intensities, followed by MS identification. High accuracy (RSD% < 1.58) and wide linearity of quantification (1-10(5) ) were achieved by LIF detection. The limit of quantitation for the model protein was as low as 0.34 amol. Parts of proteins in human liver proteome were quantified and demonstrated using FLAQ. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cell-free protein synthesis: applications in proteomics and biotechnology.

PubMed

He, Mingyue

2008-01-01

Protein production is one of the key steps in biotechnology and functional proteomics. Expression of proteins in heterologous hosts (such as in E. coli) is generally lengthy and costly. Cell-free protein synthesis is thus emerging as an attractive alternative. In addition to the simplicity and speed for protein production, cell-free expression allows generation of functional proteins that are difficult to produce by in vivo systems. Recent exploitation of cell-free systems enables novel development of technologies for rapid discovery of proteins with desirable properties from very large libraries. This article reviews the recent development in cell-free systems and their application in the large scale protein analysis.

Proteomics screen to reveal molecular changes mediated by C722G missense mutation in CHRM2 gene.

PubMed

Hou, Dongyan; Chen, Ying; Liu, Jiamei; Xu, Lin; Zhang, Zhiyong; Zhang, Juan; Wang, Hua; Wang, Xin; Chen, Jin; Zhao, Rongrui; Hu, Aihua; Hakonarson, Hakon; Zhang, Lin; Shen, Yan

2013-08-26

Previously, we reported a missense mutation (C722G) in the M2-muscarinic acetylcholine receptor (CHRM2) gene associated with familial dilated cardiomyopathy. However, the exact molecular mechanisms by the related protein changes of CHRM2-C722G mutation induced are still unclear. CHRM2 and CHRM2-C722G lentiviral vector was infected to CHO cells. Proteomic analysis by label-free shotgun strategy and the STRING 9.0 software were performed. A total of 102 proteins with at least 2-fold change in the CHRM2-C722G group were identified, 42 proteins were up-regulated, whereas 57 were down-regulated. These altered proteins belong to three broad functional categories: (i) metabolic (e.g. Cytosolic acyl coenzyme A thioester hydrolase, Malate dehydrogenase); (ii) cytoskeletal (e.g. Actin-related protein, Myosin light polypeptide 6 and Alpha-actinin-1) and (iii) stress response (e.g. heat shock protein 70, Ras-related protein Rab-10). Interestingly, the marked differences in the expression of selected eight proteins (change >4.0-fold), were connected with many proteins related to apoptosis and immune/inflammatory response such as: FOS, BAX, MYC, TP53 and IL6. This novel study demonstrated for the first time a full-scale screening of the proteomics research by CHRM2-C722G mutation and profiled 102 changed proteins, of which, eight might be critical in cardiac dysfunction for future mapping. It was a full-scale screening of the proteomics research by CHRM2-C722G mutation. These proteins might serve as valuable biomarkers that could predict the presence of a precursor field. These proteins might serve to further explore the pathophysiological mechanisms in familial DCM patients with C176W mutation. Copyright © 2013 Elsevier B.V. All rights reserved.

Performance Evaluation of the Q Exactive HF-X for Shotgun Proteomics.

PubMed

Kelstrup, Christian D; Bekker-Jensen, Dorte B; Arrey, Tabiwang N; Hogrebe, Alexander; Harder, Alexander; Olsen, Jesper V

2018-01-05

Progress in proteomics is mainly driven by advances in mass spectrometric (MS) technologies. Here we benchmarked the performance of the latest MS instrument in the benchtop Orbitrap series, the Q Exactive HF-X, against its predecessor for proteomics applications. A new peak-picking algorithm, a brighter ion source, and optimized ion transfers enable productive MS/MS acquisition above 40 Hz at 7500 resolution. The hardware and software improvements collectively resulted in improved peptide and protein identifications across all comparable conditions, with an increase of up to 50 percent at short LC-MS gradients, yielding identification rates of more than 1000 unique peptides per minute. Alternatively, the Q Exactive HF-X is capable of achieving the same proteome coverage as its predecessor in approximately half the gradient time or at 10-fold lower sample loads. The Q Exactive HF-X also enables rapid phosphoproteomics with routine analysis of more than 5000 phosphopeptides with short single-shot 15 min LC-MS/MS measurements, or 16 700 phosphopeptides quantified across ten conditions in six gradient hours using TMT10-plex and offline peptide fractionation. Finally, exciting perspectives for data-independent acquisition are highlighted with reproducible identification of 55 000 unique peptides covering 5900 proteins in half an hour of MS analysis.

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

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

PubMed Central

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L.; Dianes, José A.; del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W.; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-01-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra. PMID:27493588

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.

PubMed

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L; Dianes, José A; Del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-08-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

High-coverage quantitative proteomics using amine-specific isotopic labeling.

PubMed

Melanson, Jeremy E; Avery, Steven L; Pinto, Devanand M

2006-08-01

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.

[Methods of quantitative proteomics].

PubMed

Kopylov, A T; Zgoda, V G

2007-01-01

In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.

Performance limitations of label-free sensors in molecular diagnosis using complex samples

NASA Astrophysics Data System (ADS)

Varma, Manoj

2016-03-01

Label-free biosensors promised a paradigm involving direct detection of biomarkers from complex samples such as serum without requiring multistep sample processing typical of labelled methods such as ELISA or immunofluorescence assays. Label-free sensors have witnessed decades of development with a veritable zoo of techniques available today exploiting a multitude of physical effects. It is appropriate now to critically assess whether label-free technologies have succeeded in delivering their promise with respect to diagnostic applications, particularly, ambitious goals such as early cancer detection using serum biomarkers, which require low limits of detection (LoD). Comparison of nearly 120 limits of detection (LoD) values reported by labelled and label-free sensing approaches over a wide range of detection techniques and target molecules in serum revealed that labeled techniques achieve 2-3 orders of magnitude better LoDs. Data from experiments where labelled and label-free assays were performed simultaneously using the same assay parameters also confirm that the LoD achieved by labelled techniques is 2 to 3 orders of magnitude better than that by label-free techniques. Furthermore, label-free techniques required significant signal amplification, for e.g. using nanoparticle conjugated secondary antibodies, to achieve LoDs comparable to labelled methods substantially deviating from the original "direct detection" paradigm. This finding has important implications on the practical limits of applying label-free detection methods for molecular diagnosis.

Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing*

PubMed Central

Welle, Kevin A.; Zhang, Tian; Hryhorenko, Jennifer R.; Shen, Shichen; Qu, Jun; Ghaemmaghami, Sina

2016-01-01

Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data. PMID:27765818

Ion mobility-enhanced MS(E)-based label-free analysis reveals effects of low-dose radiation post contextual fear conditioning training on the mouse hippocampal proteome.

PubMed

Huang, Lin; Wickramasekara, Samanthi I; Akinyeke, Tunde; Stewart, Blair S; Jiang, Yuan; Raber, Jacob; Maier, Claudia S

2016-05-17

Recent advances in the field of biodosimetry have shown that the response of biological systems to ionizing radiation is complex and depends on the type and dose of radiation, the tissue(s) exposed, and the time lapsed after exposure. The biological effects of low dose radiation on learning and memory are not well understood. An ion mobility-enhanced data-independent acquisition (MS(E)) approach in conjunction with the ISOQuant software tool was utilized for label-free quantification of hippocampal proteins with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-rays, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. Global proteome analysis revealed deregulation of 73 proteins (out of 399 proteins). Deregulated proteins indicated adverse effects of irradiation on myelination and perturbation of energy metabolism pathways involving a shift from the TCA cycle to glutamate oxidation. Our findings also indicate that proteins associated with synaptic activity, including vesicle recycling and neurotransmission, were altered in the irradiated mice. The elevated LTP and decreased LTD suggest improved synaptic transmission and enhanced efficiency of neurotransmitter release which would be consistent with the observed comparable contextual fear memory performance of the mice following post-training whole body or sham-irradiation. This study is significant because the biological consequences of low dose radiation on learning and memory are complex and not yet well understood. We conducted a IMS-enhanced MS(E)-based label-free quantitative proteomic analysis of hippocampal tissue with the goal of determining protein alteration associated with low-dose whole body ionizing radiation (X-ray, 1Gy) of 5.5-month-old male C57BL/6J mice post contextual fear conditioning training. The IMS-enhanced MS(E) approach in conjunction with ISOQuant software was robust and accurate with low median CV values of

Label-free functional nucleic acid sensors for detecting target agents

DOEpatents

Lu, Yi; Xiang, Yu

2015-01-13

A general methodology to design label-free fluorescent functional nucleic acid sensors using a vacant site approach and an abasic site approach is described. In one example, a method for designing label-free fluorescent functional nucleic acid sensors (e.g., those that include a DNAzyme, aptamer or aptazyme) that have a tunable dynamic range through the introduction of an abasic site (e.g., dSpacer) or a vacant site into the functional nucleic acids. Also provided is a general method for designing label-free fluorescent aptamer sensors based on the regulation of malachite green (MG) fluorescence. A general method for designing label-free fluorescent catalytic and molecular beacons (CAMBs) is also provided. The methods demonstrated here can be used to design many other label-free fluorescent sensors to detect a wide range of analytes. Sensors and methods of using the disclosed sensors are also provided.

The genome of flax (Linum usitatissimum) assembled de novo from short shotgun sequence reads.

PubMed

Wang, Zhiwen; Hobson, Neil; Galindo, Leonardo; Zhu, Shilin; Shi, Daihu; McDill, Joshua; Yang, Linfeng; Hawkins, Simon; Neutelings, Godfrey; Datla, Raju; Lambert, Georgina; Galbraith, David W; Grassa, Christopher J; Geraldes, Armando; Cronk, Quentin C; Cullis, Christopher; Dash, Prasanta K; Kumar, Polumetla A; Cloutier, Sylvie; Sharpe, Andrew G; Wong, Gane K-S; Wang, Jun; Deyholos, Michael K

2012-11-01

Flax (Linum usitatissimum) is an ancient crop that is widely cultivated as a source of fiber, oil and medicinally relevant compounds. To accelerate crop improvement, we performed whole-genome shotgun sequencing of the nuclear genome of flax. Seven paired-end libraries ranging in size from 300 bp to 10 kb were sequenced using an Illumina genome analyzer. A de novo assembly, comprised exclusively of deep-coverage (approximately 94× raw, approximately 69× filtered) short-sequence reads (44-100 bp), produced a set of scaffolds with N(50) =694 kb, including contigs with N(50)=20.1 kb. The contig assembly contained 302 Mb of non-redundant sequence representing an estimated 81% genome coverage. Up to 96% of published flax ESTs aligned to the whole-genome shotgun scaffolds. However, comparisons with independently sequenced BACs and fosmids showed some mis-assembly of regions at the genome scale. A total of 43384 protein-coding genes were predicted in the whole-genome shotgun assembly, and up to 93% of published flax ESTs, and 86% of A. thaliana genes aligned to these predicted genes, indicating excellent coverage and accuracy at the gene level. Analysis of the synonymous substitution rates (K(s) ) observed within duplicate gene pairs was consistent with a recent (5-9 MYA) whole-genome duplication in flax. Within the predicted proteome, we observed enrichment of many conserved domains (Pfam-A) that may contribute to the unique properties of this crop, including agglutinin proteins. Together these results show that de novo assembly, based solely on whole-genome shotgun short-sequence reads, is an efficient means of obtaining nearly complete genome sequence information for some plant species. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.

Gluten-Free Labeling of Foods

MedlinePlus

... Vaccines, Blood & Biologics Animal & Veterinary Cosmetics Tobacco Products Food Home Food Guidance & Regulation Guidance Documents & Regulatory Information by Topic Allergens Gluten-Free Labeling of Foods Share Tweet Linkedin Pin it More sharing options ...

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.

Subcellular proteome profiles of different latex fractions revealed washed solutions from rubber particles contain crucial enzymes for natural rubber biosynthesis.

PubMed

Wang, Dan; Sun, Yong; Chang, Lili; Tong, Zheng; Xie, Quanliang; Jin, Xiang; Zhu, Liping; He, Peng; Li, Hongbin; Wang, Xuchu

2018-06-30

Rubber particle (RP) is a specific organelle for natural rubber biosynthesis (NRB) and storage in rubber tree Hevea brasiliensis. NRB is processed by RP membrane-localized proteins, which were traditionally purified by repeated washing. However, we noticed many proteins in the discarded washing solutions (WS) from RP. Here, we compared the proteome profiles of WS, C-serum (CS) and RP by 2-DE, and identified 233 abundant proteins from WS by mass spectrometry. Many spots on 2-DE gels were identified as different protein species. We further performed shotgun analysis of CS, WS and RP and identified 1837, 1799 and 1020 unique proteins, respectively. Together with 2-DE, we finally identified 1825 proteins from WS, 246 were WS-specific. These WS-specific proteins were annotated in Gene Ontology, indicating most abundant pathways are organic substance metabolic process, protein degradation, primary metabolic process, and energy metabolism. Protein-protein interaction analysis revealed these WS-specific proteins are mainly involved in ribosomal metabolism, proteasome system, vacuolar protein sorting and endocytosis. Label free and Western blotting revealed many WS-specific proteins and protein complexes are crucial for NRB initiation. These findings not only deepen our understanding of WS proteome, but also provide new evidences on the roles of RP membrane proteins in NRB. Natural rubber is stored in rubber particle from the rubber tree. Rubber particles were traditionally purified by repeated washing, but many proteins were identified from the washing solutions (WS). We obtained the first visualization proteome profiles with 1825 proteins from WS, including 246 WS-specific ones. These WS proteins contain almost all enzymes for polyisoprene initiation and may play important roles in rubber biosynthesis. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteogenomics Dashboard for the Human Proteome Project.

PubMed

Tabas-Madrid, Daniel; Alves-Cruzeiro, Joao; Segura, Victor; Guruceaga, Elizabeth; Vialas, Vital; Prieto, Gorka; García, Carlos; Corrales, Fernando J; Albar, Juan Pablo; Pascual-Montano, Alberto

2015-09-04

dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.

Shotgun Pyrosequencing Metagenomic Analyses of Dusts from Swine Confinement and Grain Facilities

PubMed Central

Boissy, Robert J.; Romberger, Debra J.; Roughead, William A.; Weissenburger-Moser, Lisa; Poole, Jill A.; LeVan, Tricia D.

2014-01-01

Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70%) at the phylum level, Clostridia (44%) at the Class level, and Clostridiales at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses

Shotgun pyrosequencing metagenomic analyses of dusts from swine confinement and grain facilities.

PubMed

Boissy, Robert J; Romberger, Debra J; Roughead, William A; Weissenburger-Moser, Lisa; Poole, Jill A; LeVan, Tricia D

2014-01-01

Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70%) at the phylum level, Clostridia (44%) at the Class level, and Clostridiales at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses

TransOmic analysis of forebrain sections in Sp2 conditional knockout embryonic mice using IR-MALDESI imaging of lipids and LC-MS/MS label-free proteomics

PubMed Central

Loziuk, Philip; Meier, Florian; Johnson, Caroline

2016-01-01

Quantitative methods for detection of biological molecules are needed more than ever before in the emerging age of “omics” and “big data.” Here, we provide an integrated approach for systematic analysis of the “lipidome” in tissue. To test our approach in a biological context, we utilized brain tissue selectively deficient for the transcription factor Specificity Protein 2 (Sp2). Conditional deletion of Sp2 in the mouse cerebral cortex results in developmental deficiencies including disruption of lipid metabolism. Silver (Ag) cationization was implemented for infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) to enhance the ion abundances for olefinic lipids, as these have been linked to regulation by Sp2. Combining Ag-doped and conventional IR-MALDESI imaging, this approach was extended to IR-MALDESI imaging of embryonic mouse brains. Further, our imaging technique was combined with bottom-up shotgun proteomic LC-MS/MS analysis and western blot for comparing Sp2 conditional knockout (Sp2-cKO) and wild-type (WT) cortices of tissue sections. This provided an integrated omics dataset which revealed many specific changes to fundamental cellular processes and biosynthetic pathways. In particular, step-specific altered abundances of nucleotides, lipids, and associated proteins were observed in the cerebral cortices of Sp2-cKO embryos. PMID:26942738

Proteomic and Lipidomic Analysis of Nanoparticle Corona upon Contact with Lung Surfactant Reveals Differences in Protein, but Not Lipid Composition.

PubMed

Raesch, Simon Sebastian; Tenzer, Stefan; Storck, Wiebke; Rurainski, Alexander; Selzer, Dominik; Ruge, Christian Arnold; Perez-Gil, Jesus; Schaefer, Ulrich Friedrich; Lehr, Claus-Michael

2015-12-22

Pulmonary surfactant (PS) constitutes the first line of host defense in the deep lung. Because of its high content of phospholipids and surfactant specific proteins, the interaction of inhaled nanoparticles (NPs) with the pulmonary surfactant layer is likely to form a corona that is different to the one formed in plasma. Here we present a detailed lipidomic and proteomic analysis of NP corona formation using native porcine surfactant as a model. We analyzed the adsorbed biomolecules in the corona of three NP with different surface properties (PEG-, PLGA-, and Lipid-NP) after incubation with native porcine surfactant. Using label-free shotgun analysis for protein and LC-MS for lipid analysis, we quantitatively determined the corona composition. Our results show a conserved lipid composition in the coronas of all investigated NPs regardless of their surface properties, with only hydrophilic PEG-NPs adsorbing fewer lipids in total. In contrast, the analyzed NP displayed a marked difference in the protein corona, consisting of up to 417 different proteins. Among the proteins showing significant differences between the NP coronas, there was a striking prevalence of molecules with a notoriously high lipid and surface binding, such as, e.g., SP-A, SP-D, DMBT1. Our data indicate that the selective adsorption of proteins mediates the relatively similar lipid pattern in the coronas of different NPs. On the basis of our lipidomic and proteomic analysis, we provide a detailed set of quantitative data on the composition of the surfactant corona formed upon NP inhalation, which is unique and markedly different to the plasma corona.

Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins.

PubMed

Boja, Emily S; Rodriguez, Henry

2012-04-01

Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of Data Acquisition Strategies on Quadrupole Ion Trap Instrumentation for Shotgun Proteomics

PubMed Central

Canterbury, Jesse D.; Merrihew, Gennifer E.; Goodlett, David R.; MacCoss, Michael J.; Shaffer, Scott A.

2015-01-01

A common strategy in mass spectrometry analyses of complex protein mixtures is to digest the proteins to peptides, separate the peptides by microcapillary liquid chromatography and collect tandem mass spectra (MS/MS) on the eluting, complex peptide mixtures, a process commonly termed “shotgun proteomics”. For years, the most common way of data collection was via data-dependent acquisition (DDA), a process driven by an automated instrument control routine that directs MS/MS acquisition from the highest abundant signals to the lowest, a process often leaving lower abundant signals unanalyzed and therefore unidentified in the experiment. Advances in both instrumentation duty cycle and sensitivity allow DDA to probe to lower peptide abundance and therefore enable mapping proteomes to a more significant depth. An alternative to acquiring data by DDA is by data-independent acquisition (DIA), in which a specified range in m/z is fragmented without regard to prioritization of a precursor ion or its relative abundance in the mass spectrum. As a consequence, DIA acquisition potentially offers more comprehensive analysis of peptides than DDA and in principle can yield tandem mass spectra of all ionized molecules following their conversion to the gas-phase. In this work, we evaluate both DDA and DIA on three different linear ion trap instruments: an LTQ, an LTQ modified in-house with an electrodynamic ion funnel, and an LTQ-Velos. These instruments were chosen as they are representative of both older (LTQ) and newer (LTQ-Velos) ion trap designs i.e., linear ion trap and dual ion traps, respectively, and allow direct comparison of peptide identification using both DDA and DIA analysis. Further, as the LTQ-Velos has an improved “S-lens” ion guide in the high-pressure region to improve ion flux, we found it logical to determine if the former LTQ model could be leveraged by improving sensitivity by modifying with an electrodynamic ion guide of significantly different

Label-free probing of genes by time-domain terahertz sensing.

PubMed

Haring Bolivar, P; Brucherseifer, M; Nagel, M; Kurz, H; Bosserhoff, A; Büttner, R

2002-11-07

A label-free sensing approach for the label-free characterization of genetic material with terahertz (THz) electromagnetic waves is presented. Time-resolved THz analysis of polynucleotides demonstrates a strong dependence of the complex refractive index of DNA molecules in the THz frequency range on their hybridization state. By monitoring THz signals one can thus infer the binding state (hybridized or denatured) of oligo- and polynucleotides, enabling the label-free determination the genetic composition of unknown DNA sequences. A broadband experimental proof-of-principle in a freespace analytic configuration, as well as a higher-sensitivity approach using integrated THz sensors reaching femtomol detection levels and demonstrating the capability to detect single-base mutations, are presented. The potential application for next generation high-throughput label-free genetic analytic systems is discussed.

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

Proteomics and Pathway Analyses of the Milk Fat Globule in Sheep Naturally Infected by Mycoplasma agalactiae Provide Indications of the In Vivo Response of the Mammary Epithelium to Bacterial Infection ▿ ‡

PubMed Central

Addis, Maria Filippa; Pisanu, Salvatore; Ghisaura, Stefania; Pagnozzi, Daniela; Marogna, Gavino; Tanca, Alessandro; Biosa, Grazia; Cacciotto, Carla; Alberti, Alberto; Pittau, Marco; Roggio, Tonina; Uzzau, Sergio

2011-01-01

Milk fat globules (MFGs) are vesicles released in milk as fat droplets surrounded by the endoplasmic reticulum and apical cell membranes. During formation and apocrine secretion by lactocytes, various amounts of cytoplasmic crescents remain trapped within the released vesicle, making MFGs a natural sampling mechanism of the lactating cell contents. With the aim of investigating the events occurring in the mammary epithelium during bacterial infection, the MFG proteome was characterized by two-dimensional difference gel electrophoresis (2-D DIGE), SDS-PAGE followed by shotgun liquid chromatography-tandem mass spectrometry (GeLC-MS/MS), label-free quantification by the normalized spectral abundance factor (NSAF) approach, Western blotting, and pathway analysis, using sheep naturally infected by Mycoplasma agalactiae. A number of protein classes were found to increase in MFGs upon infection, including proteins involved in inflammation and host defense, cortical cytoskeleton proteins, heat shock proteins, and proteins related to oxidative stress. Conversely, a strikingly lower abundance was observed for proteins devoted to MFG metabolism and secretion. To our knowledge, this is the first report describing proteomic changes occurring in MFGs during sheep infectious mastitis. The results presented here offer new insights into the in vivo response of mammary epithelial cells to bacterial infection and open the way to the discovery of protein biomarkers for monitoring clinical and subclinical mastitis. PMID:21690237

A comprehensive proteomics study on platelet concentrates: Platelet proteome, storage time and Mirasol pathogen reduction technology.

PubMed

Salunkhe, Vishal; De Cuyper, Iris M; Papadopoulos, Petros; van der Meer, Pieter F; Daal, Brunette B; Villa-Fajardo, María; de Korte, Dirk; van den Berg, Timo K; Gutiérrez, Laura

2018-03-19

Platelet concentrates (PCs) represent a blood transfusion product with a major concern for safety as their storage temperature (20-24°C) allows bacterial growth, and their maximum storage time period (less than a week) precludes complete microbiological testing. Pathogen inactivation technologies (PITs) provide an additional layer of safety to the blood transfusion products from known and unknown pathogens such as bacteria, viruses, and parasites. In this context, PITs, such as Mirasol Pathogen Reduction Technology (PRT), have been developed and are implemented in many countries. However, several studies have shown in vitro that Mirasol PRT induces a certain level of platelet shape change, hyperactivation, basal degranulation, and increased oxidative damage during storage. It has been suggested that Mirasol PRT might accelerate what has been described as the platelet storage lesion (PSL), but supportive molecular signatures have not been obtained. We aimed at dissecting the influence of both variables, that is, Mirasol PRT and storage time, at the proteome level. We present comprehensive proteomics data analysis of Control PCs and PCs treated with Mirasol PRT at storage days 1, 2, 6, and 8. Our workflow was set to perform proteomics analysis using a gel-free and label-free quantification (LFQ) approach. Semi-quantification was based on LFQ signal intensities of identified proteins using MaxQuant/Perseus software platform. Data are available via ProteomeXchange with identifier PXD008119. We identified marginal differences between Mirasol PRT and Control PCs during storage. However, those significant changes at the proteome level were specifically related to the functional aspects previously described to affect platelets upon Mirasol PRT. In addition, the effect of Mirasol PRT on the platelet proteome appeared not to be exclusively due to an accelerated or enhanced PSL. In summary, semi-quantitative proteomics allows to discern between proteome changes due to

Using label-free screening technology to improve efficiency in drug discovery.

PubMed

Halai, Reena; Cooper, Matthew A

2012-02-01

Screening assays have traditionally utilized reporter labels to quantify biological responses relevant to the disease state of interest. However, there are limitations associated with the use of labels that may be overcome with temporal measurements possible with label-free. This review comprises general and system-specific information from literature searches using PubMed, published books and the authors' personal experience. This review highlights the label-free approaches in the context of various applications. The authors also note technical issues relevant to the development of label-free assays and their application to HTS. The limitations associated with the use of transfected cell lines and the use of label-based assays are gradually being realized. As such, greater emphasis is being placed on label-free biophysical techniques using native cell lines. The introduction of 96- and 384-well plate label-free systems is helping to broker a wider acceptance of these approaches in high-throughput screening. However, potential users of the technologies remain skeptical, primarily because the physical basis of the signals generated, and their contextual relevance to cell biology and signal transduction, has not been fully elucidated. Until this is done, these new technology platforms are more likely to complement, rather than replace, traditional screening platforms.

The State of the Human Proteome in 2013 as viewed through PeptideAtlas: Comparing the Kidney, Urine, and Plasma Proteomes for the Biology and Disease-driven Human Proteome Project

PubMed Central

Farrah, Terry; Deutsch, Eric W.; Omenn, Gilbert S.; Sun, Zhi; Watts, Julian D.; Yamamoto, Tadashi; Shteynberg, David; Harris, Micheleen M.; Moritz, Robert L.

2014-01-01

The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics datasets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively—for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ~14,000 Swiss-Prot entries, an increase over 2012 of ~7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue. PMID:24261998

Common Features Between the Proteomes of Floral and Extrafloral Nectar From the Castor Plant (Ricinus Communis) and the Proteomes of Exudates From Carnivorous Plants

PubMed Central

Nogueira, Fábio C. S.; Farias, Andreza R. B.; Teixeira, Fabiano M.; Domont, Gilberto B.; Campos, Francisco A. P.

2018-01-01

Label-free quantitative proteome analysis of extrafloral (EFN) and floral nectar (FN) from castor (Ricinus communis) plants resulted in the identification of 72 and 37 proteins, respectively. Thirty proteins were differentially accumulated between EFN and FN, and 24 of these were more abundant in the EFN. In addition to proteins involved in maintaining the nectar pathogen free such as chitinases and glucan 1,3-beta-glucosidase, both proteomes share an array of peptidases, lipases, carbohydrases, and nucleases. A total of 39 of the identified proteins, comprising different classes of hydrolases, were found to have biochemical matching partners in the exudates of at least five genera of carnivorous plants, indicating the EFN and FN possess a potential to digest biological material from microbial, animal or plant origin equivalent to the exudates of carnivorous plants. PMID:29755492

Common Features Between the Proteomes of Floral and Extrafloral Nectar From the Castor Plant (Ricinus Communis) and the Proteomes of Exudates From Carnivorous Plants.

PubMed

Nogueira, Fábio C S; Farias, Andreza R B; Teixeira, Fabiano M; Domont, Gilberto B; Campos, Francisco A P

2018-01-01

Label-free quantitative proteome analysis of extrafloral (EFN) and floral nectar (FN) from castor ( Ricinus communis ) plants resulted in the identification of 72 and 37 proteins, respectively. Thirty proteins were differentially accumulated between EFN and FN, and 24 of these were more abundant in the EFN. In addition to proteins involved in maintaining the nectar pathogen free such as chitinases and glucan 1,3-beta-glucosidase, both proteomes share an array of peptidases, lipases, carbohydrases, and nucleases. A total of 39 of the identified proteins, comprising different classes of hydrolases, were found to have biochemical matching partners in the exudates of at least five genera of carnivorous plants, indicating the EFN and FN possess a potential to digest biological material from microbial, animal or plant origin equivalent to the exudates of carnivorous plants.

A label-free internal standard method for the differential analysis of bioactive lupin proteins using nano HPLC-Chip coupled with Ion Trap mass spectrometry.

PubMed

Brambilla, Francesca; Resta, Donatella; Isak, Ilena; Zanotti, Marco; Arnoldi, Anna

2009-01-01

Quantitative proteomics based on MS is useful for pointing out the differences in some food proteomes relevant to human nutrition. Stable isotope label-free (SIF) techniques are suitable for comparing an unlimited number of samples by the use of relatively simple experimental workflows. We have developed an internal standard label-free method based on the intensities of peptide precursor ions from MS/MS spectra, collected in data dependent runs, for the simultaneous qualitative characterization and relative quantification of storage proteins of Lupinus albus seeds in protein extracts of four lupin cultivars (cv Adam, Arés, Lucky, Multitalia). The use of an innovative microfluidic system, the HPLC-Chip, coupled with a classical IT mass spectrometer, has allowed a complete qualitative characterization of all proteins. In particular, the homology search mode has permitted to identify single amino acid substitutions in the sequences of vicilins (beta-conglutin precursor and vicilin-like protein). The MS/MS sequencing of substituted peptides confirms the high heterogeneity of vicilins according to the peculiar characteristics of the vicilin-encoding gene family. Two suitable bioinformatics parameters were optimized for the differential analyses of the main bioactive proteins: the "normalized protein average of common reproducible peptides" (N-ACRP) for gamma-conglutin, which is a homogeneous protein, and the "normalized protein mean peptide spectral intensity" (N-MEAN) for the highly heterogenous class of the vicilins.

Defining the Adipose Tissue Proteome of Dairy Cows to Reveal Biomarkers Related to Peripartum Insulin Resistance and Metabolic Status.

PubMed

Zachut, Maya

2015-07-02

Adipose tissue is a central regulator of metabolism in dairy cows; however, little is known about the association between various proteins in adipose tissue and the metabolic status of peripartum cows. Therefore, the objectives were to (1) examine total protein expression in adipose tissue of dairy cows and (2) identify biomarkers in adipose that are linked to insulin resistance and to cows' metabolic status. Adipose tissue biopsies were obtained from eight multiparous cows at -17 and +4 days relative to parturition. Proteins were analyzed by intensity-based, label-free, quantitative shotgun proteomics (nanoLC-MS/MS). Cows were divided into groups with insulin-resistant (IR) and insulin-sensitive (IS) adipose according to protein kinase B phosphorylation following insulin stimulation. Cows with IR adipose lost more body weight postpartum compared with IS cows. Differential expression of 143 out of 586 proteins was detected in prepartum versus postpartum adipose. Comparing IR to IS adipose revealed differential expression of 18.9% of the proteins; those related to lipolysis (hormone-sensitive lipase, perilipin, monoglycerol lipase) were increased in IR adipose. In conclusion, we found novel biomarkers related to IR in adipose and to metabolic status that could be used to characterize high-yielding dairy cows that are better adapted to peripartum metabolic stress.

Colonization State Influences the Hemocyte Proteome in a Beneficial Squid–Vibrio Symbiosis*

PubMed Central

Schleicher, Tyler R.; VerBerkmoes, Nathan C.; Shah, Manesh; Nyholm, Spencer V.

2014-01-01

The squid Euprymna scolopes and the luminescent bacterium Vibrio fischeri form a highly specific beneficial light organ symbiosis. Not only does the host have to select V. fischeri from the environment, but it must also prevent subsequent colonization by non-symbiotic microorganisms. Host macrophage-like hemocytes are believed to play a role in mediating the symbiosis with V. fischeri. Previous studies have shown that the colonization state of the light organ influences the host's hemocyte response to the symbiont. To further understand the molecular mechanisms behind this process, we used two quantitative mass-spectrometry-based proteomic techniques, isobaric tags for relative and absolute quantification (iTRAQ) and label-free spectral counting, to compare and quantify the adult hemocyte proteomes from colonized (sym) and uncolonized (antibiotic-treated/cured) squid. Overall, iTRAQ allowed for the quantification of 1,024 proteins with two or more peptides. Thirty-seven unique proteins were determined to be significantly different between sym and cured hemocytes (p value < 0.05), with 20 more abundant proteins and 17 less abundant in sym hemocytes. The label-free approach resulted in 1,241 proteins that were identified in all replicates. Of 185 unique proteins present at significantly different amounts in sym hemocytes (as determined by spectral counting), 92 were more abundant and 93 were less abundant. Comparisons between iTRAQ and spectral counting revealed that 30 of the 37 proteins quantified via iTRAQ exhibited trends similar to those identified by the label-free method. Both proteomic techniques mutually identified 16 proteins that were significantly different between the two groups of hemocytes (p value < 0.05). The presence of V. fischeri in the host light organ influenced the abundance of proteins associated with the cytoskeleton, adhesion, lysosomes, proteolysis, and the innate immune response. These data provide evidence that colonization by V. fischeri

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

PubMed

Calderón-Celis, Francisco; Encinar, Jorge Ruiz; Sanz-Medel, Alfredo

2017-07-31

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and

Emerging applications of label-free optical biosensors

NASA Astrophysics Data System (ADS)

Zanchetta, Giuliano; Lanfranco, Roberta; Giavazzi, Fabio; Bellini, Tommaso; Buscaglia, Marco

2017-01-01

Innovative technical solutions to realize optical biosensors with improved performance are continuously proposed. Progress in material fabrication enables developing novel substrates with enhanced optical responses. At the same time, the increased spectrum of available biomolecular tools, ranging from highly specific receptors to engineered bioconjugated polymers, facilitates the preparation of sensing surfaces with controlled functionality. What remains often unclear is to which extent this continuous innovation provides effective breakthroughs for specific applications. In this review, we address this challenging question for the class of label-free optical biosensors, which can provide a direct signal upon molecular binding without using secondary probes. Label-free biosensors have become a consolidated approach for the characterization and screening of molecular interactions in research laboratories. However, in the last decade, several examples of other applications with high potential impact have been proposed. We review the recent advances in label-free optical biosensing technology by focusing on the potential competitive advantage provided in selected emerging applications, grouped on the basis of the target type. In particular, direct and real-time detection allows the development of simpler, compact, and rapid analytical methods for different kinds of targets, from proteins to DNA and viruses. The lack of secondary interactions facilitates the binding of small-molecule targets and minimizes the perturbation in single-molecule detection. Moreover, the intrinsic versatility of label-free sensing makes it an ideal platform to be integrated with biomolecular machinery with innovative functionality, as in case of the molecular tools provided by DNA nanotechnology.

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide-based quantitative proteomics.

PubMed

Liu, Kehui; Zhang, Jiyang; Fu, Bin; Xie, Hongwei; Wang, Yingchun; Qian, Xiaohong

2014-07-01

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Human CD62Ldim neutrophils identified as a separate subset by proteome profiling and in vivo pulse-chase labeling.

PubMed

Tak, Tamar; Wijten, Patrick; Heeres, Marjolein; Pickkers, Peter; Scholten, Arjen; Heck, Albert J R; Vrisekoop, Nienke; Leenen, Luke P; Borghans, José A M; Tesselaar, Kiki; Koenderman, Leo

2017-06-29

During acute inflammation, 3 neutrophil subsets are found in the blood: neutrophils with a conventional segmented nucleus, neutrophils with a banded nucleus, and T-cell-suppressing CD62L dim neutrophils with a high number of nuclear lobes. In this study, we compared the in vivo kinetics and proteomes of banded, mature, and hypersegmented neutrophils to determine whether these cell types represent truly different neutrophil subsets or reflect changes induced by lipopolysaccharide (LPS) activation. Using in vivo pulse-chase labeling of neutrophil DNA with 6,6- 2 H 2 -glucose, we found that 2 H-labeled banded neutrophils appeared much earlier in blood than labeled CD62L dim and segmented neutrophils, which shared similar label kinetics. Comparison of the proteomes by cluster analysis revealed that CD62L dim neutrophils were clearly separate from conventional segmented neutrophils despite having similar kinetics in peripheral blood. Interestingly, the conventional segmented cells were more related at a proteome level to banded cells despite a 2-day difference in maturation time. The differences between CD62L dim and mature neutrophils are unlikely to have been a direct result of LPS-induced activation, because of the extremely low transcriptional capacity of CD62L dim neutrophils and the fact that neutrophils do not directly respond to the low dose of LPS used in the study (2 ng/kg body weight). Therefore, we propose CD62L dim neutrophils are a truly separate neutrophil subset that is recruited to the bloodstream in response to acute inflammation. This trial was registered at www.clinicaltrials.gov as #NCT01766414. © 2017 by The American Society of Hematology.

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

Nanostructured plasmonic interferometers for ultrasensitive label-free biosensing

NASA Astrophysics Data System (ADS)

Gao, Yongkang

Optical biosensors that utilize surface plasmon resonance (SPR) technique to analyze the biomolecular interactions have been extensively explored in the last two decades and have become the gold standard for label-free biosensing. These powerful sensing tools allow fast, highly-sensitive monitoring of the interaction between biomolecules in real time, without the need for laborious fluorescent labeling, and have found widely ranging applications from biomedical diagnostics and drug discovery, to environmental sensing and food safety monitoring. However, the prism-coupling SPR geometry is complex and bulky, and has severely limited the integration of this technique into low-cost portable biomedical devices for point-of-care diagnostics and personal healthcare applications. Also, the complex prism-coupling scheme prevents the use of high numerical aperture (NA) optics to increase the spatial resolution for multi-channel, high-throughput detection in SPR imaging mode. This dissertation is focused on the design and fabrication of a promising new class of nanopatterned interferometric SPR sensors that integrate the strengths of miniaturized nanoplasmonic architectures with sensitive optical interferometry techniques to achieve bold advances in SPR biosensing. The nanosensor chips developed provide superior sensing performance comparable to conventional SPR systems, but employing a far simpler collinear optical transmission geometry, which largely facilitates system integration, miniaturization, and low-cost production. Moreover, the fabricated nanostructure-based SPR sensors feature a very small sensor footprint, allowing massive multiplexing on a chip for high-throughput detection. The successful transformation of SPR technique from bulky prism-coupling setup into this low-cost compact plasmonic platform would have a far-reaching impact on point-of-care diagnostic tools and also lead to advances in high-throughput sensing applications in proteomics, immunology, drug

Shotgun ecotoxicoproteomics of Daphnia pulex: biochemical effects of the anticancer drug tamoxifen.

PubMed

Borgatta, Myriam; Hernandez, Céline; Decosterd, Laurent Arthur; Chèvre, Nathalie; Waridel, Patrice

2015-01-02

Among pollutants released into the environment by human activities, residues of pharmaceuticals are an increasing matter of concern because of their potential impact on ecosystems. The aim of this study was to analyze differences of protein expression resulting from acute (2 days) and middle-term (7 days) exposure of aquatic microcrustacean Daphnia pulex to the anticancer drug tamoxifen. Using a liquid chromatography-mass spectrometry shotgun approach, about 4000 proteins could be identified, providing the largest proteomics data set of D. pulex published up to now. Considering both time points and tested concentrations, 189 proteins showed a significant fold change. The identity of regulated proteins suggested a decrease in translation, an increase in protein degradation and changes in carbohydrate and lipid metabolism as the major effects of the drug. Besides these impacted processes, which reflect a general stress response of the organism, some other regulated proteins play a role in Daphnia reproduction. These latter results are in accordance with our previous observations of the impact of tamoxifen on D. pulex reproduction and illustrate the potential of ecotoxicoproteomics to unravel links between xenobiotic effects at the biochemical and organismal levels. Data are available via ProteomeXchange with identifier PXD001257.

The goat (Capra hircus) mammary gland secretory tissue proteome as influenced by weight loss: A study using label free proteomics

USDA-ARS?s Scientific Manuscript database

Seasonal weight loss (SWL) is a significant limitation to animal production. Breeds that have evolved in harsh climates have acquired tolerance to SWL through selection. Herein, labelfree proteomics was used to characterize the effects of SWL in two goat breeds with different levels of adaptation to...

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.

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

Proteomic Identification and Quantification of S-glutathionylation in Mouse Macrophages Using Resin-Assisted Enrichment and Isobaric Labeling

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

Su, Dian; Gaffrey, Matthew J.; Guo, Jia

2014-02-11

Protein S-glutathionylation (SSG) is an important regulatory posttranslational modification of protein cysteine (Cys) thiol redox switches, yet the role of specific cysteine residues as targets of modification is poorly understood. We report a novel quantitative mass spectrometry (MS)-based proteomic method for site-specific identification and quantification of S-glutathionylation across different conditions. Briefly, this approach consists of initial blocking of free thiols by alkylation, selective reduction of glutathionylated thiols and enrichment using thiol affinity resins, followed by on-resin tryptic digestion and isobaric labeling with iTRAQ (isobaric tags for relative and absolute quantitation) for MS-based identification and quantification. The overall approach was validatedmore » by application to RAW 264.7 mouse macrophages treated with different doses of diamide to induce glutathionylation. A total of 1071 Cys-sites from 690 proteins were identified in response to diamide treatment, with ~90% of the sites displaying >2-fold increases in SSG-modification compared to controls.. This approach was extended to identify potential SSG modified Cys-sites in response to H2O2, an endogenous oxidant produced by activated macrophages and many pathophysiological stimuli. The results revealed 364 Cys-sites from 265 proteins that were sensitive to S-glutathionylation in response to H2O2 treatment. These proteins covered a range of molecular types and molecular functions with free radical scavenging, and cell death and survival included as the most significantly enriched functional categories. Overall the results demonstrate that our approach is effective for site-specific identification and quantification of S-glutathionylated proteins. The analytical strategy also provides a unique approach to determining the major pathways and cell processes most susceptible to glutathionylation at a proteome-wide scale.« less

Golgi Enrichment and Proteomic Analysis of Developing Pinus radiata Xylem by Free-Flow Electrophoresis

PubMed Central

Macdonald, Lucy J.; Adams, Paul D.; Petzold, Christopher J.; Strabala, Timothy J.; Wagner, Armin; Heazlewood, Joshua L.

2013-01-01

Our understanding of the contribution of Golgi proteins to cell wall and wood formation in any woody plant species is limited. Currently, little Golgi proteomics data exists for wood-forming tissues. In this study, we attempted to address this issue by generating and analyzing Golgi-enriched membrane preparations from developing xylem of compression wood from the conifer Pinus radiata. Developing xylem samples from 3-year-old pine trees were harvested for this purpose at a time of active growth and subjected to a combination of density centrifugation followed by free flow electrophoresis, a surface charge separation technique used in the enrichment of Golgi membranes. This combination of techniques was successful in achieving an approximately 200-fold increase in the activity of the Golgi marker galactan synthase and represents a significant improvement for proteomic analyses of the Golgi from conifers. A total of thirty known Golgi proteins were identified by mass spectrometry including glycosyltransferases from gene families involved in glucomannan and glucuronoxylan biosynthesis. The free flow electrophoresis fractions of enriched Golgi were highly abundant in structural proteins (actin and tubulin) indicating a role for the cytoskeleton during compression wood formation. The mass spectrometry proteomics data associated with this study have been deposited to the ProteomeXchange with identifier PXD000557. PMID:24416096

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

The effect of intermediate clothing targets on shotgun ballistics.

PubMed

Cail, Kenneth; Klatt, Edward

2013-12-01

The ballistic properties of shotgun shells are complex because of multiple projectiles fired simultaneously that interact and spread out to affect their energy relayed to a human target. Intermediate targets such as clothing can affect penetration into tissues. We studied the effect of common clothing fabrics as intermediate targets on penetration of shotgun shell pellets, using ordnance gelatin to simulate soft tissue and thin cowhide to simulate skin. A standard 12-gauge shotgun with modified choke was used with no. 8 shot ammunition. We found that protection afforded by fabrics to reduce penetration of shotgun pellets into tissues was greater at increasing distance from the muzzle beyond 40 yd (36.6 m). The thicker denim and cotton fabrics provided slightly greater protection than polyester. This study demonstrates that clothing modifies the potential wound patterns to victims of shotgun injuries.

Multiple Click-Selective tRNA Synthetases Expand Mammalian Cell-Specific Proteomics.

PubMed

Yang, Andrew C; du Bois, Haley; Olsson, Niclas; Gate, David; Lehallier, Benoit; Berdnik, Daniela; Brewer, Kyle D; Bertozzi, Carolyn R; Elias, Joshua E; Wyss-Coray, Tony

2018-06-13

Bioorthogonal tools enable cell-type-specific proteomics, a prerequisite to understanding biological processes in multicellular organisms. Here we report two engineered aminoacyl-tRNA synthetases for mammalian bioorthogonal labeling: a tyrosyl ( ScTyr Y43G ) and a phenylalanyl ( MmPhe T413G ) tRNA synthetase that incorporate azide-bearing noncanonical amino acids specifically into the nascent proteomes of host cells. Azide-labeled proteins are chemoselectively tagged via azide-alkyne cycloadditions with fluorophores for imaging or affinity resins for mass spectrometric characterization. Both mutant synthetases label human, hamster, and mouse cell line proteins and selectively activate their azido-bearing amino acids over 10-fold above the canonical. ScTyr Y43G and MmPhe T413G label overlapping but distinct proteomes in human cell lines, with broader proteome coverage upon their coexpression. In mice, ScTyr Y43G and MmPhe T413G label the melanoma tumor proteome and plasma secretome. This work furnishes new tools for mammalian residue-specific bioorthogonal chemistry, and enables more robust and comprehensive cell-type-specific proteomics in live mammals.

Plasma Proteome Dynamics: Analysis of Lipoproteins and Acute Phase Response Proteins with 2H2O Metabolic Labeling*

PubMed Central

Li, Ling; Willard, Belinda; Rachdaoui, Nadia; Kirwan, John P.; Sadygov, Rovshan G.; Stanley, William C.; Previs, Stephen; McCullough, Arthur J.; Kasumov, Takhar

2012-01-01

Understanding the pathologies related to the regulation of protein metabolism requires methods for studying the kinetics of individual proteins. We developed a 2H2O metabolic labeling technique and software for protein kinetic studies in free living organisms. This approach for proteome dynamic studies requires the measurement of total body water enrichments by GC-MS, isotopic distribution of the tryptic peptide by LC-MS/MS, and estimation of the asymptotical number of deuterium incorporated into a peptide by software. We applied this technique to measure the synthesis rates of several plasma lipoproteins and acute phase response proteins in rats. Samples were collected at different time points, and proteins were separated by a gradient gel electrophoresis. 2H labeling of tryptic peptides was analyzed by ion trap tandem mass spectrometry (LTQ MS/MS) for measurement of the fractional synthesis rates of plasma proteins. The high sensitivity of LTQ MS in zoom scan mode in combination with 2H label amplification in proteolytic peptides allows detection of the changes in plasma protein synthesis related to animal nutritional status. Our results demonstrate that fasting has divergent effects on the rate of synthesis of plasma proteins, increasing synthesis of ApoB 100 but decreasing formation of albumin and fibrinogen. We conclude that this technique can effectively measure the synthesis of plasma proteins and can be used to study the regulation of protein homeostasis under physiological and pathological conditions. PMID:22393261

Plant proteome analysis: a 2006 update.

PubMed

Jorrín, Jesús V; Maldonado, Ana M; Castillejo, Ma Angeles

2007-08-01

This 2006 'Plant Proteomics Update' is a continuation of the two previously published in 'Proteomics' by 2004 (Canovas et al., Proteomics 2004, 4, 285-298) and 2006 (Rossignol et al., Proteomics 2006, 6, 5529-5548) and it aims to bring up-to-date the contribution of proteomics to plant biology on the basis of the original research papers published throughout 2006, with references to those appearing last year. According to the published papers and topics addressed, we can conclude that, as observed for the three previous years, there has been a quantitative, but not qualitative leap in plant proteomics. The full potential of proteomics is far from being exploited in plant biology research, especially if compared to other organisms, mainly yeast and humans, and a number of challenges, mainly technological, remain to be tackled. The original papers published last year numbered nearly 100 and deal with the proteome of at least 26 plant species, with a high percentage for Arabidopsis thaliana (28) and rice (11). Scientific objectives ranged from proteomic analysis of organs/tissues/cell suspensions (57) or subcellular fractions (29), to the study of plant development (12), the effect of hormones and signalling molecules (8) and response to symbionts (4) and stresses (27). A small number of contributions have covered PTMs (8) and protein interactions (4). 2-DE (specifically IEF-SDS-PAGE) coupled to MS still constitutes the almost unique platform utilized in plant proteome analysis. The application of gel-free protein separation methods and 'second generation' proteomic techniques such as multidimensional protein identification technology (MudPIT), and those for quantitative proteomics including DIGE, isotope-coded affinity tags (ICAT), iTRAQ and stable isotope labelling by amino acids in cell culture (SILAC) still remains anecdotal. This review is divided into seven sections: Introduction, Methodology, Subcellular proteomes, Development, Responses to biotic and abiotic

P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

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

Webb-Robertson, Bobbie-Jo M.; Bramer, Lisa M.; Jensen, Jeffrey L.

P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. 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 to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternativelymore » available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).« less

Effects of Fe and Mn deficiencies on the protein profiles of tomato (Solanum lycopersicum) xylem sap as revealed by shotgun analyses.

PubMed

Ceballos-Laita, Laura; Gutierrez-Carbonell, Elain; Takahashi, Daisuke; Abadía, Anunciación; Uemura, Matsuo; Abadía, Javier; López-Millán, Ana Flor

2018-01-06

The aim of this work was to study the effects of Fe and Mn deficiencies on the xylem sap proteome of tomato using a shotgun proteomic approach, with the final goal of elucidating plant response mechanisms to these stresses. This approach yielded 643 proteins reliably identified and quantified with 70% of them predicted as secretory. Iron and Mn deficiencies caused statistically significant and biologically relevant abundance changes in 119 and 118 xylem sap proteins, respectively. In both deficiencies, metabolic pathways most affected were protein metabolism, stress/oxidoreductases and cell wall modifications. First, results suggest that Fe deficiency elicited more stress responses than Mn deficiency, based on the changes in oxidative and proteolytic enzymes. Second, both nutrient deficiencies affect the secondary cell wall metabolism, with changes in Fe deficiency occurring via peroxidase activity, and in Mn deficiency involving peroxidase, Cu-oxidase and fasciclin-like arabinogalactan proteins. Third, the primary cell wall metabolism was affected by both nutrient deficiencies, with changes following opposite directions as judged from the abundances of several glycoside-hydrolases with endo-glycolytic activities and pectin esterases. Fourth, signaling pathways via xylem involving CLE and/or lipids as well as changes in phosphorylation and N-glycosylation also play a role in the responses to these stresses. Biological significance In spite of being essential for the delivery of nutrients to the shoots, our knowledge of xylem responses to nutrient deficiencies is very limited. The present work applies a shotgun proteomic approach to unravel the effects of Fe and Mn deficiencies on the xylem sap proteome. Overall, Fe deficiency seems to elicit more stress in the xylem sap proteome than Mn deficiency, based on the changes measured in proteolytic and oxido-reductase proteins, whereas both nutrients exert modifications in the composition of the primary and secondary

Label-free high-throughput imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mahjoubfar, A.; Chen, C.; Niazi, K. R.; Rabizadeh, S.; Jalali, B.

2014-03-01

Flow cytometry is an optical method for studying cells based on their individual physical and chemical characteristics. It is widely used in clinical diagnosis, medical research, and biotechnology for analysis of blood cells and other cells in suspension. Conventional flow cytometers aim a laser beam at a stream of cells and measure the elastic scattering of light at forward and side angles. They also perform single-point measurements of fluorescent emissions from labeled cells. However, many reagents used in cell labeling reduce cellular viability or change the behavior of the target cells through the activation of undesired cellular processes or inhibition of normal cellular activity. Therefore, labeled cells are not completely representative of their unaltered form nor are they fully reliable for downstream studies. To remove the requirement of cell labeling in flow cytometry, while still meeting the classification sensitivity and specificity goals, measurement of additional biophysical parameters is essential. Here, we introduce an interferometric imaging flow cytometer based on the world's fastest continuous-time camera. Our system simultaneously measures cellular size, scattering, and protein concentration as supplementary biophysical parameters for label-free cell classification. It exploits the wide bandwidth of ultrafast laser pulses to perform blur-free quantitative phase and intensity imaging at flow speeds as high as 10 meters per second and achieves nanometer-scale optical path length resolution for precise measurements of cellular protein concentration.

Seasonal heat stress affects adipose tissue proteome toward enrichment of the Nrf2-mediated oxidative stress response in late-pregnant dairy cows.

PubMed

Zachut, M; Kra, G; Livshitz, L; Portnick, Y; Yakoby, S; Friedlander, G; Levin, Y

2017-03-31

Environmental heat stress and metabolic stress during transition from late gestation to lactation are main factors limiting production in dairy cattle, and there is a complex interaction between them. Many proteins expressed in adipose tissue are involved in metabolic responses to stress. We aimed to investigate the effects of seasonal heat stress on adipose proteome in late-pregnant cows, and to identify biomarkers of heat stress. Late pregnant cows during summer heat stress (S, n=18), or during the winter season (W, n=12) were used. Subcutaneous adipose tissue biopsies sampled 14days prepartum from S (n=10) and W (n=8) were analyzed by intensity-based, label-free, quantitative shotgun proteomics (nano-LC-MS/MS). Plasma concentrations of malondialdehyde and cortisol were higher in S than in W cows. Proteomic analysis revealed that 107/1495 proteins were differentially abundant in S compared to W (P<0.05 and fold change of at least ±1.5). Top canonical pathways in S vs. W adipose were Nrf2-mediated oxidative stress response, acute-phase response, and FXR/RXR and LXR/RXR activation. Novel biomarkers of heat stress in adipose tissue were found. These findings indicate that seasonal heat stress has a unique effect on adipose tissue in late-pregnant cows. This work shows that seasonal heat stress increases plasma concentrations of the oxidative stress marker malondialdehyde and cortisol in transition dairy cows. As many proteins expressed in the adipose tissue are involved in metabolic responses to stress, we investigated the effects of heat stress on the proteome of adipose tissue from late-pregnant cows during summer or winter seasons. We demonstrated that heat stress enriches several stress-related pathways, such as the Nrf2-mediated oxidative stress response and the acute-phase response in adipose tissues. Thus, environmental heat stress has a unique effect on adipose tissue in late-pregnant cows, as part of the regulatory adaptations to chronic heat load during

Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine.

PubMed

Zhang, Xi

2017-02-01

Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel image processing method study for a label-free optical biosensor

NASA Astrophysics Data System (ADS)

Yang, Chenhao; Wei, Li'an; Yang, Rusong; Feng, Ying

2015-10-01

Optical biosensor is generally divided into labeled type and label-free type, the former mainly contains fluorescence labeled method and radioactive-labeled method, while fluorescence-labeled method is more mature in the application. The mainly image processing methods of fluorescent-labeled biosensor includes smooth filtering, artificial gridding and constant thresholding. Since some fluorescent molecules may influence the biological reaction, label-free methods have been the main developing direction of optical biosensors nowadays. The using of wider field of view and larger angle of incidence light path which could effectively improve the sensitivity of the label-free biosensor also brought more difficulties in image processing, comparing with the fluorescent-labeled biosensor. Otsu's method is widely applied in machine vision, etc, which choose the threshold to minimize the intraclass variance of the thresholded black and white pixels. It's capacity-constrained with the asymmetrical distribution of images as a global threshold segmentation. In order to solve the irregularity of light intensity on the transducer, we improved the algorithm. In this paper, we present a new image processing algorithm based on a reflectance modulation biosensor platform, which mainly comprises the design of sliding normalization algorithm for image rectification and utilizing the improved otsu's method for image segmentation, in order to implement automatic recognition of target areas. Finally we used adaptive gridding method extracting the target parameters for analysis. Those methods could improve the efficiency of image processing, reduce human intervention, enhance the reliability of experiments and laid the foundation for the realization of high throughput of label-free optical biosensors.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

Shotgun metagenomic data streams: surfing without fear

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

Berendzen, Joel R

2010-12-06

Timely information about bio-threat prevalence, consequence, propagation, attribution, and mitigation is needed to support decision-making, both routinely and in a crisis. One DNA sequencer can stream 25 Gbp of information per day, but sampling strategies and analysis techniques are needed to turn raw sequencing power into actionable knowledge. Shotgun metagenomics can enable biosurveillance at the level of a single city, hospital, or airplane. Metagenomics characterizes viruses and bacteria from complex environments such as soil, air filters, or sewage. Unlike targeted-primer-based sequencing, shotgun methods are not blind to sequences that are truly novel, and they can measure absolute prevalence. Shotgun metagenomicmore » sampling can be non-invasive, efficient, and inexpensive while being informative. We have developed analysis techniques for shotgun metagenomic sequencing that rely upon phylogenetic signature patterns. They work by indexing local sequence patterns in a manner similar to web search engines. Our methods are laptop-fast and favorable scaling properties ensure they will be sustainable as sequencing methods grow. We show examples of application to soil metagenomic samples.« less

Metabolic labeling reveals proteome dynamics of mouse mitochondria.

PubMed

Kim, Tae-Young; Wang, Ding; Kim, Allen K; Lau, Edward; Lin, Amanda J; Liem, David A; Zhang, Jun; Zong, Nobel C; Lam, Maggie P Y; Ping, Peipei

2012-12-01

Mitochondrial dysfunction is associated with many human diseases. Mitochondrial damage is exacerbated by inadequate protein quality control and often further contributes to pathogenesis. The maintenance of mitochondrial functions requires a delicate balance of continuous protein synthesis and degradation, i.e. protein turnover. To understand mitochondrial protein dynamics in vivo, we designed a metabolic heavy water ((2)H(2)O) labeling strategy customized to examine individual protein turnover in the mitochondria in a systematic fashion. Mice were fed with (2)H(2)O at a minimal level (<5% body water) without physiological impacts. Mitochondrial proteins were analyzed from 9 mice at each of the 13 time points between 0 and 90 days (d) of labeling. A novel multiparameter fitting approach computationally determined the normalized peak areas of peptide mass isotopomers at initial and steady-state time points and permitted the protein half-life to be determined without plateau-level (2)H incorporation. We characterized the turnover rates of 458 proteins in mouse cardiac and hepatic mitochondria and found median turnover rates of 0.0402 d(-1) and 0.163 d(-1), respectively, corresponding to median half-lives of 17.2 d and 4.26 d. Mitochondria in the heart and those in the liver exhibited distinct turnover kinetics, with limited synchronization within functional clusters. We observed considerable interprotein differences in turnover rates in both organs, with half-lives spanning from hours to months (≈ 60 d). Our proteomics platform demonstrates the first large-scale analysis of mitochondrial protein turnover rates in vivo, with potential applications in translational research.

Novel royal jelly proteins identified by gel-based and gel-free proteomics.

PubMed

Han, Bin; Li, Chenxi; Zhang, Lan; Fang, Yu; Feng, Mao; Li, Jianke

2011-09-28

Royal jelly (RJ) plays an important role in caste determination of the honeybee; the genetically same female egg develops into either a queen or worker bee depending on the time and amount of RJ fed to the larvae. RJ also has numerous health-promoting properties for humans. Gel-based and gel-free proteomics approaches and high-performance liquid chromatography-chip quadruple time-of-flight tandem mass spectrometry were applied to comprehensively investigate the protein components of RJ. Overall, 37 and 22 nonredundant proteins were identified by one-dimensional gel electrophoresis and gel-free analysis, respectively, and 19 new proteins were found by these two proteomics approaches. Major royal jelly proteins (MRJPs) were identified as the principal protein components of RJ, and proteins related to carbohydrate metabolism such as glucose oxidase, α-glucosidase precursor, and glucose dehydrogenase were also successfully identified. Importantly, the 19 newly identified proteins were mainly classified into three functional categories: oxidation-reduction (ergic53 CG6822-PA isoform A isoform 1, Sec61 CG9539-PA, and ADP/ATP translocase), protein binding (regucalcin and translationally controlled tumor protein CG4800-PA isoform 1), and lipid transport (apolipophorin-III-like protein). These new findings not only significantly increase the RJ proteome coverage but also help to provide new knowledge of RJ for honeybee biology and potential use for human health promotion.

Analysis of the Cerebrospinal Fluid Proteome in Alzheimer's Disease

PubMed Central

Khoonsari, Payam Emami; Häggmark, Anna; Lönnberg, Maria; Mikus, Maria; Kilander, Lena; Lannfelt, Lars; Bergquist, Jonas; Ingelsson, Martin; Nilsson, Peter

2016-01-01

Alzheimer’s disease is a neurodegenerative disorder accounting for more than 50% of cases of dementia. Diagnosis of Alzheimer’s disease relies on cognitive tests and analysis of amyloid beta, protein tau, and hyperphosphorylated tau in cerebrospinal fluid. Although these markers provide relatively high sensitivity and specificity for early disease detection, they are not suitable for monitor of disease progression. In the present study, we used label-free shotgun mass spectrometry to analyse the cerebrospinal fluid proteome of Alzheimer’s disease patients and non-demented controls to identify potential biomarkers for Alzheimer’s disease. We processed the data using five programs (DecyderMS, Maxquant, OpenMS, PEAKS, and Sieve) and compared their results by means of reproducibility and peptide identification, including three different normalization methods. After depletion of high abundant proteins we found that Alzheimer’s disease patients had lower fraction of low-abundance proteins in cerebrospinal fluid compared to healthy controls (p<0.05). Consequently, global normalization was found to be less accurate compared to using spiked-in chicken ovalbumin for normalization. In addition, we determined that Sieve and OpenMS resulted in the highest reproducibility and PEAKS was the programs with the highest identification performance. Finally, we successfully verified significantly lower levels (p<0.05) of eight proteins (A2GL, APOM, C1QB, C1QC, C1S, FBLN3, PTPRZ, and SEZ6) in Alzheimer’s disease compared to controls using an antibody-based detection method. These proteins are involved in different biological roles spanning from cell adhesion and migration, to regulation of the synapse and the immune system. PMID:26950848

Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.

PubMed

Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.

A Critical Appraisal of Techniques, Software Packages, and Standards for Quantitative Proteomic Analysis

PubMed Central

Lawless, Craig; Hubbard, Simon J.; Fan, Jun; Bessant, Conrad; Hermjakob, Henning; Jones, Andrew R.

2012-01-01

Abstract New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool (http://www.proteosuite.org/?q=other_resources) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology. PMID:22804616

Label-free resistive-pulse cytometry.

PubMed

Chapman, M R; Sohn, L L

2011-01-01

Numerous methods have recently been developed to characterize cells for size, shape, and specific cell-surface markers. Most of these methods rely upon exogenous labeling of the cells and are better suited for large cell populations (>10,000). Here, we review a label-free method of characterizing and screening cells based on the Coulter-counter technique of particle sizing: an individual cell transiting a microchannel (or "pore") causes a downward pulse in the measured DC current across that "pore". Pulse magnitude corresponds to the cell size, pulse width to the transit time needed for the cell to pass through the pore, and pulse shape to how the cell traverses across the pore (i.e., rolling or tumbling). When the pore is functionalized with an antibody that is specific to a surface-epitope of interest, label-free screening of a specific marker is possible, as transient binding between the two results in longer time duration than when the pore is unfunctionalized or functionalized with a nonspecific antibody. While this method cannot currently compete with traditional technology in terms of throughput, there are a number of applications for which this technology is better suited than current commercial cytometry systems. Applications include the rapid and nondestructive analysis of small cell populations (<100), which is not possible with current technology, and a platform for providing true point-of-care clinical diagnostics, due to the simplicity of the device, low manufacturing costs, and ease of use. Copyright © 2011 Elsevier Inc. All rights reserved.

Study and development of label-free optical biosensors for biomedical applications

NASA Astrophysics Data System (ADS)

Choi, Charles J.

For the majority of assays currently performed, fluorescent or colorimetric chemical labels are commonly attached to the molecules under study so that they may be readily visualized. The methods of using labels to track biomolecular binding events are very sensitive and effective, and are employed as standardized assay protocol across research labs worldwide. However, using labels induces experimental uncertainties due to the effect of the label on molecular conformation, active binding sites, or inability to find an appropriate label that functions equivalently for all molecules in an experiment. Therefore, the ability to perform highly sensitive biochemical detection without the use of fluorescent labels would further simplify assay protocols and would provide quantitative kinetic data, while removing experimental artifacts from fluorescent quenching, shelf-life, and background fluorescence phenomena. In view of the advantages mentioned above, the study and development of optical label-free sensor technologies have been undertaken here. In general, label-free photonic crystal (PC) biosensors and metal nanodome array surface-enhanced Raman scattering (SERS) substrates, both of which are fabricated by nanoreplica molding process, have been used as the method to attack the problem. Chapter 1 shows the work on PC label-free biosensor incorporated microfluidic network for bioassay performance enhancement and kinetic reaction rate constant determination. Chapter 2 describes the work on theoretical and experimental comparison of label-free biosensing in microplate, microfluidic, and spot-based affinity capture assays. Chapter 3 shows the work on integration of PC biosensor with actuate-to-open valve microfluidic chip for pL-volume combinatorial mixing and screening application. In Chapter 4, the development and characterization of SERS nanodome array is shown. Lastly, Chapter 5 describes SERS nanodome sensor incorporated tubing for point-of-care monitoring of

Nanoscale Label-free Bioprobes to Detect Intracellular Proteins in Single Living Cells

PubMed Central

Hong, Wooyoung; Liang, Feng; Schaak, Diane; Loncar, Marko; Quan, Qimin

2014-01-01

Fluorescent labeling techniques have been widely used in live cell studies; however, the labeling processes can be laborious and challenging for use in non-transfectable cells, and labels can interfere with protein functions. While label-free biosensors have been realized by nanofabrication, a method to track intracellular protein dynamics in real-time, in situ and in living cells has not been found. Here we present the first demonstration of label-free detection of intracellular p53 protein dynamics through a nanoscale surface plasmon-polariton fiber-tip-probe (FTP). PMID:25154394

Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy.

PubMed

You, Sixian; Tu, Haohua; Chaney, Eric J; Sun, Yi; Zhao, Youbo; Bower, Andrew J; Liu, Yuan-Zhi; Marjanovic, Marina; Sinha, Saurabh; Pu, Yang; Boppart, Stephen A

2018-05-29

Intravital microscopy (IVM) emerged and matured as a powerful tool for elucidating pathways in biological processes. Although label-free multiphoton IVM is attractive for its non-perturbative nature, its wide application has been hindered, mostly due to the limited contrast of each imaging modality and the challenge to integrate them. Here we introduce simultaneous label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 MHz to enable fast (2-orders-of-magnitude improvement), simultaneous, and efficient acquisition of autofluorescence (FAD and NADH) and second/third harmonic generation from a wide array of cellular and extracellular components (e.g., tumor cells, immune cells, vesicles, and vessels) in living tissue using only 14 mW for extended time-lapse investigations. Our work demonstrates the versatility and efficiency of SLAM microscopy for tracking cellular events in vivo, and is a major enabling advance in label-free IVM.

Alternative fluorescent labeling strategies for characterizing gram-positive pathogenic bacteria: Flow cytometry supported counting, sorting, and proteome analysis of Staphylococcus aureus retrieved from infected host cells.

PubMed

Hildebrandt, Petra; Surmann, Kristin; Salazar, Manuela Gesell; Normann, Nicole; Völker, Uwe; Schmidt, Frank

2016-10-01

Staphylococcus aureus is a Gram-positive opportunistic pathogen that is able to cause a broad range of infectious diseases in humans. Furthermore, S. aureus is able to survive inside nonprofessional phagocytic host cell which serve as a niche for the pathogen to hide from the immune system and antibiotics therapies. Modern OMICs technologies provide valuable tools to investigate host-pathogen interactions upon internalization. However, these experiments are often hampered by limited capabilities to retrieve bacteria from such an experimental setting. Thus, the aim of this study was to develop a labeling strategy allowing fast detection and quantitation of S. aureus in cell lysates or infected cell lines by flow cytometry for subsequent proteome analyses. Therefore, S. aureus cells were labeled with the DNA stain SYTO ® 9, or Vancomycin BODIPY ® FL (VMB), a glycopeptide antibiotic binding to most Gram-positive bacteria which was conjugated to a fluorescent dye. Staining of S. aureus HG001 with SYTO 9 allowed counting of bacteria from pure cultures but not in cell lysates from infection experiments. In contrast, with VMB it was feasible to stain bacteria from pure cultures as well as from samples of infection experiments. VMB can also be applied for histocytochemistry analysis of formaldehyde fixed cell layers grown on coverslips. Proteome analyses of S. aureus labeled with VMB revealed that the labeling procedure provoked only minor changes on proteome level and allowed cell sorting and analysis of S. aureus from infection settings with sensitivity similar to continuous gfp expression. Furthermore, VMB labeling allowed precise counting of internalized bacteria and can be employed for downstream analyses, e.g., proteomics, of strains not easily amendable to genetic manipulation such as clinical isolates. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Label-free photoacoustic nanoscopy

PubMed Central

Danielli, Amos; Maslov, Konstantin; Garcia-Uribe, Alejandro; Winkler, Amy M.; Li, Chiye; Wang, Lidai; Chen, Yun; Dorn, Gerald W.; Wang, Lihong V.

2014-01-01

Abstract. Super-resolution microscopy techniques—capable of overcoming the diffraction limit of light—have opened new opportunities to explore subcellular structures and dynamics not resolvable in conventional far-field microscopy. However, relying on staining with exogenous fluorescent markers, these techniques can sometimes introduce undesired artifacts to the image, mainly due to large tagging agent sizes and insufficient or variable labeling densities. By contrast, the use of endogenous pigments allows imaging of the intrinsic structures of biological samples with unaltered molecular constituents. Here, we report label-free photoacoustic (PA) nanoscopy, which is exquisitely sensitive to optical absorption, with an 88 nm resolution. At each scanning position, multiple PA signals are successively excited with increasing laser pulse energy. Because of optical saturation or nonlinear thermal expansion, the PA amplitude depends on the nonlinear incident optical fluence. The high-order dependence, quantified by polynomial fitting, provides super-resolution imaging with optical sectioning. PA nanoscopy is capable of super-resolution imaging of either fluorescent or nonfluorescent molecules. PMID:25104412

A New Algorithm Using Cross-Assignment for Label-Free Quantitation with LC/LTQ-FT MS

PubMed Central

Andreev, Victor P.; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L.

2008-01-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQFT MS mass spectrometer (or other high resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed “cross-assignment”, is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC/MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of E.coli samples spiked with known amounts of non-E.coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC/MS datasets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication. PMID:17441747

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

PubMed

Andreev, Victor P; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L

2007-06-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.

A statistical framework for protein quantitation in bottom-up MS-based proteomics

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

Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

2009-08-15

ABSTRACT Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and confidence measures. Challenges include the presence of low-quality or incorrectly identified peptides and widespread, informative, missing data. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model for protein abundance in terms of peptide peak intensities, applicable to both label-based and label-free quantitation experiments. The model allows for both random and censoring missingness mechanisms and provides naturally for protein-level estimates and confidence measures. The model is also used to derive automated filtering and imputation routines. Three LC-MS datasets are used tomore » illustrate the methods. Availability: The software has been made available in the open-source proteomics platform DAnTE (Polpitiya et al. (2008)) (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu« less

A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

PubMed

Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

2013-03-01

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

Proteomic Analysis of a NAP1 Clostridium difficile Clinical Isolate Resistant to Metronidazole

PubMed Central

Chong, Patrick M.; Lynch, Tarah; McCorrister, Stuart; Kibsey, Pamela; Miller, Mark; Gravel, Denise; Westmacott, Garrett R.; Mulvey, Michael R.

2014-01-01

Background Clostridium difficile is an anaerobic, Gram-positive bacterium that has been implicated as the leading cause of antibiotic-associated diarrhea. Metronidazole is currently the first-line treatment for mild to moderate C. difficile infections. Our laboratory isolated a strain of C. difficile with a stable resistance phenotype to metronidazole. A shotgun proteomics approach was used to compare differences in the proteomes of metronidazole-resistant and -susceptible isolates. Methodology/Principal Findings NAP1 C. difficile strains CD26A54_R (Met-resistant), CD26A54_S (reduced- susceptibility), and VLOO13 (Met-susceptible) were grown to mid-log phase, and spiked with metronidazole at concentrations 2 doubling dilutions below the MIC. Peptides from each sample were labeled with iTRAQ and subjected to 2D-LC-MS/MS analysis. In the absence of metronidazole, higher expression was observed of some proteins in C. difficile strains CD26A54_S and CD26A54_R that may be involved with reduced susceptibility or resistance to metronidazole, including DNA repair proteins, putative nitroreductases, and the ferric uptake regulator (Fur). After treatment with metronidazole, moderate increases were seen in the expression of stress-related proteins in all strains. A moderate increase was also observed in the expression of the DNA repair protein RecA in CD26A54_R. Conclusions/Significance This study provided an in-depth proteomic analysis of a stable, metronidazole-resistant C. difficile isolate. The results suggested that a multi-factorial response may be associated with high level metronidazole-resistance in C. difficile, including the possible roles of altered iron metabolism and/or DNA repair. PMID:24400070

Proteomic analysis of a NAP1 Clostridium difficile clinical isolate resistant to metronidazole.

PubMed

Chong, Patrick M; Lynch, Tarah; McCorrister, Stuart; Kibsey, Pamela; Miller, Mark; Gravel, Denise; Westmacott, Garrett R; Mulvey, Michael R

2014-01-01

Clostridium difficile is an anaerobic, Gram-positive bacterium that has been implicated as the leading cause of antibiotic-associated diarrhea. Metronidazole is currently the first-line treatment for mild to moderate C. difficile infections. Our laboratory isolated a strain of C. difficile with a stable resistance phenotype to metronidazole. A shotgun proteomics approach was used to compare differences in the proteomes of metronidazole-resistant and -susceptible isolates. NAP1 C. difficile strains CD26A54_R (Met-resistant), CD26A54_S (reduced- susceptibility), and VLOO13 (Met-susceptible) were grown to mid-log phase, and spiked with metronidazole at concentrations 2 doubling dilutions below the MIC. Peptides from each sample were labeled with iTRAQ and subjected to 2D-LC-MS/MS analysis. In the absence of metronidazole, higher expression was observed of some proteins in C. difficile strains CD26A54_S and CD26A54_R that may be involved with reduced susceptibility or resistance to metronidazole, including DNA repair proteins, putative nitroreductases, and the ferric uptake regulator (Fur). After treatment with metronidazole, moderate increases were seen in the expression of stress-related proteins in all strains. A moderate increase was also observed in the expression of the DNA repair protein RecA in CD26A54_R. This study provided an in-depth proteomic analysis of a stable, metronidazole-resistant C. difficile isolate. The results suggested that a multi-factorial response may be associated with high level metronidazole-resistance in C. difficile, including the possible roles of altered iron metabolism and/or DNA repair.

Rapid label-free profiling of oral cancer biomarker proteins using nano-UPLC-Q-TOF ion mobility mass spectrometry.

PubMed

Nassar, Ala F; Williams, Brad J; Yaworksy, Dustin C; Patel, Vyomesh; Rusling, James F

2016-03-01

It has become quite clear that single cancer biomarkers cannot in general provide high sensitivity and specificity for reliable clinical cancer diagnostics. This paper explores the feasibility of rapid detection of multiple biomarker proteins in model oral cancer samples using label-free protein relative quantitation. MS-based label-free quantitative proteomics offer a rapid alternative that bypasses the need for stable isotope containing compounds to chemically bind and label proteins. Total protein content in oral cancer cell culture conditioned media was precipitated, subjected to proteolytic digestion, and then analyzed using a nano-UPLC (where UPLC is ultra-performance liquid chromatography) coupled to a hybrid Q-Tof ion-mobility mass spectrometry (MS). Rapid, simultaneous identification and quantification of multiple possible cancer biomarker proteins was achieved. In a comparative study between cancer and noncancer samples, approximately 952 proteins were identified using a high-throughput 1D ion mobility assisted data independent acquisition (IM-DIA) approach. As we previously demonstrated that interleukin-8 (IL-8) and vascular endothelial growth factor A (VEGF-A) were readily detected in oral cancer cell conditioned media(1), we targeted these biomarker proteins to validate our approach. Target biomarker protein IL-8 was found between 3.5 and 8.8 fmol, while VEGF-A was found at 1.45 fmol in the cancer cell media. Overall, our data suggest that the nano-UPLC-IM-DIA bioassay is a feasible approach to identify and quantify proteins in complex samples without the need for stable isotope labeling. These results have significant implications for rapid tumor diagnostics and prognostics by monitoring proteins such as IL-8 and VEGF-A implicated in cancer development and progression. The analysis in tissue or plasma is not possible at this time, but the subsequent work would be needed for validation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Approach for Extracting Cytoplasmic Proteins from Streptococcus sanguinis using Mass Spectrometry

PubMed Central

El-Rami, Fadi; Nelson, Kristina; Xu, Ping

2017-01-01

Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining “proteomic signatures” as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis. PMID:29152022

Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.

PubMed

Martínez-Bartolomé, Salvador; Deutsch, Eric W; Binz, Pierre-Alain; Jones, Andrew R; Eisenacher, Martin; Mayer, Gerhard; Campos, Alex; Canals, Francesc; Bech-Serra, Joan-Josep; Carrascal, Montserrat; Gay, Marina; Paradela, Alberto; Navajas, Rosana; Marcilla, Miguel; Hernáez, María Luisa; Gutiérrez-Blázquez, María Dolores; Velarde, Luis Felipe Clemente; Aloria, Kerman; Beaskoetxea, Jabier; Medina-Aunon, J Alberto; Albar, Juan P

2013-12-16

Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and

Label-Free Aptasensors for the Detection of Mycotoxins

PubMed Central

Rhouati, Amina; Catanante, Gaelle; Nunes, Gilvanda; Hayat, Akhtar; Marty, Jean-Louis

2016-01-01

Various methodologies have been reported in the literature for the qualitative and quantitative monitoring of mycotoxins in food and feed samples. Based on their enhanced specificity, selectivity and versatility, bio-affinity assays have inspired many researchers to develop sensors by exploring bio-recognition phenomena. However, a significant problem in the fabrication of these devices is that most of the biomolecules do not generate an easily measurable signal upon binding to the target analytes, and signal-generating labels are required to perform the measurements. In this context, aptamers have been emerged as a potential and attractive bio-recognition element to design label-free aptasensors for various target analytes. Contrary to other bioreceptor-based approaches, the aptamer-based assays rely on antigen binding-induced conformational changes or oligomerization states rather than binding-assisted changes in adsorbed mass or charge. This review will focus on current designs in label-free conformational switchable design strategies, with a particular focus on applications in the detection of mycotoxins. PMID:27999353

The wheat chloroplastic proteome.

PubMed

Kamal, Abu Hena Mostafa; Cho, Kun; Choi, Jong-Soon; Bae, Kwang-Hee; Komatsu, Setsuko; Uozumi, Nobuyuki; Woo, Sun Hee

2013-11-20

With the availability of plant genome sequencing, analysis of plant proteins with mass spectrometry has become promising and admired. Determining the proteome of a cell is still a challenging assignment, which is convoluted by proteome dynamics and convolution. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. In this review, an overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. In recent years, we and other groups have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during vegetative stage. Those studies provide interesting results leading to better understanding of the photosynthesis and identifying the stress-responsive proteins. Indeed, recent studies aimed at resolving the photosynthesis pathway in wheat. Proteomic analysis combining two complementary approaches such as 2-DE and shotgun methods couple to high through put mass spectrometry (LTQ-FTICR and MALDI-TOF/TOF) in order to better understand the responsible proteins in photosynthesis and abiotic stress (salt and water) in wheat chloroplast will be focused. In this review we discussed the identification of the most abundant protein in wheat chloroplast and stress-responsive under salt and water stress in chloroplast of wheat seedlings, thus providing the proteomic view of the events during the development of this seedling under stress conditions. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. An overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. We have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during seedling stage. Those studies

Novel Advances in Shotgun Lipidomics for Biology and Medicine

PubMed Central

Wang, Miao; Wang, Chunyan; Han, Rowland H.; Han, Xianlin

2015-01-01

The field of lipidomics, as coined in 2003, has made profound advances and been rapidly expanded. The mass spectrometry-based strategies of this analytical methodology-oriented research discipline for lipid analysis are largely fallen into three categories: direct infusion-based shotgun lipidomics, liquid chromatography-mass spectrometry-based platforms, and matrix-assisted laser desorption/ionization mass spectrometry-based approaches (particularly in imagining lipid distribution in tissues or cells). This review focuses on shotgun lipidomics. After briefly introducing its fundamentals, the major materials of this article cover its recent advances. These include the novel methods of lipid extraction, novel shotgun lipidomics strategies for identification and quantification of previously hardly accessible lipid classes and molecular species including isomers, and novel tools for processing and interpretation of lipidomics data. Representative applications of advanced shotgun lipidomics for biological and biomedical research are also presented in this review. We believe that with these novel advances in shotgun lipidomics, this approach for lipid analysis should become more comprehensive and high throughput, thereby greatly accelerating the lipidomics field to substantiate the aberrant lipid metabolism, signaling, trafficking, and homeostasis under pathological conditions and their underpinning biochemical mechanisms. PMID:26703190

Developments in label-free microfluidic methods for single-cell analysis and sorting.

PubMed

Carey, Thomas R; Cotner, Kristen L; Li, Brian; Sohn, Lydia L

2018-04-24

Advancements in microfluidic technologies have led to the development of many new tools for both the characterization and sorting of single cells without the need for exogenous labels. Label-free microfluidics reduce the preparation time, reagents needed, and cost of conventional methods based on fluorescent or magnetic labels. Furthermore, these devices enable analysis of cell properties such as mechanical phenotype and dielectric parameters that cannot be characterized with traditional labels. Some of the most promising technologies for current and future development toward label-free, single-cell analysis and sorting include electronic sensors such as Coulter counters and electrical impedance cytometry; deformation analysis using optical traps and deformation cytometry; hydrodynamic sorting such as deterministic lateral displacement, inertial focusing, and microvortex trapping; and acoustic sorting using traveling or standing surface acoustic waves. These label-free microfluidic methods have been used to screen, sort, and analyze cells for a wide range of biomedical and clinical applications, including cell cycle monitoring, rapid complete blood counts, cancer diagnosis, metastatic progression monitoring, HIV and parasite detection, circulating tumor cell isolation, and point-of-care diagnostics. Because of the versatility of label-free methods for characterization and sorting, the low-cost nature of microfluidics, and the rapid prototyping capabilities of modern microfabrication, we expect this class of technology to continue to be an area of high research interest going forward. New developments in this field will contribute to the ongoing paradigm shift in cell analysis and sorting technologies toward label-free microfluidic devices, enabling new capabilities in biomedical research tools as well as clinical diagnostics. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices. © 2018 Wiley Periodicals, Inc.

Shotgun proteomic analysis of Emiliania huxleyi, a marine phytoplankton species of major biogeochemical importance.

PubMed

Jones, Bethan M; Edwards, Richard J; Skipp, Paul J; O'Connor, C David; Iglesias-Rodriguez, M Debora

2011-06-01

Emiliania huxleyi is a unicellular marine phytoplankton species known to play a significant role in global biogeochemistry. Through the dual roles of photosynthesis and production of calcium carbonate (calcification), carbon is transferred from the atmosphere to ocean sediments. Almost nothing is known about the molecular mechanisms that control calcification, a process that is tightly regulated within the cell. To initiate proteomic studies on this important and phylogenetically remote organism, we have devised efficient protein extraction protocols and developed a bioinformatics pipeline that allows the statistically robust assignment of proteins from MS/MS data using preexisting EST sequences. The bioinformatics tool, termed BUDAPEST (Bioinformatics Utility for Data Analysis of Proteomics using ESTs), is fully automated and was used to search against data generated from three strains. BUDAPEST increased the number of identifications over standard protein database searches from 37 to 99 proteins when data were amalgamated. Proteins involved in diverse cellular processes were uncovered. For example, experimental evidence was obtained for a novel type I polyketide synthase and for various photosystem components. The proteomic and bioinformatic approaches developed in this study are of wider applicability, particularly to the oceanographic community where genomic sequence data for species of interest are currently scarce.

Escherichia coli cell-free protein synthesis and isotope labeling of mammalian proteins.

PubMed

Terada, Takaho; Yokoyama, Shigeyuki

2015-01-01

This chapter describes the cell-free protein synthesis method, using an Escherichia coli cell extract. This is a cost-effective method for milligram-scale protein production and is particularly useful for the production of mammalian proteins, protein complexes, and membrane proteins that are difficult to synthesize by recombinant expression methods, using E. coli and eukaryotic cells. By adjusting the conditions of the cell-free method, zinc-binding proteins, disulfide-bonded proteins, ligand-bound proteins, etc., may also be produced. Stable isotope labeling of proteins can be accomplished by the cell-free method, simply by using stable isotope-labeled amino acid(s) in the cell-free reaction. Moreover, the cell-free protein synthesis method facilitates the avoidance of stable isotope scrambling and dilution over the recombinant expression methods and is therefore advantageous for amino acid-selective stable isotope labeling. Site-specific stable isotope labeling is also possible with a tRNA molecule specific to the UAG codon. By the cell-free protein synthesis method, coupled transcription-translation is performed from a plasmid vector or a PCR-amplified DNA fragment encoding the protein. A milligram quantity of protein can be produced with a milliliter-scale reaction solution in the dialysis mode. More than a thousand solution structures have been determined by NMR spectroscopy for uniformly labeled samples of human and mouse functional domain proteins, produced by the cell-free method. Here, we describe the practical aspects of mammalian protein production by the cell-free method for NMR spectroscopy. © 2015 Elsevier Inc. All rights reserved.

Labeling of indocyanine green with carrier-free iodine-123

DOEpatents

Ansari, Azizullah N.; Lambrecht, Richard M.; Redvanly, Carol S.; Wolf, Alfred P.

1976-01-01

The method of labeling indocyanine green (ICG) with carrier-free iodine-123 comprising the steps of condensing xenon-123 on crystals of ICG followed by permitting decay of the .sup.123 Xe a sufficient length of time to produce .sup.123 I-electronically excited ions and atoms which subsequently label ICG.

A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics.

PubMed

Van Oudenhove, Laurence; Devreese, Bart

2013-06-01

Proteomics has evolved substantially since its early days, some 20 years ago. In this mini-review, we aim to provide an overview of general methodologies and more recent developments in mass spectrometric approaches used for relative and absolute quantitation of proteins. Enhancement of sensitivity of the mass spectrometers as well as improved sample preparation and protein fractionation methods are resulting in a more comprehensive analysis of proteomes. We also document some upcoming trends for quantitative proteomics such as the use of label-free quantification methods. Hopefully, microbiologists will continue to explore proteomics as a tool in their research to understand the adaptation of microorganisms to their ever changing environment. We encourage them to incorporate some of the described new developments in mass spectrometry to facilitate their analyses and improve the general knowledge of the fascinating world of microorganisms.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

PubMed

Gunawardena, Harsha P; O'Brien, Jonathon; Wrobel, John A; Xie, Ling; Davies, Sherri R; Li, Shunqiang; Ellis, Matthew J; Qaqish, Bahjat F; Chen, Xian

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative

Phase sensitive spectral domain interferometry for label free biomolecular interaction analysis and biosensing applications

NASA Astrophysics Data System (ADS)

Chirvi, Sajal

Biomolecular interaction analysis (BIA) plays vital role in wide variety of fields, which include biomedical research, pharmaceutical industry, medical diagnostics, and biotechnology industry. Study and quantification of interactions between natural biomolecules (proteins, enzymes, DNA) and artificially synthesized molecules (drugs) is routinely done using various labeled and label-free BIA techniques. Labeled BIA (Chemiluminescence, Fluorescence, Radioactive) techniques suffer from steric hindrance of labels on interaction site, difficulty of attaching labels to molecules, higher cost and time of assay development. Label free techniques with real time detection capabilities have demonstrated advantages over traditional labeled techniques. The gold standard for label free BIA is surface Plasmon resonance (SPR) that detects and quantifies the changes in refractive index of the ligand-analyte complex molecule with high sensitivity. Although SPR is a highly sensitive BIA technique, it requires custom-made sensor chips and is not well suited for highly multiplexed BIA required in high throughput applications. Moreover implementation of SPR on various biosensing platforms is limited. In this research work spectral domain phase sensitive interferometry (SD-PSI) has been developed for label-free BIA and biosensing applications to address limitations of SPR and other label free techniques. One distinct advantage of SD-PSI compared to other label-free techniques is that it does not require use of custom fabricated biosensor substrates. Laboratory grade, off-the-shelf glass or plastic substrates of suitable thickness with proper surface functionalization are used as biosensor chips. SD-PSI is tested on four separate BIA and biosensing platforms, which include multi-well plate, flow cell, fiber probe with integrated optics and fiber tip biosensor. Sensitivity of 33 ng/ml for anti-IgG is achieved using multi-well platform. Principle of coherence multiplexing for multi

A Statistical Framework for Protein Quantitation in Bottom-Up MS-Based Proteomics

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

Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

2009-08-15

Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate themore » methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. Availability: The software has been made available in the opensource proteomics platform DAnTE (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu Supplementary information: Supplementary data are available at Bioinformatics online.« less

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins

COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA

PubMed Central

Wenger, Craig D.; Phanstiel, Douglas H.; Lee, M. Violet; Bailey, Derek J.; Coon, Joshua J.

2011-01-01

Here we present the Coon OMSSA Proteomic Analysis Software Suite (COMPASS): a free and open-source software pipeline for high-throughput analysis of proteomics data, designed around the Open Mass Spectrometry Search Algorithm. We detail a synergistic set of tools for protein database generation, spectral reduction, peptide false discovery rate analysis, peptide quantitation via isobaric labeling, protein parsimony and protein false discovery rate analysis, and protein quantitation. We strive for maximum ease of use, utilizing graphical user interfaces and working with data files in the original instrument vendor format. Results are stored in plain text comma-separated values files, which are easy to view and manipulate with a text editor or spreadsheet program. We illustrate the operation and efficacy of COMPASS through the use of two LC–MS/MS datasets. The first is a dataset of a highly annotated mixture of standard proteins and manually validated contaminants that exhibits the identification workflow. The second is a dataset of yeast peptides, labeled with isobaric stable isotope tags and mixed in known ratios, to demonstrate the quantitative workflow. For these two datasets, COMPASS performs equivalently or better than the current de facto standard, the Trans-Proteomic Pipeline. PMID:21298793

Label and label-free based surface-enhanced Raman scattering for pathogen bacteria detection: A review.

PubMed

Liu, Yu; Zhou, Haibo; Hu, Ziwei; Yu, Guangxia; Yang, Danting; Zhao, Jinshun

2017-08-15

Rapid, accurate detection of pathogen bacteria is a highly topical research area for the sake of food safety and public health. Surface-enhanced Raman scattering (SERS) is being considered as a powerful and attractive technique for pathogen bacteria detection, due to its sensitivity, high speed, comparatively low cost, multiplexing ability and portability. This contribution aims to give a comprehensive overview of SERS as a technique for rapid detection of pathogen bacteria based on label and label-free strategies. A brief tutorial on SERS is given first of all. Then we summarize the recent trends and developments of label and label-free based SERS applied to detection of pathogen bacteria, including the relatively complete interpretation of SERS spectra. In addition, multifunctional SERS platforms for pathogen bacteria in matrix are discussed as well. Furthermore, an outlook of the work done and a perspective on the future directions of SERS as a reliable tool for real-time pathogen bacteria detection are given. Copyright © 2017 Elsevier B.V. All rights reserved.

BBMerge – Accurate paired shotgun read merging via overlap

DOE PAGES

Bushnell, Brian; Rood, Jonathan; Singer, Esther

2017-10-26

Merging paired-end shotgun reads generated on high-throughput sequencing platforms can substantially improve various subsequent bioinformatics processes, including genome assembly, binning, mapping, annotation, and clustering for taxonomic analysis. With the inexorable growth of sequence data volume and CPU core counts, the speed and scalability of read-processing tools becomes ever-more important. The accuracy of shotgun read merging is crucial as well, as errors introduced by incorrect merging percolate through to reduce the quality of downstream analysis. Thus, we designed a new tool to maximize accuracy and minimize processing time, allowing the use of read merging on larger datasets, and in analyses highlymore » sensitive to errors. We present BBMerge, a new merging tool for paired-end shotgun sequence data. We benchmark BBMerge by comparison with eight other widely used merging tools, assessing speed, accuracy and scalability. Evaluations of both synthetic and real-world datasets demonstrate that BBMerge produces merged shotgun reads with greater accuracy and at higher speed than any existing merging tool examined. BBMerge also provides the ability to merge non-overlapping shotgun read pairs by using k-mer frequency information to assemble the unsequenced gap between reads, achieving a significantly higher merge rate while maintaining or increasing accuracy.« less

BBMerge – Accurate paired shotgun read merging via overlap

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

Bushnell, Brian; Rood, Jonathan; Singer, Esther

Merging paired-end shotgun reads generated on high-throughput sequencing platforms can substantially improve various subsequent bioinformatics processes, including genome assembly, binning, mapping, annotation, and clustering for taxonomic analysis. With the inexorable growth of sequence data volume and CPU core counts, the speed and scalability of read-processing tools becomes ever-more important. The accuracy of shotgun read merging is crucial as well, as errors introduced by incorrect merging percolate through to reduce the quality of downstream analysis. Thus, we designed a new tool to maximize accuracy and minimize processing time, allowing the use of read merging on larger datasets, and in analyses highlymore » sensitive to errors. We present BBMerge, a new merging tool for paired-end shotgun sequence data. We benchmark BBMerge by comparison with eight other widely used merging tools, assessing speed, accuracy and scalability. Evaluations of both synthetic and real-world datasets demonstrate that BBMerge produces merged shotgun reads with greater accuracy and at higher speed than any existing merging tool examined. BBMerge also provides the ability to merge non-overlapping shotgun read pairs by using k-mer frequency information to assemble the unsequenced gap between reads, achieving a significantly higher merge rate while maintaining or increasing accuracy.« less

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

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.

The Brain Proteome of the Ubiquitin Ligase Peli1 Knock-Out Mouse during Experimental Autoimmune Encephalomyelitis.

PubMed

Lereim, Ragnhild Reehorst; Oveland, Eystein; Xiao, Yichuan; Torkildsen, Øivind; Wergeland, Stig; Myhr, Kjell-Morten; Sun, Shao-Cong; Berven, Frode S

2016-09-01

The ubiquitin ligase Peli1 has previously been suggested as a potential treatment target in multiple sclerosis. In the multiple sclerosis disease model, experimental autoimmune encephalomyelitis, Peli1 knock-out led to less activated microglia and less inflammation in the central nervous system. Despite being important in microglia, Peli1 expression has also been detected in glial and neuronal cells. In the present study the overall brain proteomes of Peli1 knock-out mice and wild-type mice were compared prior to experimental autoimmune encephalomyelitis induction, at onset of the disease and at disease peak. Brain samples from the frontal hemisphere, peripheral from the extensive inflammatory foci, were analyzed using TMT-labeling of sample pools, and the discovered proteins were verified in individual mice using label-free proteomics. The greatest proteomic differences between Peli1 knock-out and wild-type mice were observed at the disease peak. In Peli1 knock-out a higher degree of antigen presentation, increased activity of adaptive and innate immune cells and alterations to proteins involved in iron metabolism were observed during experimental autoimmune encephalomyelitis. These results unravel global effects to the brain proteome when abrogating Peli1 expression, underlining the importance of Peli1 as a regulator of the immune response also peripheral to inflammatory foci during experimental autoimmune encephalomyelitis. The proteomics data is available in PRIDE with accession PXD003710.

Comparative Proteomic Analysis of Tolerance and Adaptation of Ethanologenic Saccharomyces cerevisiae to Furfural, a Lignocellulosic Inhibitory Compound▿ †

PubMed Central

Lin, Feng-Ming; Qiao, Bin; Yuan, Ying-Jin

2009-01-01

The molecular mechanism involved in tolerance and adaptation of ethanologenic Saccharomyces cerevisiae to inhibitors (such as furfural, acetic acid, and phenol) represented in lignocellulosic hydrolysate is still unclear. Here, 18O-labeling-aided shotgun comparative proteome analysis was applied to study the global protein expression profiles of S. cerevisiae under conditions of treatment of furfural compared with furfural-free fermentation profiles. Proteins involved in glucose fermentation and/or the tricarboxylic acid cycle were upregulated in cells treated with furfural compared with the control cells, while proteins involved in glycerol biosynthesis were downregulated. Differential levels of expression of alcohol dehydrogenases were observed. On the other hand, the levels of NADH, NAD+, and NADH/NAD+ were reduced whereas the levels of ATP and ADP were increased. These observations indicate that central carbon metabolism, levels of alcohol dehydrogenases, and the redox balance may be related to tolerance of ethanologenic yeast for and adaptation to furfural. Furthermore, proteins involved in stress response, including the unfolded protein response, oxidative stress, osmotic and salt stress, DNA damage and nutrient starvation, were differentially expressed, a finding that was validated by quantitative real-time reverse transcription-PCR to further confirm that the general stress responses are essential for cellular defense against furfural. These insights into the response of yeast to the presence of furfural will benefit the design and development of inhibitor-tolerant ethanologenic yeast by metabolic engineering or synthetic biology. PMID:19363068

Label-free electrical detection using carbon nanotube-based biosensors.

PubMed

Maehashi, Kenzo; Matsumoto, Kazuhiko

2009-01-01

Label-free detections of biomolecules have attracted great attention in a lot of life science fields such as genomics, clinical diagnosis and practical pharmacy. In this article, we reviewed amperometric and potentiometric biosensors based on carbon nanotubes (CNTs). In amperometric detections, CNT-modified electrodes were used as working electrodes to significantly enhance electroactive surface area. In contrast, the potentiometric biosensors were based on aptamer-modified CNT field-effect transistors (CNTFETs). Since aptamers are artificial oligonucleotides and thus are smaller than the Debye length, proteins can be detected with high sensitivity. In this review, we discussed on the technology, characteristics and developments for commercialization in label-free CNT-based biosensors.

Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa

PubMed Central

Campos, Alexandre; Turkina, Maria V.; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho

2018-01-01

Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa. The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds. PMID:29364843

Facile preparation of salivary extracellular vesicles for cancer proteomics

NASA Astrophysics Data System (ADS)

Sun, Yan; Xia, Zhijun; Shang, Zhi; Sun, Kaibo; Niu, Xiaomin; Qian, Liqiang; Fan, Liu-Yin; Cao, Cheng-Xi; Xiao, Hua

2016-04-01

Extracellular vesicles (EVs) are membrane surrounded structures released by cells, which have been increasingly recognized as mediators of intercellular communication. Recent reports indicate that EVs participate in important biological processes and could serve as potential source for cancer biomarkers. As an attractive EVs source with merit of non-invasiveness, human saliva is a unique medium for clinical diagnostics. Thus, we proposed a facile approach to prepare salivary extracellular vesicles (SEVs). Affinity chromatography column combined with filter system (ACCF) was developed to efficiently remove the high abundant proteins and viscous interferences of saliva. Protein profiling in the SEVs obtained by this strategy was compared with conventional centrifugation method, which demonstrated that about 70% more SEVs proteins could be revealed. To explore its utility for cancer proteomics, we analyzed the proteome of SEVs in lung cancer patients and normal controls. Shotgun proteomic analysis illustrated that 113 and 95 proteins have been identified in cancer group and control group, respectively. Among those 63 proteins that have been consistently discovered only in cancer group, 12 proteins are lung cancer related. Our results demonstrated that SEVs prepared through the developed strategy are valuable samples for proteomics and could serve as a promising liquid biopsy for cancer.

Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa.

PubMed

Domínguez-Pérez, Dany; Campos, Alexandre; Alexei Rodríguez, Armando; Turkina, Maria V; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho

2018-01-24

Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa . The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds.

Label-free optical resonant sensors for biochemical applications

NASA Astrophysics Data System (ADS)

Ciminelli, Caterina; Campanella, Clarissa Martina; Dell'Olio, Francesco; Campanella, Carlo Edoardo; Armenise, Mario Nicola

2013-03-01

For a number of years, the scientific community has been paying growing attention to the monitoring and enhancement of public health and the quality of life through the detection of all dangerous agents for the human body, including gases, proteins, virus, and bacterial agents. When these agents are detected through label-free biochemical sensors, the molecules are not modified structurally or functionally by adding fluorescent or radioactive dyes. This work focuses on label-free optical ring resonator-based configurations suited for bio-chemical sensing, highlighting their physical aspects and specific applications. Resonant wavelength shift and the modal splitting occurring when the analyte interacts with microresonant structures are the two major physical aspects analyzed in this paper. Competitive optical platforms proposed in the literature are also illustrated together with their properties and performance.

Proteomic profile of dormant Trichophyton Rubrum conidia

PubMed Central

Leng, Wenchuan; Liu, Tao; Li, Rui; Yang, Jian; Wei, Candong; Zhang, Wenliang; Jin, Qi

2008-01-01

Background Trichophyton rubrum is the most common dermatophyte causing fungal skin infections in humans. Asexual sporulation is an important means of propagation for T. rubrum, and conidia produced by this way are thought to be the primary cause of human infections. Despite their importance in pathogenesis, the conidia of T. rubrum remain understudied. We intend to intensively investigate the proteome of dormant T. rubrum conidia to characterize its molecular and cellular features and to enhance the development of novel therapeutic strategies. Results The proteome of T. rubrum conidia was analyzed by combining shotgun proteomics with sample prefractionation and multiple enzyme digestion. In total, 1026 proteins were identified. All identified proteins were compared to those in the NCBI non-redundant protein database, the eukaryotic orthologous groups database, and the gene ontology database to obtain functional annotation information. Functional classification revealed that the identified proteins covered nearly all major biological processes. Some proteins were spore specific and related to the survival and dispersal of T. rubrum conidia, and many proteins were important to conidial germination and response to environmental conditions. Conclusion Our results suggest that the proteome of T. rubrum conidia is considerably complex, and that the maintenance of conidial dormancy is an intricate and elaborate process. This data set provides the first global framework for the dormant T. rubrum conidia proteome and is a stepping stone on the way to further study of the molecular mechanisms of T. rubrum conidial germination and the maintenance of conidial dormancy. PMID:18578874

Current algorithmic solutions for peptide-based proteomics data generation and identification.

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Look away: arterial and venous intravascular embolisation following shotgun injury.

PubMed

Vedelago, John; Dick, Elizabeth; Thomas, Robert; Jones, Brynmor; Kirmi, Olga; Becker, Jennifer; Alavi, Afshin; Gedroyc, Wladyslaw

2014-01-01

We describe two cases of intravascular embolization of shotgun pellets found distant to the entry site of penetrating firearm injury. The cases demonstrate antegrade embolization of a shotgun pellet from neck to right middle cerebral artery, and antegrade followed by retrograde venous embolization through the left lower limb to pelvis. Radiologists and Trauma Physicians should be aware that post shotgun injury, the likelihood of an embolised shot pellet is increased compared to other types of firearm missile injury, and should therefore search away from the site of injury to find such missiles. Shotgun pellets may travel in an antegrade or a retrograde intravascular direction - both were seen in these cases - and may not be clinically obvious. This underscores the importance of a meticuluous search through all images, including CT scout images, for evidence of their presence.

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

Real-time label-free biosensing with integrated planar waveguide ring resonators

NASA Astrophysics Data System (ADS)

Sohlström, Hans; Gylfason, Kristinn B.; Hill, Daniel

2010-05-01

We review the use of planar integrated optical waveguide ring resonators for label free bio-sensing and present recent results from two European biosensor collaborations: SABIO and InTopSens. Planar waveguide ring resonators are attractive for label-free biosensing due to their small footprint, high Q-factors, and compatibility with on-chip optics and microfluidics. This enables integrated sensor arrays for compact labs-on-chip. One application of label-free sensor arrays is for point-of-care medical diagnostics. Bringing such powerful tools to the single medical practitioner is an important step towards personalized medicine, but requires addressing a number of issues: improving limit of detection, managing the influence of temperature, parallelization of the measurement for higher throughput and on-chip referencing, efficient light-coupling strategies to simplify alignment, and packaging of the optical chip and integration with microfluidics. From the SABIO project we report refractive index measurement and label-free biosensing in an 8-channel slotwaveguide ring resonator sensor array, within a compact cartridge with integrated microfluidics. The sensors show a volume sensing detection limit of 5 x 10-6 RIU and a surface sensing detection limit of 0.9 pg/mm2. From the InTopSens project we report early results on silicon-on-insulator racetrack resonators.

Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data

PubMed Central

Serang, Oliver; MacCoss, Michael J.; Noble, William Stafford

2010-01-01

The problem of identifying proteins from a shotgun proteomics experiment has not been definitively solved. Identifying the proteins in a sample requires ranking them, ideally with interpretable scores. In particular, “degenerate” peptides, which map to multiple proteins, have made such a ranking difficult to compute. The problem of computing posterior probabilities for the proteins, which can be interpreted as confidence in a protein’s presence, has been especially daunting. Previous approaches have either ignored the peptide degeneracy problem completely, addressed it by computing a heuristic set of proteins or heuristic posterior probabilities, or by estimating the posterior probabilities with sampling methods. We present a probabilistic model for protein identification in tandem mass spectrometry that recognizes peptide degeneracy. We then introduce graph-transforming algorithms that facilitate efficient computation of protein probabilities, even for large data sets. We evaluate our identification procedure on five different well-characterized data sets and demonstrate our ability to efficiently compute high-quality protein posteriors. PMID:20712337

Quantitative proteomic analysis of bacterial enzymes released in cheese during ripening.

PubMed

Jardin, Julien; Mollé, Daniel; Piot, Michel; Lortal, Sylvie; Gagnaire, Valérie

2012-04-02

Due to increasingly available bacterial genomes in databases, proteomic tools have recently been used to screen proteins expressed by micro-organisms in food in order to better understand their metabolism in situ. While the main objective is the systematic identification of proteins, the next step will be to bridge the gap between identification and quantification of these proteins. For that purpose, a new mass spectrometry-based approach was applied, using isobaric tagging reagent for quantitative proteomic analysis (iTRAQ), which are amine specific and yield labelled peptides identical in mass. Experimental Swiss-type cheeses were manufactured from microfiltered milk using Streptococcus thermophilus ITG ST20 and Lactobacillus helveticus ITG LH1 as lactic acid starters. At three ripening times (7, 20 and 69 days), cheese aqueous phases were extracted and enriched in bacterial proteins by fractionation. Each sample, standardised in protein amount prior to proteomic analyses, was: i) analysed by 2D-electrophoresis for qualitative analysis and ii) submitted to trypsinolysis, and labelled with specific iTRAQ tag, one per ripening time. The three labelled samples were mixed together and analysed by nano-LC coupled on-line with ESI-QTOF mass spectrometer. Thirty proteins, both from bacterial or bovine origin, were identified and efficiently quantified. The free bacterial proteins detected were enzymes from the central carbon metabolism as well as stress proteins. Depending on the protein considered, the quantity of these proteins in the cheese aqueous extract increased from 2.5 to 20 fold in concentration from day 7 to day 69 of ripening. Copyright © 2012 Elsevier B.V. All rights reserved.

Mass spectrometry-based proteomics: basic principles and emerging technologies and directions.

PubMed

Van Riper, Susan K; de Jong, Ebbing P; Carlis, John V; Griffin, Timothy J

2013-01-01

As the main catalytic and structural molecules within living systems, proteins are the most likely biomolecules to be affected by radiation exposure. Proteomics, the comprehensive characterization of proteins within complex biological samples, is therefore a research approach ideally suited to assess the effects of radiation exposure on cells and tissues. For comprehensive characterization of proteomes, an analytical platform capable of quantifying protein abundance, identifying post-translation modifications and revealing members of protein complexes on a system-wide level is necessary. Mass spectrometry (MS), coupled with technologies for sample fractionation and automated data analysis, provides such a versatile and powerful platform. In this chapter we offer a view on the current state of MS-proteomics, and focus on emerging technologies within three areas: (1) New instrumental methods; (2) New computational methods for peptide identification; and (3) Label-free quantification. These emerging technologies should be valuable for researchers seeking to better understand biological effects of radiation on living systems.

Comparative label-free LC-MS/MS analysis of colorectal adenocarcinoma and metastatic cells treated with 5-fluorouracil.

PubMed

Bauer, Kerry M; Lambert, Paul A; Hummon, Amanda B

2012-06-01

A label-free mass spectrometric strategy was used to examine the effect of 5-fluorouracil (5-FU) on the primary and metastatic colon carcinoma cell lines, SW480 and SW620, with and without treatment. 5-FU is the most common chemotherapeutic treatment for colon cancer. Pooled biological replicates were analyzed by nanoLC-MS/MS and protein quantification was determined via spectral counting. Phenotypic and proteomic changes were evident and often similar in both cell lines. The SW620 cells were more resistant to 5-FU treatment, with an IC(50) 2.7-fold higher than that for SW480. In addition, both cell lines showed pronounced abundance changes in pathways relating to antioxidative stress response and cell adhesion remodeling due to 5-FU treatment. For example, the detoxification enzyme NQO1 was increased with treatment in both cell lines, while disparate members of the peroxiredoxin family, PRDX2 or PRDX5 and PRDX6, were elevated with 5-FU exposure in either SW480 or SW620, respectively. Cell adhesion-associated proteins CTNNB1 and RhoA showed decreased expression with 5-FU treatment in both cell lines. The differential quantitative response in the proteomes of these patient-matched cell lines to drug treatment underscores the subtle molecular differences separating primary and metastatic cancer cells. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Concurrent Label-Free Mass Spectrometric Analysis of Dystrophin Isoform Dp427 and the Myofibrosis Marker Collagen in Crude Extracts from mdx-4cv Skeletal Muscles

PubMed Central

Murphy, Sandra; Zweyer, Margit; Mundegar, Rustam R.; Henry, Michael; Meleady, Paula; Swandulla, Dieter; Ohlendieck, Kay

2015-01-01

The full-length dystrophin protein isoform of 427 kDa (Dp427), the absence of which represents the principal abnormality in X-linked muscular dystrophy, is difficult to identify and characterize by routine proteomic screening approaches of crude tissue extracts. This is probably related to its large molecular size, its close association with the sarcolemmal membrane, and its existence within a heterogeneous glycoprotein complex. Here, we used a careful extraction procedure to isolate the total protein repertoire from normal versus dystrophic mdx-4cv skeletal muscles, in conjunction with label-free mass spectrometry, and successfully identified Dp427 by proteomic means. In contrast to a considerable number of previous comparative studies of the total skeletal muscle proteome, using whole tissue proteomics we show here for the first time that the reduced expression of this membrane cytoskeletal protein is the most significant alteration in dystrophinopathy. This agrees with the pathobiochemical concept that the almost complete absence of dystrophin is the main defect in Duchenne muscular dystrophy and that the mdx-4cv mouse model of dystrophinopathy exhibits only very few revertant fibers. Significant increases in collagens and associated fibrotic marker proteins, such as fibronectin, biglycan, asporin, decorin, prolargin, mimecan, and lumican were identified in dystrophin-deficient muscles. The up-regulation of collagen in mdx-4cv muscles was confirmed by immunofluorescence microscopy and immunoblotting. Thus, this is the first mass spectrometric study of crude tissue extracts that puts the proteomic identification of dystrophin in its proper pathophysiological context. PMID:28248273

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.

Entrance, exit, and reentrance of one shot with a shotgun.

PubMed

Gulmann, C; Hougen, H P

1999-03-01

The case being reported is one of a homicidal shotgun fatality with an unusual wound pattern. A 34-year-old man was shot at close range with a 12-gauge shotgun armed with No. 5 birdshot ammunition. The shot entered the left axillary region, exited through the left infraclavicular region, and thereafter penetrated the left side of the neck, causing tearing of the left common carotid artery and the right internal carotid artery. The entrance wound in the axilla was larger than the other wounds, and before autopsy it was believed that the shotgun had been fired twice, causing one wound in the neck and one wound perforating the infraclavicular region and exiting through the left axillary region. Thus, this case shows that unusual wound patterns in shotgun fatalities can easily lead to incorrect assumptions with regard to number and direction of shots fired unless thorough investigation is carried out postmortem.

Hybrid label-free multiphoton and optoacoustic microscopy (MPOM)

NASA Astrophysics Data System (ADS)

Soliman, Dominik; Tserevelakis, George J.; Omar, Murad; Ntziachristos, Vasilis

2015-07-01

Many biological applications require a simultaneous observation of different anatomical features. However, unless potentially harmful staining of the specimens is employed, individual microscopy techniques do generally not provide multi-contrast capabilities. We present a hybrid microscope integrating optoacoustic microscopy and multiphoton microscopy, including second-harmonic generation, into a single device. This combined multiphoton and optoacoustic microscope (MPOM) offers visualization of a broad range of structures by employing different contrast mechanisms and at the same time enables pure label-free imaging of biological systems. We investigate the relative performance of the two microscopy modalities and demonstrate their multi-contrast abilities through the label-free imaging of a zebrafish larva ex vivo, simultaneously visualizing muscles and pigments. This hybrid microscopy application bears great potential for developmental biology studies, enabling more comprehensive information to be obtained from biological specimens without the necessity of staining.

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

PubMed Central

Szymanski, Witold G.; Kierszniowska, Sylwia; Schulze, Waltraud X.

2013-01-01

Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling processes. Extracting sterol-enriched membrane microdomains from plant cells for proteomic analysis is a difficult task mainly due to multiple preparation steps and sources for contaminations from other cellular compartments. The plasma membrane constitutes only about 5-20% of all the membranes in a plant cell, and therefore isolation of highly purified plasma membrane fraction is challenging. A frequently used method involves aqueous two-phase partitioning in polyethylene glycol and dextran, which yields plasma membrane vesicles with a purity of 95% 1. Sterol-rich membrane microdomains within the plasma membrane are insoluble upon treatment with cold nonionic detergents at alkaline pH. This detergent-resistant membrane fraction can be separated from the bulk plasma membrane by ultracentrifugation in a sucrose gradient 2. Subsequently, proteins can be extracted from the low density band of the sucrose gradient by methanol/chloroform precipitation. Extracted protein will then be trypsin digested, desalted and finally analyzed by LC-MS/MS. Our extraction protocol for sterol-rich microdomains is optimized for the preparation of clean detergent-resistant membrane fractions from Arabidopsis thaliana cell cultures. We use full metabolic labeling of Arabidopsis thaliana suspension cell cultures with K15NO3 as the only nitrogen source for quantitative comparative proteomic studies following biological treatment of interest 3. By mixing equal ratios of labeled and unlabeled cell cultures for joint protein extraction the influence of preparation steps on final quantitative result is kept at a minimum. Also loss of material during extraction will affect both control and treatment samples in the same way, and therefore the ratio of light and heave peptide will remain constant. In the proposed method either labeled or unlabeled

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.

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

High-throughput screening based on label-free detection of small molecule microarrays

NASA Astrophysics Data System (ADS)

Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong

2017-02-01

Based on small-molecule microarrays (SMMs) and oblique-incidence reflectivity difference (OI-RD) scanner, we have developed a novel high-throughput drug preliminary screening platform based on label-free monitoring of direct interactions between target proteins and immobilized small molecules. The screening platform is especially attractive for screening compounds against targets of unknown function and/or structure that are not compatible with functional assay development. In this screening platform, OI-RD scanner serves as a label-free detection instrument which is able to monitor about 15,000 biomolecular interactions in a single experiment without the need to label any biomolecule. Besides, SMMs serves as a novel format for high-throughput screening by immobilization of tens of thousands of different compounds on a single phenyl-isocyanate functionalized glass slide. Based on the high-throughput screening platform, we sequentially screened five target proteins (purified target proteins or cell lysate containing target protein) in high-throughput and label-free mode. We found hits for respective target protein and the inhibition effects for some hits were confirmed by following functional assays. Compared to traditional high-throughput screening assay, the novel high-throughput screening platform has many advantages, including minimal sample consumption, minimal distortion of interactions through label-free detection, multi-target screening analysis, which has a great potential to be a complementary screening platform in the field of drug discovery.

Label-free DNA imaging in vivo with stimulated Raman scattering microscopy

DOE PAGES

Lu, Fa-Ke; Basu, Srinjan; Igras, Vivien; ...

2015-08-31

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based onmore » changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Moreover, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. In conclusion, our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time.« less

Label-free DNA imaging in vivo with stimulated Raman scattering microscopy

PubMed Central

Lu, Fa-Ke; Basu, Srinjan; Igras, Vivien; Hoang, Mai P.; Ji, Minbiao; Fu, Dan; Holtom, Gary R.; Neel, Victor A.; Freudiger, Christian W.; Fisher, David E.; Xie, X. Sunney

2015-01-01

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based on changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Furthermore, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. Our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time. PMID:26324899

Label-free and live cell imaging by interferometric scattering microscopy.

PubMed

Park, Jin-Sung; Lee, Il-Buem; Moon, Hyeon-Min; Joo, Jong-Hyeon; Kim, Kyoung-Hoon; Hong, Seok-Cheol; Cho, Minhaeng

2018-03-14

Despite recent remarkable advances in microscopic techniques, it still remains very challenging to directly observe the complex structure of cytoplasmic organelles in live cells without a fluorescent label. Here we report label-free and live-cell imaging of mammalian cell, Escherischia coli , and yeast, using interferometric scattering microscopy, which reveals the underlying structures of a variety of cytoplasmic organelles as well as the underside structure of the cells. The contact areas of the cells attached onto a glass substrate, e.g. , focal adhesions and filopodia, are clearly discernible. We also found a variety of fringe-like features in the cytoplasmic area, which may reflect the folded structures of cytoplasmic organelles. We thus anticipate that the label-free interferometric scattering microscopy can be used as a powerful tool to shed interferometric light on in vivo structures and dynamics of various intracellular phenomena.

An Integrated Proteomics/Transcriptomics Approach Points to Oxygen as the Main Electron Sink for Methanol Metabolism in Methylotenera mobilis▿†

PubMed Central

Beck, David A. C.; Hendrickson, Erik L.; Vorobev, Alexey; Wang, Tiansong; Lim, Sujung; Kalyuzhnaya, Marina G.; Lidstrom, Mary E.; Hackett, Murray; Chistoserdova, Ludmila

2011-01-01

Methylotenera species, unlike their close relatives in the genera Methylophilus, Methylobacillus, and Methylovorus, neither exhibit the activity of methanol dehydrogenase nor possess mxaFI genes encoding this enzyme, yet they are able to grow on methanol. In this work, we integrated a genome-wide proteomics approach, shotgun proteomics, and a genome-wide transcriptomics approach, shotgun transcriptome sequencing (RNA-seq), of Methylotenera mobilis JLW8 to identify genes and enzymes potentially involved in methanol oxidation, with special attention to alternative nitrogen sources, to address the question of whether nitrate could play a role as an electron acceptor in place of oxygen. Both proteomics and transcriptomics identified a limited number of genes and enzymes specifically responding to methanol. This set includes genes involved in oxidative stress response systems, a number of oxidoreductases, including XoxF-type alcohol dehydrogenases, a type II secretion system, and proteins without a predicted function. Nitrate stimulated expression of some genes in assimilatory nitrate reduction and denitrification pathways, while ammonium downregulated some of the nitrogen metabolism genes. However, none of these genes appeared to respond to methanol, which suggests that oxygen may be the main electron sink during growth on methanol. This study identifies initial targets for future focused physiological studies, including mutant analysis, which will provide further details into this novel process. PMID:21764938

Proteomic and transcriptional analysis of Lactobacillus johnsonii PF01 during bile salt exposure by iTRAQ shotgun proteomics and quantitative RT-PCR.

PubMed

Lee, Ji Yoon; Pajarillo, Edward Alain B; Kim, Min Jeong; Chae, Jong Pyo; Kang, Dae-Kyung

2013-01-04

Lactobacillus johnsonii PF01 has been reported to be highly resistant to bile, a key property of probiotic microorganisms. Here, we examine the nature of the bile-salt tolerance of L. johnsonii PF01. Growth inhibition and surface morphology and physiology aberrations were observed after overnight exposure to bile stress. Quantitative proteomic profiles using iTRAQ-LC-MS/MS technology identified 8307 peptides from both untreated PF01 cells and those exposed to 0.1%, 0.2%, and 0.3% bile salts. Some 215 proteins exhibited changed levels in response to bile stress; of these, levels of 94 peptides increased while those of 121 decreased. These were classified into the following categories: stress responses, cell division, transcription, translation, nucleotide metabolism, carbohydrate transport and metabolism, cell wall biosynthesis, and amino acid biosynthesis, and 16 of unidentified function. Analysis of the mRNA expression of selected genes by quantitative reverse transcriptase-PCR verified the proteomic data. Both proteomic and mRNA data provided evidence for increased phosphotransferase activity and cell wall biosynthesis. In addition, three bile salt hydrolases were significantly upregulated by bile exposure. These findings provide a basis for future evaluations of the tolerance of potential probiotic strains toward the various gastrointestinal challenges, including bile stress.

Preprocessing Significantly Improves the Peptide/Protein Identification Sensitivity of High-resolution Isobarically Labeled Tandem Mass Spectrometry Data*

PubMed Central

Sheng, Quanhu; Li, Rongxia; Dai, Jie; Li, Qingrun; Su, Zhiduan; Guo, Yan; Li, Chen; Shyr, Yu; Zeng, Rong

2015-01-01

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994. PMID:25435543

Nanoliter-Scale Oil-Air-Droplet Chip-Based Single Cell Proteomic Analysis.

PubMed

Li, Zi-Yi; Huang, Min; Wang, Xiu-Kun; Zhu, Ying; Li, Jin-Song; Wong, Catherine C L; Fang, Qun

2018-04-17

Single cell proteomic analysis provides crucial information on cellular heterogeneity in biological systems. Herein, we describe a nanoliter-scale oil-air-droplet (OAD) chip for achieving multistep complex sample pretreatment and injection for single cell proteomic analysis in the shotgun mode. By using miniaturized stationary droplet microreaction and manipulation techniques, our system allows all sample pretreatment and injection procedures to be performed in a nanoliter-scale droplet with minimum sample loss and a high sample injection efficiency (>99%), thus substantially increasing the analytical sensitivity for single cell samples. We applied the present system in the proteomic analysis of 100 ± 10, 50 ± 5, 10, and 1 HeLa cell(s), and protein IDs of 1360, 612, 192, and 51 were identified, respectively. The OAD chip-based system was further applied in single mouse oocyte analysis, with 355 protein IDs identified at the single oocyte level, which demonstrated its special advantages of high enrichment of sequence coverage, hydrophobic proteins, and enzymatic digestion efficiency over the traditional in-tube system.

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

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.

Phosphatidylinositol 3,4,5-trisphosphate activity probes for the labeling and proteomic characterization of protein binding partners.

PubMed

Rowland, Meng M; Bostic, Heidi E; Gong, Denghuang; Speers, Anna E; Lucas, Nathan; Cho, Wonhwa; Cravatt, Benjamin F; Best, Michael D

2011-12-27

Phosphatidylinositol polyphosphate lipids, such as phosphatidylinositol 3,4,5-trisphosphate [PI(3,4,5)P₃], regulate critical biological processes, many of which are aberrant in disease. These lipids often act as site-specific ligands in interactions that enforce membrane association of protein binding partners. Herein, we describe the development of bifunctional activity probes corresponding to the headgroup of PI(3,4,5)P₃ that are effective for identifying and characterizing protein binding partners from complex samples, namely cancer cell extracts. These probes contain both a photoaffinity tag for covalent labeling of target proteins and a secondary handle for subsequent detection or manipulation of labeled proteins. Probes bearing different secondary tags were exploited, either by direct attachment of a fluorescent dye for optical detection or by using an alkyne that can be derivatized after protein labeling via click chemistry. First, we describe the design and modular synthetic strategy used to generate multiple probes with different reporter tags of use for characterizing probe-labeled proteins. Next, we report initial labeling studies using purified protein, the PH domain of Akt, in which probes were found to label this target, as judged by in-gel detection. Furthermore, protein labeling was abrogated by controls including competition with an unlabeled PI(3,4,5)P₃ headgroup analogue as well as through protein denaturation, indicating specific labeling. In addition, probes featuring linkers of different lengths between the PI(3,4,5)P₃ headgroup and photoaffinity tag led to variations in protein labeling, indicating that a shorter linker was more effective in this case. Finally, proteomic labeling studies were performed using cell extracts; labeled proteins were observed by in-gel detection and characterized using postlabeling with biotin, affinity chromatography, and identification via tandem mass spectrometry. These studies yielded a total of 265

Label-free quantitative secretome analysis of Xanthomonas oryzae pv. oryzae highlights the involvement of a novel cysteine protease in its pathogenicity.

PubMed

Wang, Yiming; Gupta, Ravi; Song, Wei; Huh, Hyun-Hye; Lee, So Eui; Wu, Jingni; Agrawal, Ganesh Kumar; Rakwal, Randeep; Kang, Kyu Young; Park, Sang-Ryeol; Kim, Sun Tae

2017-10-03

Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most devastating diseases resulting in a huge loss of the total rice productivity. The initial interaction between rice and Xoo takes place in the host apoplast and is mediated primarily by secretion of various proteins from both partners. Yet, such secretory proteins remain to be largely identified and characterized. This study employed a label-free quantitative proteomics approach and identified 404 and 323 Xoo-secreted proteins from in vitro suspension-cultured cells and in planta systems, respectively. Gene Ontology analysis showed their involvement primarily in catalytic, transporter, and ATPase activities. Of a particular interest was a Xoo cysteine protease (XoCP), which showed dramatic increase in its protein abundance in planta upon Xoo interaction with a susceptible rice cultivar. Knock-out mutants of XoCP showed reduced pathogenicity on rice, highlighting its potential involvement in Xoo virulence. Besides, a parallel analysis of in planta rice-secreted proteins resulted in identification of 186 secretory proteins mainly associated with the catalytic, antioxidant, and electron carrier activities. Identified secretory proteins were exploited to shed light on their possible role in the rice-Xoo interaction, and that further deepen our understanding of such interaction. Xanthomonas oryzae pv. oryzae (Xoo), causative agent of bacterial blight disease, results in a huge loss of the total rice productivity. Using a label-free quantitative proteomics approach, we identified 727 Xoo- and 186 rice-secreted proteins. Functional annotation showed Xoo secreted proteins were mainly associated with the catalytic, transporter, and ATPase activities while the rice secreted proteins were mainly associated with the catalytic, antioxidant, and electron carrier activities. A novel Xoo cysteine protease (XoCP) was identified, showing dramatic increase in its protein abundance in planta upon Xoo

27 CFR 478.39 - Assembly of semiautomatic rifles or shotguns.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2011-04-01 2010-04-01 true Assembly of semiautomatic... AMMUNITION Administrative and Miscellaneous Provisions § 478.39 Assembly of semiautomatic rifles or shotguns.... (b) The provisions of this section shall not apply to: (1) The assembly of such rifle or shotgun for...

27 CFR 478.39 - Assembly of semiautomatic rifles or shotguns.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2014-04-01 2014-04-01 false Assembly of semiautomatic... AMMUNITION Administrative and Miscellaneous Provisions § 478.39 Assembly of semiautomatic rifles or shotguns.... (b) The provisions of this section shall not apply to: (1) The assembly of such rifle or shotgun for...

27 CFR 478.39 - Assembly of semiautomatic rifles or shotguns.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2010-04-01 2010-04-01 false Assembly of semiautomatic... AMMUNITION Administrative and Miscellaneous Provisions § 478.39 Assembly of semiautomatic rifles or shotguns.... (b) The provisions of this section shall not apply to: (1) The assembly of such rifle or shotgun for...

27 CFR 478.39 - Assembly of semiautomatic rifles or shotguns.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2013-04-01 2013-04-01 false Assembly of semiautomatic... AMMUNITION Administrative and Miscellaneous Provisions § 478.39 Assembly of semiautomatic rifles or shotguns.... (b) The provisions of this section shall not apply to: (1) The assembly of such rifle or shotgun for...

27 CFR 478.39 - Assembly of semiautomatic rifles or shotguns.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2012-04-01 2010-04-01 true Assembly of semiautomatic... AMMUNITION Administrative and Miscellaneous Provisions § 478.39 Assembly of semiautomatic rifles or shotguns.... (b) The provisions of this section shall not apply to: (1) The assembly of such rifle or shotgun for...

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.

OAM-labeled free-space optical flow routing.

PubMed

Gao, Shecheng; Lei, Ting; Li, Yangjin; Yuan, Yangsheng; Xie, Zhenwei; Li, Zhaohui; Yuan, Xiaocong

2016-09-19

Space-division multiplexing allows unprecedented scaling of bandwidth density for optical communication. Routing spatial channels among transmission ports is critical for future scalable optical network, however, there is still no characteristic parameter to label the overlapped optical carriers. Here we propose a free-space optical flow routing (OFR) scheme by using optical orbital angular moment (OAM) states to label optical flows and simultaneously steer each flow according to their OAM states. With an OAM multiplexer and a reconfigurable OAM demultiplexer, massive individual optical flows can be routed to the demanded optical ports. In the routing process, the OAM beams act as data carriers at the same time their topological charges act as each carrier's labels. Using this scheme, we experimentally demonstrate switching, multicasting and filtering network functions by simultaneously steer 10 input optical flows on demand to 10 output ports. The demonstration of data-carrying OFR with nonreturn-to-zero signals shows that this process enables synchronous processing of massive spatial channels and flexible optical network.

Label-free nano-biosensing on the road to tuberculosis detection.

PubMed

Golichenari, Behrouz; Velonia, Kelly; Nosrati, Rahim; Nezami, Alireza; Farokhi-Fard, Aref; Abnous, Khalil; Behravan, Javad; Tsatsakis, Aristidis M

2018-08-15

Tuberculosis, an ailment caused by the bacterium Mycobacterium tuberculosis (Mtb) complex, is one of the catastrophic transmittable diseases that affect human. Reports published by WHO indicate that in 2017 about 6.3 million people progressed to TB and 53 million TB patients died from 2000 to 2016. Therefore, early diagnosis of the disease is of great importance for global health care programs. Common diagnostics like the traditional PPD test and antibody-assisted assays suffer the lack of sensitivity, long processing time and cumbersome post-test proceedings. These shortcomings restrict their use and encourage innovations in TB diagnostics. In recent years, the biosensor concept opened up new horizons in sensitive and fast detection of the disease, reducing the interval time between sampling and diagnostic result. Among new diagnostics, label-free nano-biosensors are highly promising for sensitive and accessible detection of tuberculosis. Various specific label-free nano-biosensors have been recently reported detecting the whole cell of M. tuberculosis, mycobacterial proteins and IFN-γ as crucial markers in early diagnosis of TB. This article provides a focused overview on nanomaterial-based label-free biosensors for tuberculosis detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Attached and planktonic Listeria monocytogenes global proteomic responses and associated influence of strain genetics and temperature.

PubMed

Mata, Marcia M; da Silva, Wladimir P; Wilson, Richard; Lowe, Edwin; Bowman, John P

2015-02-06

Contamination of industrial and domestic food usage environments by the attachement of bacterial food-borne pathogen Listeria monocytogenes has public health and economic implications. Comprehensive proteomics experiments using label-free liquid chromatography/tandem mass spectrometry were used to compare the proteomes of two different L. monocytogenes strains (Siliken_1/2c and F2365_4b), which show very different capacities to attach to surfaces. Growth temperature and strain type were highly influential on the proteomes in both attached and planktonic cells. On the basis of the proteomic data, it is highly unlikely that specific surface proteins play a direct role in adherence to inanimate surfaces. Instead, strain-dependent responses related to cell envelope polymer biosynthesis and stress response regulation likely contribute to a different ability to attach and also to survive external stressors. Collectively, the divergent proteome-level responses observed define strain- and growth-temperature-dependent differences relevant to attachment efficacy, highlight relevant proteins involved in stress protection in attached cells, and suggest that strain differences and growth conditions are important in relation to environmental persistence.

Proteomic Characterization and Comparison of Malaysian Tropidolaemus wagleri and Cryptelytrops purpureomaculatus Venom Using Shotgun-Proteomics.

PubMed

Zainal Abidin, Syafiq Asnawi; Rajadurai, Pathmanathan; Chowdhury, Md Ezharul Hoque; Ahmad Rusmili, Muhamad Rusdi; Othman, Iekhsan; Naidu, Rakesh

2016-10-18

Tropidolaemus wagleri and Cryptelytrops purpureomaculatus are venomous pit viper species commonly found in Malaysia. Tandem mass spectrometry analysis of the crude venoms has detected different proteins in T. wagleri and C. purpureomaculatus . They were classified into 13 venom protein families consisting of enzymatic and nonenzymatic proteins. Enzymatic families detected in T. wagleri and C. purpureomaculatus venom were snake venom metalloproteinase, phospholipase A₂, ʟ-amino acid oxidase, serine proteases, 5'-nucleotidase, phosphodiesterase, and phospholipase B. In addition, glutaminyl cyclotransferase was detected in C. purpureomaculatus . C-type lectin-like proteins were common nonenzymatic components in both species. Waglerin was present and unique to T. wagleri -it was not in C. purpureomaculatus venom. In contrast, cysteine-rich secretory protein, bradykinin-potentiating peptide, and C-type natriuretic peptide were present in C. purpureomaculatus venom. Composition of the venom proteome of T. wagleri and C. purpureomaculatus provides useful information to guide production of effective antivenom and identification of proteins with potential therapeutic applications.

Proteomic Characterization and Comparison of Malaysian Tropidolaemus wagleri and Cryptelytrops purpureomaculatus Venom Using Shotgun-Proteomics

PubMed Central

Zainal Abidin, Syafiq Asnawi; Rajadurai, Pathmanathan; Chowdhury, Md Ezharul Hoque; Ahmad Rusmili, Muhamad Rusdi; Othman, Iekhsan; Naidu, Rakesh

2016-01-01

Tropidolaemus wagleri and Cryptelytrops purpureomaculatus are venomous pit viper species commonly found in Malaysia. Tandem mass spectrometry analysis of the crude venoms has detected different proteins in T. wagleri and C. purpureomaculatus. They were classified into 13 venom protein families consisting of enzymatic and nonenzymatic proteins. Enzymatic families detected in T. wagleri and C. purpureomaculatus venom were snake venom metalloproteinase, phospholipase A2, l-amino acid oxidase, serine proteases, 5′-nucleotidase, phosphodiesterase, and phospholipase B. In addition, glutaminyl cyclotransferase was detected in C. purpureomaculatus. C-type lectin-like proteins were common nonenzymatic components in both species. Waglerin was present and unique to T. wagleri—it was not in C. purpureomaculatus venom. In contrast, cysteine-rich secretory protein, bradykinin-potentiating peptide, and C-type natriuretic peptide were present in C. purpureomaculatus venom. Composition of the venom proteome of T. wagleri and C. purpureomaculatus provides useful information to guide production of effective antivenom and identification of proteins with potential therapeutic applications. PMID:27763534

Label free detection of phospholipids by infrared absorption spectroscopy

NASA Astrophysics Data System (ADS)

Ahmed, Tahsin; Foster, Erick; Vigil, Genevieve; Khan, Aamir A.; Bohn, Paul; Howard, Scott S.

2014-08-01

We present our study on compact, label-free dissolved lipid sensing by combining capillary electrophoresis separation in a PDMS microfluidic chip online with mid-infrared (MIR) absorption spectroscopy for biomarker detection. On-chip capillary electrophoresis is used to separate the biomarkers without introducing any extrinsic contrast agent, which reduces both cost and complexity. The label free biomarker detection could be done by interrogating separated biomarkers in the channel by MIR absorption spectroscopy. Phospholipids biomarkers of degenerative neurological, kidney, and bone diseases are detectable using this label free technique. These phospholipids exhibit strong absorption resonances in the MIR and are present in biofluids including urine, blood plasma, and cerebrospinal fluid. MIR spectroscopy of a 12-carbon chain phosphatidic acid (PA) (1,2-dilauroyl-snglycero- 3-phosphate (sodium salt)) dissolved in N-methylformamide, exhibits a strong amide peak near wavenumber 1660 cm-1 (wavelength 6 μm), arising from the phosphate headgroup vibrations within a low-loss window of the solvent. PA has a similar structure to many important phospholipids molecules like phosphatidylcholine (PC), phosphatidylinositol (PI), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and phosphatidylserine (PS), making it an ideal molecule for initial proof-of-concept studies. This newly proposed detection technique can lead us to minimal sample preparation and is capable of identifying several biomarkers from the same sample simultaneously.

Label-free isolation of circulating tumor cells in microfluidic devices: Current research and perspectives.

PubMed

Cima, Igor; Wen Yee, Chay; Iliescu, Florina S; Phyo, Wai Min; Lim, Kiat Hon; Iliescu, Ciprian; Tan, Min Han

2013-01-01

This review will cover the recent advances in label-free approaches to isolate and manipulate circulating tumor cells (CTCs). In essence, label-free approaches do not rely on antibodies or biological markers for labeling the cells of interest, but enrich them using the differential physical properties intrinsic to cancer and blood cells. We will discuss technologies that isolate cells based on their biomechanical and electrical properties. Label-free approaches to analyze CTCs have been recently invoked as a valid alternative to "marker-based" techniques, because classical epithelial and tumor markers are lost on some CTC populations and there is no comprehensive phenotypic definition for CTCs. We will highlight the advantages and drawbacks of these technologies and the status on their implementation in the clinics.

Comparative proteomic analysis of the aging soleus and extensor digitorum longus rat muscles using TMT labeling and mass spectrometry

PubMed Central

Chaves, Daniela F. S.; Carvalho, Paulo C.; Lima, Diogo B.; Nicastro, Humberto; Lorenzetti, Fábio M.; Filho, Mário S.; Hirabara, Sandro M.; Alves, Paulo H. M.; Moresco, James J.; Yates, John R.; Lancha, Antonio H.

2013-01-01

Sarcopenia describes an age-related decline in skeletal muscle mass, strength, and function that ultimately impairs metabolism, leads to poor balance, frequent falling, limited mobility, and a reduction in quality of life. Here we investigate the pathogenesis of sarcopenia through a proteomic shotgun approach. Briefly, we employed tandem mass tags (TMT) to quantitate and compare the protein profiles obtained from young versus old rat slow-twitch type of muscle (soleus) and a fast-twitch type of muscle (extensor digitorum longus, EDL). Our results disclose 3452 and 1848 proteins identified from soleus and EDL muscles samples of which 78 and 174 were found to be differentially expressed, respectively. In general, most of the proteins were structural related, involved in energy metabolism, oxidative stress, detoxification, or transport. Aging affected soleus and EDL muscles differently and several proteins were regulated in opposite ways. For example, pyruvate kinase had its expression and activity different in both soleus and EDL muscles. We were able to verify with existing literature many of our differentially expressed proteins as candidate aging biomarkers, and most importantly, disclose several new candidate biomarkers such as the glioblastoma amplified sequence (GAS), zero beta-globin, and prolargin. PMID:24001182

Comparative proteomic analysis of the aging soleus and extensor digitorum longus rat muscles using TMT labeling and mass spectrometry.

PubMed

Chaves, Daniela F S; Carvalho, Paulo C; Lima, Diogo B; Nicastro, Humberto; Lorenzeti, Fábio M; Siqueira-Filho, Mário; Hirabara, Sandro M; Alves, Paulo H M; Moresco, James J; Yates, John R; Lancha, Antonio H

2013-10-04

Sarcopenia describes an age-related decline in skeletal muscle mass, strength, and function that ultimately impairs metabolism and leads to poor balance, frequent falling, limited mobility, and a reduction in quality of life. Here we investigate the pathogenesis of sarcopenia through a proteomic shotgun approach. In brief, we employed tandem mass tags to quantitate and compare the protein profiles obtained from young versus old rat slow-twitch type of muscle (soleus) and a fast-twitch type of muscle (extensor digitorum longus, EDL). Our results disclose 3452 and 1848 proteins identified from soleus and EDL muscles samples, of which 78 and 174 were found to be differentially expressed, respectively. In general, most of the proteins were structural related and involved in energy metabolism, oxidative stress, detoxification, or transport. Aging affected soleus and EDL muscles differently, and several proteins were regulated in opposite ways. For example, pyruvate kinase had its expression and activity different in both soleus and EDL muscles. We were able to verify with existing literature many of our differentially expressed proteins as candidate aging biomarkers and, most importantly, disclose several new candidate biomarkers such as the glioblastoma amplified sequence, zero β-globin, and prolargin.

Trauma-associated Human Neutrophil Alterations Revealed by Comparative Proteomics Profiling

PubMed Central

Zhou, Jian-Ying; Krovvidi, Ravi K.; Gao, Yuqian; Gao, Hong; Petritis, Brianne O.; De, Asit; Miller-Graziano, Carol; Bankey, Paul E.; Petyuk, Vladislav A.; Nicora, Carrie D.; Clauss, Therese R; Moore, Ronald J.; Shi, Tujin; Brown, Joseph N.; Kaushal, Amit; Xiao, Wenzhong; Davis, Ronald W.; Maier, Ronald V.; Tompkins, Ronald G.; Qian, Wei-Jun; Camp, David G.; Smith, Richard D.

2013-01-01

PURPOSE Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown. EXPERIMENTAL DESIGN We applied 2D-LC-MS/MS based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls. RESULTS A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways. CONCLUSIONS AND CLINICAL RELEVANCE Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs. PMID:23589343

Using PeptideAtlas, SRMAtlas and PASSEL – Comprehensive Resources for discovery and targeted proteomics

PubMed Central

Kusebauch, Ulrike; Deutsch, Eric W.; Campbell, David S.; Sun, Zhi; Farrah, Terry; Moritz, Robert L.

2014-01-01

PeptideAtlas, SRMAtlas and PASSEL are web-accessible resources to support discovery and targeted proteomics research. PeptideAtlas is a multi-species compendium of shotgun proteomic data provided by the scientific community, SRMAtlas is a resource of high-quality, complete proteome SRM assays generated in a consistent manner for the targeted identification and quantification of proteins, and PASSEL is a repository that compiles and represents selected reaction monitoring data, all in an easy to use interface. The databases are generated from native mass spectrometry data files that are analyzed in a standardized manner including statistical validation of the results. Each resource offers search functionalities and can be queried by user defined constraints; the query results are provided in tables or are graphically displayed. PeptideAtlas, SRMAtlas and PASSEL are publicly available freely via the website http://www.peptideatlas.org. In this protocol, we describe the use of these resources, we highlight how to submit, search, collate and download data. PMID:24939129

Quantitative Proteomic Analysis of Mouse Embryonic Fibroblasts and Induced Pluripotent Stem Cells Using 16O /18O labeling

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

Huang, Xin; Tian, Changhai; Liu, Miao

2012-04-06

Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. Using thismore » platform a total of 2,481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1) and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.« less

Microchannel DNA Sequencing by End-Labelled Free Solution Electrophoresis

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

Barron, A.

2005-09-29

The further development of End-Labeled Free-Solution Electrophoresis will greatly simplify DNA separation and sequencing on microfluidic devices. The development and optimization of drag-tags is critical to the success of this research.

ProteinInferencer: Confident protein identification and multiple experiment comparison for large scale proteomics projects.

PubMed

Zhang, Yaoyang; Xu, Tao; Shan, Bing; Hart, Jonathan; Aslanian, Aaron; Han, Xuemei; Zong, Nobel; Li, Haomin; Choi, Howard; Wang, Dong; Acharya, Lipi; Du, Lisa; Vogt, Peter K; Ping, Peipei; Yates, John R

2015-11-03

Shotgun proteomics generates valuable information from large-scale and target protein characterizations, including protein expression, protein quantification, protein post-translational modifications (PTMs), protein localization, and protein-protein interactions. Typically, peptides derived from proteolytic digestion, rather than intact proteins, are analyzed by mass spectrometers because peptides are more readily separated, ionized and fragmented. The amino acid sequences of peptides can be interpreted by matching the observed tandem mass spectra to theoretical spectra derived from a protein sequence database. Identified peptides serve as surrogates for their proteins and are often used to establish what proteins were present in the original mixture and to quantify protein abundance. Two major issues exist for assigning peptides to their originating protein. The first issue is maintaining a desired false discovery rate (FDR) when comparing or combining multiple large datasets generated by shotgun analysis and the second issue is properly assigning peptides to proteins when homologous proteins are present in the database. Herein we demonstrate a new computational tool, ProteinInferencer, which can be used for protein inference with both small- or large-scale data sets to produce a well-controlled protein FDR. In addition, ProteinInferencer introduces confidence scoring for individual proteins, which makes protein identifications evaluable. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.

The nuclear proteome of Trypanosoma brucei

PubMed Central

Goos, Carina; Dejung, Mario; Janzen, Christian J.; Butter, Falk

2017-01-01

Trypanosoma brucei is a protozoan flagellate that is transmitted by tsetse flies into the mammalian bloodstream. The parasite has a huge impact on human health both directly by causing African sleeping sickness and indirectly, by infecting domestic cattle. The biology of trypanosomes involves some highly unusual, nuclear-localised processes. These include polycistronic transcription without classical promoters initiated from regions defined by histone variants, trans-splicing of all transcripts to the exon of a spliced leader RNA, transcription of some very abundant proteins by RNA polymerase I and antigenic variation, a switch in expression of the cell surface protein variants that allows the parasite to resist the immune system of its mammalian host. Here, we provide the nuclear proteome of procyclic Trypanosoma brucei, the stage that resides within the tsetse fly midgut. We have performed quantitative label-free mass spectrometry to score 764 significantly nuclear enriched proteins in comparison to whole cell lysates. A comparison with proteomes of several experimentally characterised nuclear and non-nuclear structures and pathways confirmed the high quality of the dataset: the proteome contains about 80% of all nuclear proteins and less than 2% false positives. Using motif enrichment, we found the amino acid sequence KRxR present in a large number of nuclear proteins. KRxR is a sub-motif of a classical eukaryotic monopartite nuclear localisation signal and could be responsible for nuclear localization of proteins in Kinetoplastida species. As a proof of principle, we have confirmed the nuclear localisation of six proteins with previously unknown localisation by expressing eYFP fusion proteins. While proteome data of several T. brucei organelles have been published, our nuclear proteome closes an important gap in knowledge to study trypanosome biology, in particular nuclear-related processes. PMID:28727848

Phosphatidylinositol (3,4,5)-Trisphosphate Activity Probes for the Labeling and Proteomic Characterization of Protein Binding Partners

PubMed Central

Rowland, Meng M.; Bostic, Heidi E.; Gong, Denghuang; Speers, Anna E.; Lucas, Nathan; Cho, Wonhwa; Cravatt, Benjamin F.; Best, Michael D.

2013-01-01

Phosphatidylinositol polyphosphate lipids, such as phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3), regulate critical biological processes, many of which are aberrant in disease. These lipids often act as site-specific ligands in interactions that enforce membrane-association of protein binding partners. Herein, we describe the development of bifunctional activity probes corresponding to the headgroup of PI(3,4,5)P3 that are effective for identifying and characterizing protein binding partners from complex samples, namely cancer cell extracts. These probes contain both a photoaffinity tag for covalent labeling of target proteins as well as a secondary handle for subsequent detection or manipulation of labeled proteins. Probes bearing different secondary tags were exploited, either by direct attachment of a fluorescent dye for optical detection or by using an alkyne that can be derivatized after protein labeling via click chemistry. First, we describe the design and modular synthetic strategy used to generate multiple probes with different reporter tags of use for characterizing probe-labeled proteins. Next, we report initial labeling studies using purified protein, the PH domain of Akt, in which probes were found to label this target, as judged by on-gel detection. Furthermore, protein labeling was abrogated by controls including competition with an unlabeled PI(3,4,5)P3 headgroup analog as well as through protein denaturation, indicating specific labeling. In addition, probes featuring different linker lengths between the PI(3,4,5)P3 headgroup and photoaffinity tag led to variations in protein labeling, indicating that a shorter linker was more effective in this case. Finally, proteomic labeling studies were performed using cell extracts, labeled proteins were observed by in-gel detection and characterized using post-labeling with biotin, affinity chromatography and identification via tandem mass spectrometry. These studies yielded a total of 265 proteins

Analytical Utility of Mass Spectral Binning in Proteomic Experiments by SPectral Immonium Ion Detection (SPIID)*

PubMed Central

Kelstrup, Christian D.; Frese, Christian; Heck, Albert J. R.; Olsen, Jesper V.; Nielsen, Michael L.

2014-01-01

Unambiguous identification of tandem mass spectra is a cornerstone in mass-spectrometry-based proteomics. As the study of post-translational modifications (PTMs) by means of shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry, the so-called diagnostic ions, which unequivocally identify a given mass spectrum as related to a specific PTM. Although such ions offer tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral-pattern-based approach for the discovery of diagnostic ions and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high-resolution peptide fragmentation spectra independent of the fragmentation method, instrument type, or protease employed. To benchmark the software tool, we analyzed large higher-energy collisional activation dissociation datasets of samples containing phosphorylation, ubiquitylation, SUMOylation, formylation, and lysine acetylation. Using the developed software tool, we were able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Because the investigated tandem mass spectra data were acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions was feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra and systematic mapping of fragmentation mechanisms related to common amino acids. PMID:24895383

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

Proteomic analysis of ripening tomato fruit infected by Botrytis cinerea.

PubMed

Shah, Punit; Powell, Ann L T; Orlando, Ron; Bergmann, Carl; Gutierrez-Sanchez, Gerardo

2012-04-06

Botrytis cinerea, a model necrotrophic fungal pathogen that causes gray mold as it infects different organs on more than 200 plant species, is a significant contributor to postharvest rot in fresh fruit and vegetables, including tomatoes. By describing host and pathogen proteomes simultaneously in infected tissues, the plant proteins that provide resistance and allow susceptibility and the pathogen proteins that promote colonization and facilitate quiescence can be identified. This study characterizes fruit and fungal proteins solubilized in the B. cinerea-tomato interaction using shotgun proteomics. Mature green, red ripe wild type and ripening inhibited (rin) mutant tomato fruit were infected with B. cinerea B05.10, and the fruit and fungal proteomes were identified concurrently 3 days postinfection. One hundred eighty-six tomato proteins were identified in common among red ripe and red ripe-equivalent ripening inhibited (rin) mutant tomato fruit infected by B. cinerea. However, the limited infections by B. cinerea of mature green wild type fruit resulted in 25 and 33% fewer defense-related tomato proteins than in red and rin fruit, respectively. In contrast, the ripening stage of genotype of the fruit infected did not affect the secreted proteomes of B. cinerea. The composition of the collected proteins populations and the putative functions of the identified proteins argue for their role in plant-pathogen interactions.

Label-free measurements on cell apoptosis using a terahertz metamaterial-based biosensor

NASA Astrophysics Data System (ADS)

Zhang, Caihong; Liang, Lanju; Ding, Liang; Jin, Biaobing; Hou, Yayi; Li, Chun; Jiang, Ling; Liu, Weiwei; Hu, Wei; Lu, Yanqing; Kang, Lin; Xu, Weiwei; Chen, Jian; Wu, Peiheng

2016-06-01

Label-free, real-time, and in-situ measurement on cell apoptosis is highly desirable in cell biology. We propose here a design of terahertz (THz) metamaterial-based biosensor for meeting this requirement. This metamaterial consists of a planar array of five concentric subwavelength gold ring resonators on a 10 μm-thick polyimide substrate, which can sense the change of dielectric environment above the metamaterial. We employ this sensor to an oral cancer cell (SCC4) with and without cisplatin, a chemotherapy drug for cancer treatment, and find a linear relation between cell apoptosis measured by Flow Cytometry and the relative change of resonant frequencies of the metamaterial measured by THz time-domain spectroscopy. This implies that we can determine the cell apoptosis in a label-free manner. We believe that this metamaterial-based biosensor can be developed into a cheap, label-free, real-time, and in-situ detection tool, which is of significant impact on the study of cell biology.

Label-Free Alignment of Nonmagnetic Particles in a Small Uniform Magnetic Field.

PubMed

Wang, Zhaomeng; Wang, Ying; Wu, Rui Ge; Wang, Z P; Ramanujan, R V

2018-01-01

Label-free manipulation of biological entities can minimize damage, increase viability and improve efficiency of subsequent analysis. Understanding the mechanism of interaction between magnetic and nonmagnetic particles in an inverse ferrofluid can provide a mechanism of label-free manipulation of such entities in a uniform magnetic field. The magnetic force, induced by relative magnetic susceptibility difference between nonmagnetic particles and surrounding magnetic particles as well as particle-particle interaction were studied. Label-free alignment of nonmagnetic particles can be achieved by higher magnetic field strength (Ba), smaller particle spacing (R), larger particle size (rp1), and higher relative magnetic permeability difference between particle and the surrounding fluid (Rμr). Rμr can be used to predict the direction of the magnetic force between both magnetic and nonmagnetic particles. A sandwich structure, containing alternate layers of magnetic and nonmagnetic particle chains, was studied. This work can be used for manipulation of nonmagnetic particles in lab-on-a-chip applications.

Chip-LC-MS for label-free profiling of human serum.

PubMed

Horvatovich, Peter; Govorukhina, Natalia I; Reijmers, Theo H; van der Zee, Ate G J; Suits, Frank; Bischoff, Rainer

2007-12-01

The discovery of biomarkers in easily accessible body fluids such as serum is one of the most challenging topics in proteomics requiring highly efficient separation and detection methodologies. Here, we present the application of a microfluidics-based LC-MS system (chip-LC-MS) to the label-free profiling of immunodepleted, trypsin-digested serum in comparison to conventional capillary LC-MS (cap-LC-MS). Both systems proved to have a repeatability of approximately 20% RSD for peak area, all sample preparation steps included, while repeatability of the LC-MS part by itself was less than 10% RSD for the chip-LC-MS system. Importantly, the chip-LC-MS system had a two times higher resolution in the LC dimension and resulted in a lower average charge state of the tryptic peptide ions generated in the ESI interface when compared to cap-LC-MS while requiring approximately 30 times less (~5 pmol) sample. In order to characterize both systems for their capability to find discriminating peptides in trypsin-digested serum samples, five out of ten individually prepared, identical sera were spiked with horse heart cytochrome c. A comprehensive data processing methodology was applied including 2-D smoothing, resolution reduction, peak picking, time alignment, and matching of the individual peak lists to create an aligned peak matrix amenable for statistical analysis. Statistical analysis by supervised classification and variable selection showed that both LC-MS systems could discriminate the two sample groups. However, the chip-LC-MS system allowed to assign 55% of the overall signal to selected peaks against 32% for the cap-LC-MS system.

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.

Feedback Microtubule Control and Microtubule-Actin Cross-talk in Arabidopsis Revealed by Integrative Proteomic and Cell Biology Analysis of KATANIN 1 Mutants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Pechan, Tibor; Luptovčiak, Ivan; Šamaj, Jozef

2017-09-01

Microtubule organization and dynamics are critical for key developmental processes such as cell division, elongation, and morphogenesis. Microtubule severing is an essential regulator of microtubules and is exclusively executed by KATANIN 1 in Arabidopsis In this study, we comparatively studied the proteome-wide effects in two KATANIN 1 mutants. Thus, shotgun proteomic analysis of roots and aerial parts of single nucleotide mutant fra2 and T-DNA insertion mutant ktn1-2 was carried out. We have detected 42 proteins differentially abundant in both fra2 and ktn1-2 KATANIN 1 dysfunction altered the abundance of proteins involved in development, metabolism, and stress responses. The differential regulation of tubulins and microtubule-destabilizing protein MDP25 implied a feedback microtubule control in KATANIN 1 mutants. Furthermore, deregulation of profilin 1, actin-depolymerizing factor 3, and actin 7 was observed. These findings were confirmed by immunoblotting analysis of actin and by microscopic observation of actin filaments using fluorescently labeled phalloidin. Results obtained by quantitative RT-PCR analysis revealed that changed protein abundances were not a consequence of altered expression levels of corresponding genes in the mutants. In conclusion, we show that abundances of several cytoskeletal proteins as well as organization of microtubules and the actin cytoskeleton are amended in accordance with defective microtubule severing. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

An automated growth enclosure for metabolic labeling of Arabidopsis thaliana with 13C-carbon dioxide - an in vivo labeling system for proteomics and metabolomics research

PubMed Central

2011-01-01

Background Labeling whole Arabidopsis (Arabidopsis thaliana) plants to high enrichment with 13C for proteomics and metabolomics applications would facilitate experimental approaches not possible by conventional methods. Such a system would use the plant's native capacity for carbon fixation to ubiquitously incorporate 13C from 13CO2 gas. Because of the high cost of 13CO2 it is critical that the design conserve the labeled gas. Results A fully enclosed automated plant growth enclosure has been designed and assembled where the system simultaneously monitors humidity, temperature, pressure and 13CO2 concentration with continuous adjustment of humidity, pressure and 13CO2 levels controlled by a computer running LabView software. The enclosure is mounted on a movable cart for mobility among growth environments. Arabidopsis was grown in the enclosure for up to 8 weeks and obtained on average >95 atom% enrichment for small metabolites, such as amino acids and >91 atom% for large metabolites, including proteins and peptides. Conclusion The capability of this labeling system for isotope dilution experiments was demonstrated by evaluation of amino acid turnover using GC-MS as well as protein turnover using LC-MS/MS. Because this 'open source' Arabidopsis 13C-labeling growth environment was built using readily available materials and software, it can be adapted easily to accommodate many different experimental designs. PMID:21310072

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification*

PubMed Central

Takemori, Nobuaki; Takemori, Ayako; Tanaka, Yuki; Endo, Yaeta; Hurst, Jane L.; Gómez-Baena, Guadalupe; Harman, Victoria M.; Beynon, Robert J.

2017-01-01

A major challenge in proteomics is the absolute accurate quantification of large numbers of proteins. QconCATs, artificial proteins that are concatenations of multiple standard peptides, are well established as an efficient means to generate standards for proteome quantification. Previously, QconCATs have been expressed in bacteria, but we now describe QconCAT expression in a robust, cell-free system. The new expression approach rescues QconCATs that previously were unable to be expressed in bacteria and can reduce the incidence of proteolytic damage to QconCATs. Moreover, it is possible to cosynthesize QconCATs in a highly-multiplexed translation reaction, coexpressing tens or hundreds of QconCATs simultaneously. By obviating bacterial culture and through the gain of high level multiplexing, it is now possible to generate tens of thousands of standard peptides in a matter of weeks, rendering absolute quantification of a complex proteome highly achievable in a reproducible, broadly deployable system. PMID:29055021

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.

A novel label-free cell-based assay technology using biolayer interferometry.

PubMed

Verzijl, D; Riedl, T; Parren, P W H I; Gerritsen, A F

2017-01-15

Biolayer interferometry (BLI) is a well-established optical label-free technique to study biomolecular interactions. Here we describe for the first time a cell-based BLI (cBLI) application that allows label-free real-time monitoring of signal transduction in living cells. Human A431 epidermoid carcinoma cells were captured onto collagen-coated biosensors and serum-starved, followed by exposure to agonistic compounds targeting various receptors, while recording the cBLI signal. Stimulation of the epidermal growth factor receptor (EGFR) with EGF, the β 2 -adrenoceptor with dopamine, or the hepatocyte growth factor receptor (HGFR/c-MET) with an agonistic antibody resulted in distinct cBLI signal patterns. We show that the mechanism underlying the observed changes in cBLI signal is mediated by rearrangement of the actin cytoskeleton, a process referred to as dynamic mass redistribution (DMR). A panel of ligand-binding blocking and non-blocking anti-EGFR antibodies was used to demonstrate that this novel BLI application can be efficiently used as a label-free cellular assay for compound screening and characterization. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Quantitative Metaproteomics and Activity-Based Probe Enrichment Reveals Significant Alterations in Protein Expression from a Mouse Model of Inflammatory Bowel Disease.

PubMed

Mayers, Michael D; Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W

2017-02-03

Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across two mouse cohorts as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control, thereby limiting genetic and environmental variables that influence microbiome composition. The data generated highlight quantitative alterations in both host and microbial proteins due to intestinal inflammation and corroborates the observed phylogenetic changes in bacteria that accompany IBD in humans and mouse models. The combination of isotope labeling with shotgun proteomics resulted in the total identification of 4434 protein clusters expressed in the microbial proteomic environment, 276 of which demonstrated differential abundance between control and IBD mice. Notably, application of a novel cysteine-reactive probe uncovered several microbial proteases and hydrolases overrepresented in the IBD mice. Implementation of these methods demonstrated that substantial insights into the identity and dysregulation of host and microbial proteins altered in IBD can be accomplished and can be used in the interrogation of other microbiome-related diseases.

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.

Label-free SERS in biological and biomedical applications: Recent progress, current challenges and opportunities

NASA Astrophysics Data System (ADS)

Zheng, Xiao-Shan; Jahn, Izabella Jolan; Weber, Karina; Cialla-May, Dana; Popp, Jürgen

2018-05-01

To achieve an insightful look within biomolecular processes on the cellular level, the development of diseases as well as the reliable detection of metabolites and pathogens, a modern analytical tool is needed that is highly sensitive, molecular-specific and exhibits fast detection. Surface-enhanced Raman spectroscopy (SERS) is known to meet these requirements and, within this review article, the recent progress of label-free SERS in biological and biomedical applications is summarized and discussed. This includes the detection of biomolecules such as metabolites, nucleic acids and proteins. Further, the characterization and identification of microorganisms has been achieved by label-free SERS-based approaches. Eukaryotic cells can be characterized by SERS in order to gain information about the outer cell wall or to detect intracellular molecules and metabolites. The potential of SERS for medically relevant detection schemes is emphasized by the label-free detection of tissue, the investigation of body fluids as well as applications for therapeutic and illicit drug monitoring. The review article is concluded with an evaluation of the recent progress and current challenges in order to highlight the direction of label-free SERS in the future.

Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation

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

Guarnieri, Michael T.; Nag, Ambarish; Yang, Shihui

2013-11-01

Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine thesemore » mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.« less

A label-free fluorescent aptamer sensor based on regulation of malachite green fluorescence

PubMed Central

Xu, Weichen; Lu, Yi

2009-01-01

We report a label-free fluorescent aptamer sensor for adenosine based on the regulation of malachite green (MG) fluorescence, with comparable sensitivity and selectivity to other labeled adenosine aptamer-based sensors. The sensor consists of free MG, an aptamer strand containing an adenosine aptamer next to an MG aptamer, and a bridging strand that partially hybridizes to the aptamer strand. Such a hybridization prevents MG from binding to MG aptamer, resulting in low fluorescence of MG in the absence of adenosine. Addition of adenosine causes the adenosine aptamer to bind adenosine, weakening the hybridization of the aptamer strand with the bridging strand, making it possible for MG to bind to the aptamer strand and exhibits high fluorescence intensity. Since this design is based purely on nucleic acid hybridization, it can be generally applied to other aptamers for the label-free detection of a broad range of analytes. PMID:20017558

Effects of Alanyl-Glutamine Treatment on the Peritoneal Dialysis Effluent Proteome Reveal Pathomechanism-Associated Molecular Signatures*

PubMed Central

Herzog, Rebecca; Boehm, Michael; Unterwurzacher, Markus; Wagner, Anja; Parapatics, Katja; Májek, Peter; Mueller, André C.; Lichtenauer, Anton; Bennett, Keiryn L.; Alper, Seth L.; Vychytil, Andreas; Aufricht, Christoph; Kratochwill, Klaus

2018-01-01

Peritoneal dialysis (PD) is a modality of renal replacement therapy in which the high volumes of available PD effluent (PDE) represents a rich source of biomarkers for monitoring disease and therapy. Although this information could help guide the management of PD patients, little is known about the potential of PDE to define pathomechanism-associated molecular signatures in PD. We therefore subjected PDE to a high-performance multiplex proteomic analysis after depletion of highly-abundant plasma proteins and enrichment of low-abundance proteins. A combination of label-free and isobaric labeling strategies was applied to PDE samples from PD patients (n = 20) treated in an open-label, randomized, two-period, cross-over clinical trial with standard PD fluid or with a novel PD fluid supplemented with alanyl-glutamine (AlaGln). With this workflow we identified 2506 unique proteins in the PDE proteome, greatly increasing coverage beyond the 171 previously-reported proteins. The proteins identified range from high abundance plasma proteins to low abundance cellular proteins, and are linked to larger numbers of biological processes and pathways, some of which are novel for PDE. Interestingly, proteins linked to membrane remodeling and fibrosis are overrepresented in PDE compared with plasma, whereas the proteins underrepresented in PDE suggest decreases in host defense, immune-competence and response to stress. Treatment with AlaGln-supplemented PD fluid is associated with reduced activity of membrane injury-associated mechanisms and with restoration of biological processes involved in stress responses and host defense. Our study represents the first application of the PDE proteome in a randomized controlled prospective clinical trial of PD. This novel proteomic workflow allowed detection of low abundance biomarkers to define pathomechanism-associated molecular signatures in PD and their alterations by a novel therapeutic intervention. PMID:29208752

sapFinder: an R/Bioconductor package for detection of variant peptides in shotgun proteomics experiments.

PubMed

Wen, Bo; Xu, Shaohang; Sheynkman, Gloria M; Feng, Qiang; Lin, Liang; Wang, Quanhui; Xu, Xun; Wang, Jun; Liu, Siqi

2014-11-01

Single nucleotide variations (SNVs) located within a reading frame can result in single amino acid polymorphisms (SAPs), leading to alteration of the corresponding amino acid sequence as well as function of a protein. Accurate detection of SAPs is an important issue in proteomic analysis at the experimental and bioinformatic level. Herein, we present sapFinder, an R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. This package automates the construction of variation-associated databases from public SNV repositories or sample-specific next-generation sequencing (NGS) data and the identification of SAPs through database searching, post-processing and generation of HTML-based report with visualized interface. sapFinder is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at http://bioconductor.org/packages/devel/bioc/html/sapFinder.html and are provided under a GPL-2 license. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Label-free imaging of cellular malformation using high resolution photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Chen, Zhongjiang; Li, Bingbing; Yang, Sihua

2014-09-01

A label-free high resolution photoacoustic microscopy (PAM) system for imaging cellular malformation is presented. The carbon fibers were used to testify the lateral resolution of the PAM. Currently, the lateral resolution is better than 2.7 μm. The human normal red blood cells (RBCs) were used to prove the imaging capability of the system, and a single red blood cell was mapped with high contrast. Moreover, the iron deficiency anemia RBCs were clearly distinguished from the cell morphology by using the PAM. The experimental results demonstrate that the photoacoustic microscopy system can accomplish label-free photoacoustic imaging and that it has clinical potential for use in the detection of erythrocytes and blood vessels malformation.

A dual marker label free electrochemical assay for Flavivirus dengue diagnosis.

PubMed

Santos, Adriano; Bueno, Paulo R; Davis, Jason J

2018-02-15

Dengue is a RNA viral illness of the genus Flavivirus which can cause, depending on the pervasiveness of the infection, hemorrhagic dengue fever or dengue shock syndrome. Herein we present an electrochemical label free approach enabling the rapid sensitive quantification of NS1 and IgG (supporting an ability to distinguish primary and secondary infections). Using a bifunctional SAM containing PEG moieties and a tethered redox thiol, both markers are detectable across clinically relevant levels by label free impedance derived redox capacitance. A subsequent frequency specific immittance function approach enables assaying (within seconds) with no impairment of analytical quality (linearity, sensitivity and variance). Copyright © 2017 Elsevier B.V. All rights reserved.

Proteomic validation of protease drug targets: pharmacoproteomics of matrix metalloproteinase inhibitor drugs using isotope-coded affinity tag labelling and tandem mass spectrometry.

PubMed

Butler, G S; Overall, C M

2007-01-01

We illustrate the use of quantitative proteomics, namely isotope-coded affinity tag labelling and tandem mass spectrometry, to assess the targets and effects of the blockade of matrix metalloproteinases by an inhibitor drug in a breast cancer cell culture system. Treatment of MT1-MMP-transfected MDA-MB-231 cells with AG3340 (Prinomastat) directly affected the processing a multitude of matrix metalloproteinase substrates, and indirectly altered the expression of an array of other proteins with diverse functions. Therefore, broad spectrum blockade of MMPs has wide-ranging biological consequences. In this human breast cancer cell line, secreted substrates accumulated uncleaved in the conditioned medium and plasma membrane protein substrates were retained on the cell surface, due to reduced processing and shedding of these proteins (cell surface receptors, growth factors and bioactive molecules) to the medium in the presence of the matrix metalloproteinase inhibitor. Hence, proteomic investigation of drug-perturbed cellular proteomes can identify new protease substrates and at the same time provides valuable information for target validation, drug efficacy and potential side effects prior to commitment to clinical trials.

Time Series Proteome Profiling

PubMed Central

Formolo, Catherine A.; Mintz, Michelle; Takanohashi, Asako; Brown, Kristy J.; Vanderver, Adeline; Halligan, Brian; Hathout, Yetrib

2014-01-01

This chapter provides a detailed description of a method used to study temporal changes in the endoplasmic reticulum (ER) proteome of fibroblast cells exposed to ER stress agents (tunicamycin and thapsigargin). Differential stable isotope labeling by amino acids in cell culture (SILAC) is used in combination with crude ER fractionation, SDS–PAGE and LC-MS/MS to define altered protein expression in tunicamycin or thapsigargin treated cells versus untreated cells. Treated and untreated cells are harvested at different time points, mixed at a 1:1 ratio and processed for ER fractionation. Samples containing labeled and unlabeled proteins are separated by SDS–PAGE, bands are digested with trypsin and the resulting peptides analyzed by LC-MS/MS. Proteins are identified using Bioworks software and the Swiss-Prot data-base, whereas ratios of protein expression between treated and untreated cells are quantified using ZoomQuant software. Data visualization is facilitated by GeneSpring software. proteomics PMID:21082445

Specific labeling of zinc finger proteins using noncanonical amino acids and copper-free click chemistry.

PubMed

Kim, Younghoon; Kim, Sung Hoon; Ferracane, Dean; Katzenellenbogen, John A; Schroeder, Charles M

2012-09-19

Zinc finger proteins (ZFPs) play a key role in transcriptional regulation and serve as invaluable tools for gene modification and genetic engineering. Development of efficient strategies for labeling metalloproteins such as ZFPs is essential for understanding and controlling biological processes. In this work, we engineered ZFPs containing cysteine-histidine (Cys2-His2) motifs by metabolic incorporation of the unnatural amino acid azidohomoalanine (AHA), followed by specific protein labeling via click chemistry. We show that cyclooctyne promoted [3 + 2] dipolar cycloaddition with azides, known as copper-free click chemistry, provides rapid and specific labeling of ZFPs at high yields as determined by mass spectrometry analysis. We observe that the DNA-binding activity of ZFPs labeled by conventional copper-mediated click chemistry was completely abolished, whereas ZFPs labeled by copper-free click chemistry retain their sequence-specific DNA-binding activity under native conditions, as determined by electrophoretic mobility shift assays, protein microarrays, and kinetic binding assays based on Förster resonance energy transfer (FRET). Our work provides a general framework to label metalloproteins such as ZFPs by metabolic incorporation of unnatural amino acids followed by copper-free click chemistry.

Quantitative Proteomic Analysis of Duck Ovarian Follicles Infected with Duck Tembusu Virus by Label-Free LC-MS

PubMed Central

Han, Kaikai; Zhao, Dongmin; Liu, Yuzhuo; Liu, Qingtao; Huang, Xinmei; Yang, Jing; An, Fengjiao; Li, Yin

2016-01-01

Duck Tembusu virus (DTMUV) is a newly emerging pathogenic flavivirus that has caused massive economic losses to the duck industry in China. DTMUV infection mainly results in significant decreases in egg production in egg-laying ducks within 1–2 weeks post infection. However, information on the comparative protein expression of host tissues in response to DTMUV infection is limited. In the present study, the cellular protein response to DTMUV infection in duck ovarian follicles was analyzed using nano-flow high-performance liquid chromatography-electrospray tandem mass spectrometry. Quantitative proteomic analysis revealed 131 differentially expressed proteins, among which 53 were up regulated and 78 were down regulated. The identified proteins were involved in the regulation of essential processes such as cellular structure and integrity, RNA processing, protein biosynthesis and modification, vesicle transport, signal transduction, and mitochondrial pathway. Some selected proteins that were found to be regulated in DTMUV-infected tissues were screened by quantitative real-time PCR to examine their regulation at the transcriptional level, western blot analysis was used to validate the changes of some selected proteins on translational level. To our knowledge, this study is the first to analyze the proteomic changes in duck ovarian follicles following DTMUV infection. The protein-related information obtained in this study may be useful to understand the host response to DTMUV infection and the inherent mechanism of DTMUV replication and pathogenicity. PMID:27066001

Proteomic analysis of common bean stem under drought stress using in-gel stable isotope labeling.

PubMed

Zadražnik, Tanja; Egge-Jacobsen, Wolfgang; Meglič, Vladimir; Šuštar-Vozlič, Jelka

2017-02-01

Drought is an abiotic stress that strongly influences plant growth, development and productivity. Proteome changes in the stem of the drought-tolerant common bean (Phaseolus vulgaris L.) cultivar Tiber have were when the plants were exposed to drought. Five-week-old plants were subjected to water deficit by withholding irrigation for 7, 12 and 17days, whereas control plants were regularly irrigated. Relative water content (RWC) of leaves, as an indicator of the degree of cell and tissue hydration, showed the highest statistically significant differences between control and drought-stressed plants after 17days of treatment, where RWC remained at 90% for control and declined to 45% for stressed plants. Plants exposed to drought for 17days and control plants at the same developmental stage were included in quantitative proteomic analysis using in-gel stable isotope labeling of proteins in combination with mass spectrometry. The quantified proteins were grouped into several functional groups, mainly into energy metabolism, photosynthesis, proteolysis, protein synthesis and proteins related to defense and stress. 70kDa heat shock protein showed the greatest increase in abundance under drought of all the proteins, suggesting its role in protecting plants against stress by re-establishing normal protein conformations and thus cellular homeostasis. The abundance of proteins involved in protein synthesis also increased under drought stress, important for recovery of damaged proteins involved in the plant cell's metabolic activities. Other important proteins in this study were related to proteolysis and folding, which are necessary for maintaining proper cellular protein homeostasis. Taken together, these results reveal the complexity of pathways involved in the drought stress response in common bean stems and enable comparison with the results of proteomic analysis of leaves, thus providing important information to further understand the biochemical and molecular mechanisms

Plasma proteins in the acquired denture pellicle enhance substrate surface free energy and Candida albicans phospholipase and proteinase activities.

PubMed

Custodio, William; Silva, Wander J; Paes Leme, Adriana F; Cury, Jaime A; Del Bel Cury, Altair A

2015-11-01

The objective of the present study was to determine if blood plasma proteins could change the proteome of the acquired denture pellicle by label-free quantitative proteomics. As pellicle proteome modulates the interaction between substrates and Candida cells, we investigated its effect on the surface free energy (SFE) of the coated resin and on Candida albicans phospholipase and aspartyl proteinase activities. Poly(methylmethacrylate) discs were exposed to saliva (control) or saliva enriched with blood plasma (experimental group). The pellicle proteome was analyzed by mass spectrometry coupled with liquid chromatography. SFE was determined by acid-base technique. After biofilm formation, phospholipase and proteinase activities were determined accordingly to classic plate methods. Data were analyzed by two-way anova and Tukey test (P < 0.05). α-Amylase, cystatins, mucins, and host-immune system proteins were the main proteins identified in the control group. Fibrinogen and albumin were observed only in the experimental group. Coated discs of the experimental group presented an increased SFE (P < 0.05). For both enzymes tested, the experimental group showed higher proteolytic activity (P < 0.001). Blood plasma changes the proteome of the acquired denture pellicle, increasing surface free energy and the activity of Candida albicans phospholipase and aspartyl proteinase. © 2014 Wiley Publishing Asia Pty Ltd.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

PubMed

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Label-free, real-time interaction and adsorption analysis 1: surface plasmon resonance.

PubMed

Fee, Conan J

2013-01-01

A key requirement for the development of proteins for use in nanotechnology is an understanding of how individual proteins bind to other molecules as they assemble into larger structures. The introduction of labels to enable the detection of biomolecules brings the inherent risk that the labels themselves will influence the nature of biomolecular interactions. Thus, there is a need for label-free interaction and adsorption analysis. In this and the following chapter, two biosensor techniques are reviewed: surface plasmon resonance (SPR) and the quartz crystal microbalance (QCM). Both allow real-time analysis of biomolecular interactions and both are label-free. The first of these, SPR, is an optical technique that is highly sensitive to the changes in refractive index that occur with protein (or other molecule) accumulation near an illuminated gold surface. Unlike QCM ( Chapter 18 ) SPR is not affected by the water that may be associated with the adsorbed layer nor by conformational changes in the adsorbed species. SPR thus provides unique information about the interaction of a protein with its binding partners.

Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood

PubMed Central

Fan, H. Christina; Blumenfeld, Yair J.; Chitkara, Usha; Hudgins, Louanne; Quake, Stephen R.

2008-01-01

We directly sequenced cell-free DNA with high-throughput shotgun sequencing technology from plasma of pregnant women, obtaining, on average, 5 million sequence tags per patient sample. This enabled us to measure the over- and underrepresentation of chromosomes from an aneuploid fetus. The sequencing approach is polymorphism-independent and therefore universally applicable for the noninvasive detection of fetal aneuploidy. Using this method, we successfully identified all nine cases of trisomy 21 (Down syndrome), two cases of trisomy 18 (Edward syndrome), and one case of trisomy 13 (Patau syndrome) in a cohort of 18 normal and aneuploid pregnancies; trisomy was detected at gestational ages as early as the 14th week. Direct sequencing also allowed us to study the characteristics of cell-free plasma DNA, and we found evidence that this DNA is enriched for sequences from nucleosomes. PMID:18838674

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.

Mapping the Extracellular and Membrane Proteome Associated with the Vasculature and the Stroma in the Embryo*

PubMed Central

Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas

2013-01-01

In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615

An ultrasensitive label-free biosensor for assaying of sequence-specific DNA-binding protein based on amplifying fluorescent conjugated polymer.