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

PubMed Central

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

2010-01-01

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

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

PubMed Central

Bianco, Linda; Perrotta, Gaetano

2015-01-01

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

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

PubMed

Bianco, Linda; Perrotta, Gaetano

2015-03-12

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

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

PubMed

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

2013-08-26

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

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.

Advances in microscale separations towards nanoproteomics applications

DOE PAGES

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

2017-07-21

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

Advances in microscale separations towards nanoproteomics applications

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

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

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

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.

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

PubMed

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

2010-08-06

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

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

PubMed Central

2010-01-01

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

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

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

A Comparative Analysis of Computational Approaches to Relative Protein Quantification Using Peptide Peak Intensities in Label-free LC-MS Proteomics Experiments

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

Matzke, Melissa M.; Brown, Joseph N.; Gritsenko, Marina A.

2013-02-01

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred frommore » one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.« less

Combining Capillary Electrophoresis with Mass Spectrometry for Applications in Proteomics

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

Simpson, David C.; Smith, Richard D.

2005-04-01

Throughout the field of global proteomics, ranging from simple organism studies to human medical applications, the high sample complexity creates demands for improved separations and analysis techniques. Furthermore, with increased organism complexity, the correlation between proteome and genome becomes less certain due to extensive mRNA processing prior to translation. In this way, the same DNA sequence can potentially code for regions in a number of distinct proteins; quantitative differences in expression (or abundance) between these often-related species are of significant interest. Well-established proteomics techniques, which use genomic information to identify peptides that originate from protease digestion, often cannot easily distinguishmore » between such gene products; intact protein-level analyses are required to complete the picture, particularly for identifying post-translational modifications. While chromatographic techniques are currently better suited to peptide analysis, capillary electrophoresis (CE) in combination with mass spectrometry (MS) may become important for intact protein analysis. This review focuses on CE/MS instrumentation and techniques showing promise for such applications, highlighting those with greatest potential. Reference will also be made to developments relevant to peptide-level analyses for use in time- or sample-limited situations.« less

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry.

PubMed

Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

2016-12-02

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

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

PubMed

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

2006-05-01

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

Preparation of the low molecular weight serum proteome for mass spectrometry analysis.

PubMed

Waybright, Timothy J; Chan, King C; Veenstra, Timothy D; Xiao, Zhen

2013-01-01

The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

PubMed Central

Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

2017-01-01

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

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

PubMed Central

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

2013-01-01

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

Introducing Proteomics in the Undergraduate Curriculum: A Simple 2D Gel Electrophoresis Exercise with Serum Proteins

ERIC Educational Resources Information Center

Kim, Thomas D.; Craig, Paul A.

2010-01-01

Two-dimensional gel electrophoresis (2DGE) remains an important tool in the study of biological systems by proteomics. While the use of 2DGE is commonplace in research publications, there are few instructional laboratories that address the use of 2DGE for analyzing complex protein samples. One reason for this lack is the fact that the preparation…

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

PubMed

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

2013-01-04

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

Comparison of protein profiles of beech bark disease-resistant or beech bark disease-susceptible American beech

Treesearch

Mary E. Mason; Marek Krasowski; Judy Loo; Jennifer. Koch

2011-01-01

Proteomic analysis of beech bark proteins from trees resistant and susceptible to beech bark disease (BBD) was conducted. Sixteen trees from eight geographically isolated stands, 10 resistant (healthy) and 6 susceptible (diseased/infested) trees, were studied. The genetic complexity of the sample unit, the sampling across a wide geographic area, and the complexity of...

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.

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

PubMed

Goh, Wilson Wen Bin; Wong, Limsoon

2016-09-02

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

Protein and gene model inference based on statistical modeling in k-partite graphs.

PubMed

Gerster, Sarah; Qeli, Ermir; Ahrens, Christian H; Bühlmann, Peter

2010-07-06

One of the major goals of proteomics is the comprehensive and accurate description of a proteome. Shotgun proteomics, the method of choice for the analysis of complex protein mixtures, requires that experimentally observed peptides are mapped back to the proteins they were derived from. This process is also known as protein inference. We present Markovian Inference of Proteins and Gene Models (MIPGEM), a statistical model based on clearly stated assumptions to address the problem of protein and gene model inference for shotgun proteomics data. In particular, we are dealing with dependencies among peptides and proteins using a Markovian assumption on k-partite graphs. We are also addressing the problems of shared peptides and ambiguous proteins by scoring the encoding gene models. Empirical results on two control datasets with synthetic mixtures of proteins and on complex protein samples of Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana suggest that the results with MIPGEM are competitive with existing tools for protein inference.

Supramolecular Affinity Chromatography for Methylation-Targeted Proteomics.

PubMed

Garnett, Graham A E; Starke, Melissa J; Shaurya, Alok; Li, Janessa; Hof, Fraser

2016-04-05

Proteome-wide studies of post-translationally methylated species using mass spectrometry are complicated by high sample diversity, competition for ionization among peptides, and mass redundancies. Antibody-based enrichment has powered methylation proteomics until now, but the reliability, pan-specificity, polyclonal nature, and stability of the available pan-specific antibodies are problematic and do not provide a standard, reliable platform for investigators. We have invented an anionic supramolecular host that can form host-guest complexes selectively with methyllysine-containing peptides and used it to create a methylysine-affinity column. The column resolves peptides on the basis of methylation-a feat impossible with a comparable commercial cation-exchange column. A proteolyzed nuclear extract was separated on the methyl-affinity column prior to standard proteomics analysis. This experiment demonstrates that such chemical methyl-affinity columns are capable of enriching and improving the analysis of methyllysine residues from complex protein mixtures. We discuss the importance of this advance in the context of biomolecule-driven enrichment methods.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

NASA Astrophysics Data System (ADS)

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-06-01

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

PubMed Central

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-01-01

Mass spectrometry–based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications. PMID:27049631

Surface modified capillary electrophoresis combined with in solution isoelectric focusing and MALDI-TOF/TOF MS: a gel-free multidimensional electrophoresis approach for proteomic profiling--exemplified on human follicular fluid.

PubMed

Hanrieder, Jörg; Zuberovic, Aida; Bergquist, Jonas

2009-04-24

Development of miniaturized analytical tools continues to be of great interest to face the challenges in proteomic analysis of complex biological samples such as human body fluids. In the light of these challenges, special emphasis is put on the speed and simplicity of newly designed technological approaches as well as the need for cost efficiency and low sample consumption. In this study, we present an alternative multidimensional bottom-up approach for proteomic profiling for fast, efficient and sensitive protein analysis in complex biological matrices. The presented setup was based on sample pre-fractionation using microscale in solution isoelectric focusing (IEF) followed by tryptic digestion and subsequent capillary electrophoresis (CE) coupled off-line to matrix assisted laser desorption/ionization time of flight tandem mass spectrometry (MALDI TOF MS/MS). For high performance CE-separation, PolyE-323 modified capillaries were applied to minimize analyte-wall interactions. The potential of the analytical setup was demonstrated on human follicular fluid (hFF) representing a typical complex human body fluid with clinical implication. The obtained results show significant identification of 73 unique proteins (identified at 95% significance level), including mostly acute phase proteins but also protein identities that are well known to be extensively involved in follicular development.

Salivary biomarker development using genomic, proteomic and metabolomic approaches

PubMed Central

2012-01-01

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches. PMID:23114182

Sample handling for mass spectrometric proteomic investigations of human sera.

PubMed

West-Nielsen, Mikkel; Høgdall, Estrid V; Marchiori, Elena; Høgdall, Claus K; Schou, Christian; Heegaard, Niels H H

2005-08-15

Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers while less effort has been invested in devising standard procedures for sample preparation and storage in relation to model building based on complex sets of mass spectrometric (MS) data. Thus, development of standardized methods for collection and storage of patient samples together with standards for transportation and handling of samples are needed. This requires knowledge about how sample processing affects MS-based proteome analyses and thereby how nonbiological biased classification errors are avoided. In this study, we characterize the effects of sample handling, including clotting conditions, storage temperature, storage time, and freeze/thaw cycles, on MS-based proteomics of human serum by using principal components analysis, support vector machine learning, and clustering methods based on genetic algorithms as class modeling and prediction methods. Using spiking to artificially create differentiable sample groups, this integrated approach yields data that--even when working with sample groups that differ more than may be expected in biological studies--clearly demonstrate the need for comparable sampling conditions for samples used for modeling and for the samples that are going into the test set group. Also, the study emphasizes the difference between class prediction and class comparison studies as well as the advantages and disadvantages of different modeling methods.

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

Evolution of complexity in the zebrafish synapse proteome

PubMed Central

Bayés, Àlex; Collins, Mark O.; Reig-Viader, Rita; Gou, Gemma; Goulding, David; Izquierdo, Abril; Choudhary, Jyoti S.; Emes, Richard D.; Grant, Seth G. N.

2017-01-01

The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases. PMID:28252024

Proteomic profiling of an undefined microbial consortium cultured in fermented dairy manure: Methods development.

PubMed

Hanson, Andrea J; Paszczynski, Andrzej J; Coats, Erik R

2016-03-01

The production of polyhydroxyalkanoates (PHA; bioplastics) from waste or surplus feedstocks using mixed microbial consortia (MMC) and aerobic dynamic feeding (ADF) is a growing field within mixed culture biotechnology. This study aimed to optimize a 2DE workflow to investigate the proteome dynamics of an MMC synthesizing PHA from fermented dairy manure. To mitigate the challenges posed to effective 2DE by this complex sample matrix, the bacterial biomass was purified using Accudenz gradient centrifugation (AGC) before protein extraction. The optimized 2DE method yielded high-quality gels suitable for quantitative comparative analysis and subsequent protein identification by LC-MS/MS. The optimized 2DE method could be adapted to other proteomic investigations involving MMC in complex organic or environmental matrices. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

PubMed

Kaur, Punit; Asea, Alexzander

2011-01-01

Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

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

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

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

2014-07-02

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

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

PubMed

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

2015-10-02

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

Advances in microscale separations towards nanoproteomics applications

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

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

Microscale separations (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. While significant advances have been achieved in MS-based proteomics, the current platforms still face a significant challenge in overall sensitivity towards nanoproteomics (i.e., with less than 1 g total amount of proteins available) applications such as cellular heterogeneity in tissue pathologies. Herein, we review recent advances in microscale separation techniques and integrated sample processing systems that improve the overall sensitivity and coverage of the proteomics workflow, and their contributionsmore » towards nanoproteomics applications.« less

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

PubMed

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

2005-09-01

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

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

PubMed

Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

2017-02-03

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

DOE PAGES

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...

2015-07-03

Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less

Coupling detergent lysis/clean-up methodology with intact protein fractionation for enhanced proteome characterization

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

Sharma, Ritin; Dill, Brian; Chourey, Karuna

2012-01-01

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four different detergent clean-up methods (Trichloroacetic acid (TCA) precipitation, Chloroform/Methanol/Water (CMW) extraction, commercial detergent removal spin column method (DRS) and filter-aided sample preparation(FASP)) with respect to varying amounts of protein biomass in the samples, and provide efficiency benchmarks with respect to protein, peptide, and spectral identifications for each method. Our results show that for protein limited samples, FASP outperforms the other three clean-up methods, while at high protein amountmore » all the methods are comparable. This information was used in a dual strategy of comparing molecular weight based fractionated and unfractionated lysates from three increasingly complex samples (Escherichia coli, a five microbial isolate mixture, and a natural microbial community groundwater sample), which were all lysed with SDS and cleaned up using FASP. The two approaches complemented each other by enhancing the number of protein identifications by 8%-25% across the three samples and provided broad pathway coverage.« less

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.

Highly efficient peptide separations in proteomics. Part 2: bi- and multidimensional liquid-based separation techniques.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Tuytten, Robin; Verleysen, Katleen; Kas, Koen; François, Isabelle; Sandra, Pat

2009-04-15

Multidimensional liquid-based separation techniques are described for maximizing the resolution of the enormous number of peptides generated upon tryptic digestion of proteomes, and hence, reduce the spatial and temporal complexity of the sample to a level that allows successful mass spectrometric analysis. This review complements the previous contribution on unidimensional high performance liquid chromatography (HPLC). Both chromatography and electrophoresis will be discussed albeit with reversed-phase HPLC (RPLC) as the final separation dimension prior to MS analysis.

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

PubMed Central

Padula, Matthew P.; Berry, Iain J.; O′Rourke, Matthew B.; Raymond, Benjamin B.A.; Santos, Jerran; Djordjevic, Steven P.

2017-01-01

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O′Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single ‘spots’ in a polyacrylamide gel, allowing the quantitation of changes in a proteoform′s abundance to ascertain changes in an organism′s phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the ‘Top-Down’. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O’Farrell’s paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism′s proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer. PMID:28387712

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis.

PubMed

Padula, Matthew P; Berry, Iain J; O Rourke, Matthew B; Raymond, Benjamin B A; Santos, Jerran; Djordjevic, Steven P

2017-04-07

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O'Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single 'spots' in a polyacrylamide gel, allowing the quantitation of changes in a proteoform's abundance to ascertain changes in an organism's phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the 'Top-Down'. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O'Farrell's paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism's proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer.

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

PubMed Central

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

2009-01-01

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies. PMID:19921851

Dual-color Proteomic Profiling of Complex Samples with a Microarray of 810 Cancer-related Antibodies*

PubMed Central

Schröder, Christoph; Jacob, Anette; Tonack, Sarah; Radon, Tomasz P.; Sill, Martin; Zucknick, Manuela; Rüffer, Sven; Costello, Eithne; Neoptolemos, John P.; Crnogorac-Jurcevic, Tatjana; Bauer, Andrea; Fellenberg, Kurt; Hoheisel, Jörg D.

2010-01-01

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses. PMID:20164060

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

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

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

2010-12-01

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

Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges.

PubMed

Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel

2014-03-01

Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A software suite for the generation and comparison of peptide arrays from sets of data collected by liquid chromatography-mass spectrometry.

PubMed

Li, Xiao-jun; Yi, Eugene C; Kemp, Christopher J; Zhang, Hui; Aebersold, Ruedi

2005-09-01

There is an increasing interest in the quantitative proteomic measurement of the protein contents of substantially similar biological samples, e.g. for the analysis of cellular response to perturbations over time or for the discovery of protein biomarkers from clinical samples. Technical limitations of current proteomic platforms such as limited reproducibility and low throughput make this a challenging task. A new LC-MS-based platform is able to generate complex peptide patterns from the analysis of proteolyzed protein samples at high throughput and represents a promising approach for quantitative proteomics. A crucial component of the LC-MS approach is the accurate evaluation of the abundance of detected peptides over many samples and the identification of peptide features that can stratify samples with respect to their genetic, physiological, or environmental origins. We present here a new software suite, SpecArray, that generates a peptide versus sample array from a set of LC-MS data. A peptide array stores the relative abundance of thousands of peptide features in many samples and is in a format identical to that of a gene expression microarray. A peptide array can be subjected to an unsupervised clustering analysis to stratify samples or to a discriminant analysis to identify discriminatory peptide features. We applied the SpecArray to analyze two sets of LC-MS data: one was from four repeat LC-MS analyses of the same glycopeptide sample, and another was from LC-MS analysis of serum samples of five male and five female mice. We demonstrate through these two study cases that the SpecArray software suite can serve as an effective software platform in the LC-MS approach for quantitative proteomics.

Comparing Simplification Strategies for the Skeletal Muscle Proteome

PubMed Central

Geary, Bethany; Young, Iain S.; Cash, Phillip; Whitfield, Phillip D.; Doherty, Mary K.

2016-01-01

Skeletal muscle is a complex tissue that is dominated by the presence of a few abundant proteins. This wide dynamic range can mask the presence of lower abundance proteins, which can be a confounding factor in large-scale proteomic experiments. In this study, we have investigated a number of pre-fractionation methods, at both the protein and peptide level, for the characterization of the skeletal muscle proteome. The analyses revealed that the use of OFFGEL isoelectric focusing yielded the largest number of protein identifications (>750) compared to alternative gel-based and protein equalization strategies. Further, OFFGEL led to a substantial enrichment of a different sub-population of the proteome. Filter-aided sample preparation (FASP), coupled to peptide-level OFFGEL provided more confidence in the results due to a substantial increase in the number of peptides assigned to each protein. The findings presented here support the use of a multiplexed approach to proteome characterization of skeletal muscle, which has a recognized imbalance in the dynamic range of its protein complement. PMID:28248220

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

PubMed

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Decoding 2D-PAGE complex maps: relevance to proteomics.

PubMed

Pietrogrande, Maria Chiara; Marchetti, Nicola; Dondi, Francesco; Righetti, Pier Giorgio

2006-03-20

This review describes two mathematical approaches useful for decoding the complex signal of 2D-PAGE maps of protein mixtures. These methods are helpful for interpreting the large amount of data of each 2D-PAGE map by extracting all the analytical information hidden therein by spot overlapping. Here the basic theory and application to 2D-PAGE maps are reviewed: the means for extracting information from the experimental data and their relevance to proteomics are discussed. One method is based on the quantitative theory of statistical model of peak overlapping (SMO) using the spot experimental data (intensity and spatial coordinates). The second method is based on the study of the 2D-autocovariance function (2D-ACVF) computed on the experimental digitised map. They are two independent methods that are able to extract equal and complementary information from the 2D-PAGE map. Both methods permit to obtain fundamental information on the sample complexity and the separation performance and to single out ordered patterns present in spot positions: the availability of two independent procedures to compute the same separation parameters is a powerful tool to estimate the reliability of the obtained results. The SMO procedure is an unique tool to quantitatively estimate the degree of spot overlapping present in the map, while the 2D-ACVF method is particularly powerful in simply singling out the presence of order in the spot position from the complexity of the whole 2D map, i.e., spot trains. The procedures were validated by extensive numerical computation on computer-generated maps describing experimental 2D-PAGE gels of protein mixtures. Their applicability to real samples was tested on reference maps obtained from literature sources. The review describes the most relevant information for proteomics: sample complexity, separation performance, overlapping extent, identification of spot trains related to post-translational modifications (PTMs).

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

Elucidating Proteoform Families from Proteoform Intact-Mass and Lysine-Count Measurements

PubMed Central

2016-01-01

Proteomics is presently dominated by the “bottom-up” strategy, in which proteins are enzymatically digested into peptides for mass spectrometric identification. Although this approach is highly effective at identifying large numbers of proteins present in complex samples, the digestion into peptides renders it impossible to identify the proteoforms from which they were derived. We present here a powerful new strategy for the identification of proteoforms and the elucidation of proteoform families (groups of related proteoforms) from the experimental determination of the accurate proteoform mass and number of lysine residues contained. Accurate proteoform masses are determined by standard LC–MS analysis of undigested protein mixtures in an Orbitrap mass spectrometer, and the lysine count is determined using the NeuCode isotopic tagging method. We demonstrate the approach in analysis of the yeast proteome, revealing 8637 unique proteoforms and 1178 proteoform families. The elucidation of proteoforms and proteoform families afforded here provides an unprecedented new perspective upon proteome complexity and dynamics. PMID:26941048

Free Flow Zonal Electrophoresis for Fractionation of Plant Membrane Compartments Prior to Proteomic Analysis.

PubMed

Barkla, Bronwyn J

2018-01-01

Free flow zonal electrophoresis (FFZE) is a versatile, reproducible, and potentially high-throughput technique for the separation of plant organelles and membranes by differences in membrane surface charge. It offers considerable benefits over traditional fractionation techniques, such as density gradient centrifugation and two-phase partitioning, as it is relatively fast, sample recovery is high, and the method provides unparalleled sample purity. It has been used to successfully purify chloroplasts and mitochondria from plants but also, to obtain highly pure fractions of plasma membrane, tonoplast, ER, Golgi, and thylakoid membranes. Application of the technique can significantly improve protein coverage in large-scale proteomics studies by decreasing sample complexity. Here, we describe the method for the fractionation of plant cellular membranes from leaves by FFZE.

Global Analysis Reveals the Complexity of the Human Glomerular Extracellular Matrix

PubMed Central

Byron, Adam; Humphries, Jonathan D.; Randles, Michael J.; Carisey, Alex; Murphy, Stephanie; Knight, David; Brenchley, Paul E.; Zent, Roy; Humphries, Martin J.

2014-01-01

The glomerulus contains unique cellular and extracellular matrix (ECM) components, which are required for intact barrier function. Studies of the cellular components have helped to build understanding of glomerular disease; however, the full composition and regulation of glomerular ECM remains poorly understood. We used mass spectrometry-based proteomics of enriched ECM extracts for a global analysis of human glomerular ECM in vivo and identified a tissue-specific proteome of 144 structural and regulatory ECM proteins. This catalog includes all previously identified glomerular components plus many new and abundant components. Relative protein quantification showed a dominance of collagen IV, collagen I, and laminin isoforms in the glomerular ECM together with abundant collagen VI and TINAGL1. Protein network analysis enabled the creation of a glomerular ECM interactome, which revealed a core of highly connected structural components. More than one half of the glomerular ECM proteome was validated using colocalization studies and data from the Human Protein Atlas. This study yields the greatest number of ECM proteins relative to previous investigations of whole glomerular extracts, highlighting the importance of sample enrichment. It also shows that the composition of glomerular ECM is far more complex than previously appreciated and suggests that many more ECM components may contribute to glomerular development and disease processes. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000456. PMID:24436468

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

PubMed

Jarnuczak, Andrew F; Lee, Dave C H; Lawless, Craig; Holman, Stephen W; Eyers, Claire E; Hubbard, Simon J

2016-09-02

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

PubMed

Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

2017-08-01

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

Technical advances in proteomics: new developments in data-independent acquisition.

PubMed

Hu, Alex; Noble, William S; Wolf-Yadlin, Alejandro

2016-01-01

The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

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

PubMed Central

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

2015-01-01

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

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

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

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

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

Development of an Enhanced Metaproteomic Approach for Deepening the Microbiome Characterization of the Human Infant Gut

PubMed Central

2015-01-01

The establishment of early life microbiota in the human infant gut is highly variable and plays a crucial role in host nutrient availability/uptake and maturation of immunity. Although high-performance mass spectrometry (MS)-based metaproteomics is a powerful method for the functional characterization of complex microbial communities, the acquisition of comprehensive metaproteomic information in human fecal samples is inhibited by the presence of abundant human proteins. To alleviate this restriction, we have designed a novel metaproteomic strategy based on double filtering (DF) the raw samples, a method that fractionates microbial from human cells to enhance microbial protein identification and characterization in complex fecal samples from healthy premature infants. This method dramatically improved the overall depth of infant gut proteome measurement, with an increase in the number of identified low-abundance proteins and a greater than 2-fold improvement in microbial protein identification and quantification. This enhancement of proteome measurement depth enabled a more extensive microbiome comparison between infants by not only increasing the confidence of identified microbial functional categories but also revealing previously undetected categories. PMID:25350865

Microfluidics for the analysis of membrane proteins: how do we get there?

PubMed

Battle, Katrina N; Uba, Franklin I; Soper, Steven A

2014-08-01

The development of fully automated and high-throughput systems for proteomics is now in demand because of the need to generate new protein-based disease biomarkers. Unfortunately, it is difficult to identify protein biomarkers that are low abundant when in the presence of highly abundant proteins, especially in complex biological samples such as serum, cell lysates, and other biological fluids. Membrane proteins, which are in many cases of low abundance compared to the cytosolic proteins, have various functions and can provide insight into the state of a disease and serve as targets for new drugs making them attractive biomarker candidates. Traditionally, proteins are identified through the use of gel electrophoretic techniques, which are not always suitable for particular protein samples such as membrane proteins. Microfluidics offers the potential as a fully automated platform for the efficient and high-throughput analysis of complex samples, such as membrane proteins, and do so with performance metrics that exceed their bench-top counterparts. In recent years, there have been various improvements to microfluidics and their use for proteomic analysis as reported in the literature. Consequently, this review presents an overview of the traditional proteomic-processing pipelines for membrane proteins and insights into new technological developments with a focus on the applicability of microfluidics for the analysis of membrane proteins. Sample preparation techniques will be discussed in detail and novel interfacing strategies as it relates to MS will be highlighted. Lastly, some general conclusions and future perspectives are presented. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

NASA Astrophysics Data System (ADS)

Belov, Arseniy M.; Viner, Rosa; Santos, Marcia R.; Horn, David M.; Bern, Marshall; Karger, Barry L.; Ivanov, Alexander R.

2017-12-01

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). [Figure not available: see fulltext.

An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers.

PubMed

Yasui, Yutaka; McLerran, Dale; Adam, Bao-Ling; Winget, Marcy; Thornquist, Mark; Feng, Ziding

2003-01-01

Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein "signals" from background "noise" in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.

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

PubMed

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

2016-01-30

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

Proteomics Analysis of Skeletal Muscle from Leptin-Deficient ob/ob Mice Reveals Adaptive Remodeling of Metabolic Characteristics and Fiber Type Composition.

PubMed

Schönke, Milena; Björnholm, Marie; Chibalin, Alexander V; Zierath, Juleen R; Deshmukh, Atul S

2018-03-01

Skeletal muscle insulin resistance, an early metabolic defect in the pathogenesis of type 2 diabetes (T2D), may be a cause or consequence of altered protein expression profiles. Proteomics technology offers enormous promise to investigate molecular mechanisms underlying pathologies, however, the analysis of skeletal muscle is challenging. Using state-of-the-art multienzyme digestion and filter-aided sample preparation (MED-FASP) and a mass spectrometry (MS)-based workflow, we performed a global proteomics analysis of skeletal muscle from leptin-deficient, obese, insulin resistant (ob/ob) and lean mice in mere two fractions in a short time (8 h per sample). We identified more than 6000 proteins with 118 proteins differentially regulated in obesity. This included protein kinases, phosphatases, and secreted and fiber type associated proteins. Enzymes involved in lipid metabolism in skeletal muscle from ob/ob mice were increased, providing evidence against reduced fatty acid oxidation in lipid-induced insulin resistance. Mitochondrial and peroxisomal proteins, as well as components of pyruvate and lactate metabolism, were increased. Finally, the skeletal muscle proteome from ob/ob mice displayed a shift toward the "slow fiber type." This detailed characterization of an obese rodent model of T2D demonstrates an efficient workflow for skeletal muscle proteomics, which may easily be adapted to other complex tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advancing the global proteome survey platform by using an oriented single chain antibody fragment immobilization approach.

PubMed

Säll, Anna; Persson, Helena; Ohlin, Mats; Borrebaeck, Carl A K; Wingren, Christer

2016-09-25

Increasing the understanding of a proteome and how its protein composition is affected by for example different diseases, such as cancer, has the potential to improve strategies for early diagnosis and therapeutics. The Global Proteome Survey or GPS is a method that combines mass spectrometry and affinity enrichment with the use of antibodies. The technology enables profiling of complex proteomes in a species independent manner. The sensitivity of GPS, and other methods relying on affinity enrichment, is largely affected by the activity of the exploited affinity reagent. We here present an improvement of the GPS platform by utilizing an antibody immobilization approach which ensures a controlled immobilization process of the antibody to the magnetic bead support. More specifically, we make use of an antibody format that enables site-directed biotinylation and use this in combination with streptavidin coated magnetic beads. The performance of the expanded GPS platform was evaluated by profiling yeast proteome samples. We demonstrate that the oriented antibody immobilization strategy increases the ability of the GPS platform and results in larger fraction of functional antibodies. Additionally, we show that this new antibody format enabled in-solution capture, i.e. immobilization of the antibodies after sample incubation. A workflow has been established that permit the use of an oriented immobilization strategy for the GPS platform. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

PubMed

Ma, Hongyan; Delafield, Daniel G; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ᅟ.

Proteomic analysis of corneal endothelial cell-descemet membrane tissues reveals influence of insulin dependence and disease severity in type 2 diabetes mellitus.

PubMed

Skeie, Jessica M; Aldrich, Benjamin T; Goldstein, Andrew S; Schmidt, Gregory A; Reed, Cynthia R; Greiner, Mark A

2018-01-01

The objective of this study was to characterize the proteome of the corneal endothelial cell layer and its basement membrane (Descemet membrane) in humans with various severities of type II diabetes mellitus compared to controls, and identify differentially expressed proteins across a range of diabetic disease severities that may influence corneal endothelial cell health. Endothelium-Descemet membrane complex tissues were peeled from transplant suitable donor corneas. Protein fractions were isolated from each sample and subjected to multidimensional liquid chromatography and tandem mass spectrometry. Peptide spectra were matched to the human proteome, assigned gene ontology, and grouped into protein signaling pathways unique to each of the disease states. We identified an average of 12,472 unique proteins in each of the endothelium-Descemet membrane complex tissue samples. There were 2,409 differentially expressed protein isoforms that included previously known risk factors for type II diabetes mellitus related to metabolic processes, oxidative stress, and inflammation. Gene ontology analysis demonstrated that diabetes progression has many protein footprints related to metabolic processes, binding, and catalysis. The most represented pathways involved in diabetes progression included mitochondrial dysfunction, cell-cell junction structure, and protein synthesis regulation. This proteomic dataset identifies novel corneal endothelial cell and Descemet membrane protein expression in various stages of diabetic disease. These findings give insight into the mechanisms involved in diabetes progression relevant to the corneal endothelium and its basement membrane, prioritize new pathways for therapeutic targeting, and provide insight into potential biomarkers for determining the health of this tissue.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP)

NASA Astrophysics Data System (ADS)

Ma, Hongyan; Delafield, Daniel G.; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion.

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.

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.

Hydroponics on a chip: analysis of the Fe deficient Arabidopsis thylakoid membrane proteome.

PubMed

Laganowsky, Arthur; Gómez, Stephen M; Whitelegge, Julian P; Nishio, John N

2009-04-13

The model plant Arabidopsis thaliana was used to evaluate the thylakoid membrane proteome under Fe-deficient conditions. Plants were cultivated using a novel hydroponic system, called "hydroponics on a chip", which yields highly reproducible plant tissue samples for physiological analyses, and can be easily used for in vivo stable isotope labeling. The thylakoid membrane proteome, from intact chloroplasts isolated from Fe-sufficient and Fe-deficient plants grown with hydroponics on a chip, was analyzed using liquid chromatography coupled to mass spectrometry. Intact masses of thylakoid membrane proteins were measured, many for the first time, and several proteins were identified with post-translational modifications that were altered by Fe deficiency; for example, the doubly phosphorylated form of the photosystem II oxygen evolving complex, PSBH, increased under Fe-deficiency. Increased levels of photosystem II protein subunit PSBS were detected in the Fe-deficient samples. Antioxidant enzymes, including ascorbate peroxidase and peroxiredoxin Q, were only detected in the Fe-deficient samples. We present the first biochemical evidence that the two major LHC IIb proteins (LHCB1 and LHCB2) may have significantly different functions in the thylakoid membrane. The study illustrates the utility of intact mass proteomics as an indispensable tool for functional genomics. "Hydroponics on a chip" provides the ability to grow A. thaliana under defined conditions that will be useful for systems biology.

Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry.

PubMed

Planatscher, Hannes; Supper, Jochen; Poetz, Oliver; Stoll, Dieter; Joos, Thomas; Templin, Markus F; Zell, Andreas

2010-06-25

Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry.

PubMed

Zhao, Yan; Chang, Cheng; Qin, Peibin; Cao, Qichen; Tian, Fang; Jiang, Jing; Li, Xianyu; Yu, Wenfeng; Zhu, Yunping; He, Fuchu; Ying, Wantao; Qian, Xiaohong

2016-01-21

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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

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

2016-05-03

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

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2017-06-06

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3-10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7-20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

Proteomic analysis of human aqueous humor using multidimensional protein identification technology

PubMed Central

Richardson, Matthew R.; Price, Marianne O.; Price, Francis W.; Pardo, Jennifer C.; Grandin, Juan C.; You, Jinsam; Wang, Mu

2009-01-01

Aqueous humor (AH) supports avascular tissues in the anterior segment of the eye, maintains intraocular pressure, and potentially influences the pathogenesis of ocular diseases. Nevertheless, the AH proteome is still poorly defined despite several previous efforts, which were hindered by interfering high abundance proteins, inadequate animal models, and limited proteomic technologies. To facilitate future investigations into AH function, the AH proteome was extensively characterized using an advanced proteomic approach. Samples from patients undergoing cataract surgery were pooled and depleted of interfering abundant proteins and thereby divided into two fractions: albumin-bound and albumin-depleted. Multidimensional Protein Identification Technology (MudPIT) was utilized for each fraction; this incorporates strong cation exchange chromatography to reduce sample complexity before reversed-phase liquid chromatography and tandem mass spectrometric analysis. Twelve proteins had multi-peptide, high confidence identifications in the albumin-bound fraction and 50 proteins had multi-peptide, high confidence identifications in the albumin-depleted fraction. Gene ontological analyses were performed to determine which cellular components and functions were enriched. Many proteins were previously identified in the AH and for several their potential role in the AH has been investigated; however, the majority of identified proteins were novel and only speculative roles can be suggested. The AH was abundant in anti-oxidant and immunoregulatory proteins as well as anti-angiogenic proteins, which may be involved in maintaining the avascular tissues. This is the first known report to extensively characterize and describe the human AH proteome and lays the foundation for future work regarding its function in homeostatic and pathologic states. PMID:20019884

Highly efficient peptide separations in proteomics Part 1. Unidimensional high performance liquid chromatography.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Verleysen, Katleen; Kas, Koen; Sandra, Pat

2008-04-15

Sample complexity and dynamic range constitute enormous challenges in proteome analysis. The back-end technology in typical proteomics platforms, namely mass spectrometry (MS), can only tolerate a certain complexity, has a limited dynamic range per spectrum and is very sensitive towards ion suppression. Therefore, component overlap has to be minimized for successful mass spectrometric analysis and subsequent protein identification and quantification. The present review describes the advances that have been made in liquid-based separation techniques with focus on the recent developments to boost the resolving power. The review is divided in two parts; the first part deals with unidimensional liquid chromatography and the second part with bi- and multidimensional liquid-based separation techniques. Part 1 mainly focuses on reversed-phase HPLC due to the fact that it is and will, in the near future, remain the technique of choice to be hyphenated with MS. The impact of increasing the column length, decreasing the particle diameter, replacing the traditional packed beds by monolithics, amongst others, is described. The review is complemented with data obtained in the laboratories of the authors.

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes

PubMed Central

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-01-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)1 not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. PMID:27215607

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes.

PubMed

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-08-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)(1) not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-11-01

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

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges - A review.

PubMed

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-06-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes.

Separomics applied to the proteomics and peptidomics of low-abundance proteins: Choice of methods and challenges – A review

PubMed Central

Baracat-Pereira, Maria Cristina; de Oliveira Barbosa, Meire; Magalhães, Marcos Jorge; Carrijo, Lanna Clicia; Games, Patrícia Dias; Almeida, Hebréia Oliveira; Sena Netto, José Fabiano; Pereira, Matheus Rodrigues; de Barros, Everaldo Gonçalves

2012-01-01

The enrichment and isolation of proteins are considered limiting steps in proteomic studies. Identification of proteins whose expression is transient, those that are of low-abundance, and of natural peptides not described in databases, is still a great challenge. Plant extracts are in general complex, and contaminants interfere with the identification of proteins involved in important physiological processes, such as plant defense against pathogens. This review discusses the challenges and strategies of separomics applied to the identification of low-abundance proteins and peptides in plants, especially in plants challenged by pathogens. Separomics is described as a group of methodological strategies for the separation of protein molecules for proteomics. Several tools have been used to remove highly abundant proteins from samples and also non-protein contaminants. The use of chromatographic techniques, the partition of the proteome into subproteomes, and an effort to isolate proteins in their native form have allowed the isolation and identification of rare proteins involved in different processes. PMID:22802713

Proteome complexity and the forces that drive proteome imbalance.

PubMed

Harper, J Wade; Bennett, Eric J

2016-09-15

The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer.

Statistical Analysis of Variation in the Human Plasma Proteome

DOE PAGES

Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; ...

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where onemore » human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.« less

Statistical analysis of variation in the human plasma proteome.

PubMed

Corzett, Todd H; Fodor, Imola K; Choi, Megan W; Walsworth, Vicki L; Turteltaub, Kenneth W; McCutchen-Maloney, Sandra L; Chromy, Brett A

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Proteogenomic strategies for identification of aberrant cancer peptides using large-scale Next Generation Sequencing data

DOE PAGES

Woo, Sunghee; Cha, Seong Won; Na, Seungjin; ...

2014-11-17

Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, and the discovery of novel biomarkers. The availability of genomics technologies (mainly wholegenome and exome sequencing, and transcript sampling via RNA-seq, collectively referred to as NGS) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome using only genomic approaches. Recently, combination of proteomic and genomic technologies are increasingly employed. However, the complexity and redundancymore » of NGS data remains a challenge for proteogenomics, and various trade-offs must be made to allow for the searches to take place. This paperprovides a discussion of two such trade-offs, relating to large database search, and FDR calculations, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2,787,062 novel splice junctions, 38,464 deletions, 1105 insertions, and 182,302 substitutions. Proteomic data from a single ovarian carcinoma sample (439,858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65,578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.« less

A chronic fatigue syndrome – related proteome in human cerebrospinal fluid

PubMed Central

Baraniuk, James N; Casado, Begona; Maibach, Hilda; Clauw, Daniel J; Pannell, Lewis K; Hess S, Sonja

2005-01-01

Background Chronic Fatigue Syndrome (CFS), Persian Gulf War Illness (PGI), and fibromyalgia are overlapping symptom complexes without objective markers or known pathophysiology. Neurological dysfunction is common. We assessed cerebrospinal fluid to find proteins that were differentially expressed in this CFS-spectrum of illnesses compared to control subjects. Methods Cerebrospinal fluid specimens from 10 CFS, 10 PGI, and 10 control subjects (50 μl/subject) were pooled into one sample per group (cohort 1). Cohort 2 of 12 control and 9 CFS subjects had their fluids (200 μl/subject) assessed individually. After trypsin digestion, peptides were analyzed by capillary chromatography, quadrupole-time-of-flight mass spectrometry, peptide sequencing, bioinformatic protein identification, and statistical analysis. Results Pooled CFS and PGI samples shared 20 proteins that were not detectable in the pooled control sample (cohort 1 CFS-related proteome). Multilogistic regression analysis (GLM) of cohort 2 detected 10 proteins that were shared by CFS individuals and the cohort 1 CFS-related proteome, but were not detected in control samples. Detection of ≥1 of a select set of 5 CFS-related proteins predicted CFS status with 80% concordance (logistic model). The proteins were α-1-macroglobulin, amyloid precursor-like protein 1, keratin 16, orosomucoid 2 and pigment epithelium-derived factor. Overall, 62 of 115 proteins were newly described. Conclusion This pilot study detected an identical set of central nervous system, innate immune and amyloidogenic proteins in cerebrospinal fluids from two independent cohorts of subjects with overlapping CFS, PGI and fibromyalgia. Although syndrome names and definitions were different, the proteome and presumed pathological mechanism(s) may be shared. PMID:16321154

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 elemental) proteomics is provided in this review. © 2017 Wiley Periodicals, Inc.

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.

Microbial Interactions in Plants: Perspectives and Applications of Proteomics.

PubMed

Imam, Jahangir; Shukla, Pratyoosh; Mandal, Nimai Prasad; Variar, Mukund

2017-01-01

The structure and function of proteins involved in plant-microbe interactions is investigated through large-scale proteomics technology in a complex biological sample. Since the whole genome sequences are now available for several plant species and microbes, proteomics study has become easier, accurate and huge amount of data can be generated and analyzed during plant-microbe interactions. Proteomics approaches are highly important and relevant in many studies and showed that only genomics approaches are not sufficient enough as much significant information are lost as the proteins and not the genes coding them are final product that is responsible for the observed phenotype. Novel approaches in proteomics are developing continuously enabling the study of the various aspects in arrangements and configuration of proteins and its functions. Its application is becoming more common and frequently used in plant-microbe interactions with the advancement in new technologies. They are more used for the portrayal of cell and extracellular destructiveness and pathogenicity variables delivered by pathogens. This distinguishes the protein level adjustments in host plants when infected with pathogens and advantageous partners. This review provides a brief overview of different proteomics technology which is currently available followed by their exploitation to study the plant-microbe interaction. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Proteomics Is Analytical Chemistry: Fitness-for-Purpose in the Application of Top-Down and Bottom-Up Analyses.

PubMed

Coorssen, Jens R; Yergey, Alfred L

2015-12-03

Molecular mechanisms underlying health and disease function at least in part based on the flexibility and fine-tuning afforded by protein isoforms and post-translational modifications. The ability to effectively and consistently resolve these protein species or proteoforms, as well as assess quantitative changes is therefore central to proteomic analyses. Here we discuss the pros and cons of currently available and developing analytical techniques from the perspective of the full spectrum of available tools and their current applications, emphasizing the concept of fitness-for-purpose in experimental design based on consideration of sample size and complexity; this necessarily also addresses analytical reproducibility and its variance. Data quality is considered the primary criterion, and we thus emphasize that the standards of Analytical Chemistry must apply throughout any proteomic analysis.

High-field asymmetric waveform ion mobility spectrometry for mass spectrometry-based proteomics.

PubMed

Swearingen, Kristian E; Moritz, Robert L

2012-10-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve the detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, the authors review recent developments in LC-FAIMS-MS and its application to MS-based proteomics.

Proteomic analysis of enterotoxigenic Escherichia coli (ETEC) in neutral and alkaline conditions.

PubMed

Gonzales-Siles, Lucia; Karlsson, Roger; Kenny, Diarmuid; Karlsson, Anders; Sjöling, Åsa

2017-01-07

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea in children and travelers to endemic areas. Secretion of the heat labile AB 5 toxin (LT) is induced by alkaline conditions. In this study, we determined the surface proteome of ETEC exposed to alkaline conditions (pH 9) as compared to neutral conditions (pH 7) using a LPI Hexalane FlowCell combined with quantitative proteomics. Relative quantitation with isobaric labeling (TMT) was used to compare peptide abundance and their corresponding proteins in multiple samples at MS/MS level. For protein identification and quantification samples were analyzed using either a 1D-LCMS or a 2D-LCMS approach. Strong up-regulation of the ATP synthase operon encoding F1Fo ATP synthase and down-regulation of proton pumping proteins NuoF, NuoG, Ndh and WrbA were detected among proteins involved in regulating the proton and electron transport under alkaline conditions. Reduced expression of proteins involved in osmotic stress was found at alkaline conditions while the Sec-dependent transport over the inner membrane and outer membrane protein proteins such as OmpA and the β-Barrel Assembly Machinery (BAM) complex were up-regulated. ETEC exposed to alkaline environments express a specific proteome profile characterized by up-regulation of membrane proteins and secretion of LT toxin. Alkaline microenvironments have been reported close to the intestinal epithelium and the alkaline proteome may hence represent a better view of ETEC during infection.

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

PubMed

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

2018-06-09

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

Proteome complexity and the forces that drive proteome imbalance

PubMed Central

Harper, J. Wade; Bennett, Eric J.

2016-01-01

Summary The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer. PMID:27629639

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

Waldbauer, J.; Zhang, L.; Rizzo, A. I.

2015-12-01

Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

The hydroxyl-functionalized magnetic particles for purification of glycan-binding proteins.

PubMed

Sun, Xiuxuan; Yang, Ganglong; Sun, Shisheng; Quan, Rui; Dai, Weiwei; Li, Bin; Chen, Chao; Li, Zheng

2009-12-01

Glycan-protein interactions play important biological roles in biological processes. Although there are some methods such as glycan arrays that may elucidate recognition events between carbohydrates and protein as well as screen the important glycan-binding proteins, there is a lack of simple effectively separate method to purify them from complex samples. In proteomics studies, fractionation of samples can help to reduce their complexity and to enrich specific classes of proteins for subsequent downstream analyses. Herein, a rapid simple method for purification of glycan-binding proteins from proteomic samples was developed using hydroxyl-coated magnetic particles coupled with underivatized carbohydrate. Firstly, the epoxy-coated magnetic particles were further hydroxyl functionalized with 4-hydroxybenzhydrazide, then the carbohydrates were efficiently immobilized on hydroxyl functionalized surface of magnetic particles by formation of glycosidic bond with the hemiacetal group at the reducing end of the suitable carbohydrates via condensation. All conditions of this method were optimized. The magnetic particle-carbohydrate conjugates were used to purify the glycan-binding proteins from human serum. The fractionated glycan-binding protein population was displayed by SDS-PAGE. The result showed that the amount of 1 mg magnetic particles coupled with mannose in acetate buffer (pH 5.4) was 10 micromol. The fractionated glycan-binding protein population in human serum could be eluted from the magnetic particle-mannose conjugates by 0.1% SDS. The methodology could work together with the glycan microarrays for screening and purification of the important GBPs from complex protein samples.

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

PubMed Central

2011-01-01

Background Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology. Result We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site. This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser. Conclusions Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html PMID:21414234

Integrated Blood Barcode Chips

PubMed Central

Fan, Rong; Vermesh, Ophir; Srivastava, Alok; Yen, Brian K.H.; Qin, Lidong; Ahmad, Habib; Kwong, Gabriel A.; Liu, Chao-Chao; Gould, Juliane; Hood, Leroy; Heath, James R.

2008-01-01

Blood comprises the largest version of the human proteome1. Changes of plasma protein profiles can reflect physiological or pathological conditions associated with many human diseases, making blood the most important fluid for clinical diagnostics2-4. Nevertheless, only a handful of plasma proteins are utilized in routine clinical tests. This is due to a host of reasons, including the intrinsic complexity of the plasma proteome1, the heterogeneity of human diseases and the fast kinetics associated with protein degradation in sampled blood5. Simple technologies that can sensitively sample large numbers of proteins over broad concentration ranges, from small amounts of blood, and within minutes of sample collection, would assist in solving these problems. Herein, we report on an integrated microfluidic system, called the Integrated Blood Barcode Chip (IBBC). It enables on-chip blood separation and the rapid measurement of a panel of plasma proteins from small quantities of blood samples including a fingerprick of whole blood. This platform holds potential for inexpensive, non-invasive, and informative clinical diagnoses, particularly, for point-of-care. PMID:19029914

Functional protease profiling for diagnosis of malignant disease.

PubMed

Findeisen, Peter; Neumaier, Michael

2012-01-01

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ABRF-PRG07: advanced quantitative proteomics study.

PubMed

Falick, Arnold M; Lane, William S; Lilley, Kathryn S; MacCoss, Michael J; Phinney, Brett S; Sherman, Nicholas E; Weintraub, Susan T; Witkowska, H Ewa; Yates, Nathan A

2011-04-01

A major challenge for core facilities is determining quantitative protein differences across complex biological samples. Although there are numerous techniques in the literature for relative and absolute protein quantification, the majority is nonroutine and can be challenging to carry out effectively. There are few studies comparing these technologies in terms of their reproducibility, accuracy, and precision, and no studies to date deal with performance across multiple laboratories with varied levels of expertise. Here, we describe an Association of Biomolecular Resource Facilities (ABRF) Proteomics Research Group (PRG) study based on samples composed of a complex protein mixture into which 12 known proteins were added at varying but defined ratios. All of the proteins were present at the same concentration in each of three tubes that were provided. The primary goal of this study was to allow each laboratory to evaluate its capabilities and approaches with regard to: detection and identification of proteins spiked into samples that also contain complex mixtures of background proteins and determination of relative quantities of the spiked proteins. The results returned by 43 participants were compiled by the PRG, which also collected information about the strategies used to assess overall performance and as an aid to development of optimized protocols for the methodologies used. The most accurate results were generally reported by the most experienced laboratories. Among laboratories that used the same technique, values that were closer to the expected ratio were obtained by more experienced groups.

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

PubMed

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

2016-06-03

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

Bovine milk proteome in the first 9 days: protein interactions in maturation of the immune and digestive system of the newborn.

PubMed

Zhang, Lina; Boeren, Sjef; Hageman, Jos A; van Hooijdonk, Toon; Vervoort, Jacques; Hettinga, Kasper

2015-01-01

In order to better understand the milk proteome and its changes from colostrum to mature milk, samples taken at seven time points in the first 9 days from 4 individual cows were analyzed using proteomic techniques. Both the similarity in changes from day 0 to day 9 in the quantitative milk proteome, and the differences in specific protein abundance, were observed among four cows. One third of the quantified proteins showed a significant decrease in concentration over the first 9 days after calving, especially in the immune proteins (as much as 40 fold). Three relative high abundant enzymes (XDH, LPL, and RNASE1) and cell division and proliferation protein (CREG1) may be involved in the maturation of the gastro-intestinal tract. In addition, high correlations between proteins involved in complement and blood coagulation cascades illustrates the complex nature of biological interrelationships between milk proteins. The linear decrease of protease inhibitors and proteins involved in innate and adaptive immune system implies a protective role for protease inhibitor against degradation. In conclusion, the results found in this study not only improve our understanding of the role of colostrum in both host defense and development of the newborn calf but also provides guidance for the improvement of infant formula through better understanding of the complex interactions between milk proteins.

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes

NASA Astrophysics Data System (ADS)

Li, Huilin; Nguyen, Hong Hanh; Ogorzalek Loo, Rachel R.; Campuzano, Iain D. G.; Loo, Joseph A.

2018-02-01

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation.

Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma.

PubMed

O'Grady, John P; Meyer, Kevin W; Poe, Derrick N

2017-01-01

The improving efficacy of many biological therapeutics and identification of low-level biomarkers are driving the analytical proteomics community to deal with extremely high levels of sample complexity relative to their analytes. Many protein quantitation and biomarker validation procedures utilize an immunoaffinity enrichment step to purify the sample and maximize the sensitivity of the corresponding liquid chromatography tandem mass spectrometry measurements. In order to generate surrogate peptides with better mass spectrometric properties, protein enrichment is followed by a proteolytic cleavage step. This is often a time-consuming multistep process. Presented here is a workflow which enables rapid protein enrichment and proteolytic cleavage to be performed in a single, easy-to-use reactor. Using this strategy Klotho, a low-abundance biomarker found in plasma, can be accurately quantitated using a protocol that takes under 5 h from start to finish.

Single-cell proteomics: potential implications for cancer diagnostics.

PubMed

Gavasso, Sonia; Gullaksen, Stein-Erik; Skavland, Jørn; Gjertsen, Bjørn T

2016-01-01

Single-cell proteomics in cancer is evolving and promises to provide more accurate diagnoses based on detailed molecular features of cells within tumors. This review focuses on technologies that allow for collection of complex data from single cells, but also highlights methods that are adaptable to routine cancer diagnostics. Current diagnostics rely on histopathological analysis, complemented by mutational detection and clinical imaging. Though crucial, the information gained is often not directly transferable to defined therapeutic strategies, and predicting therapy response in a patient is difficult. In cancer, cellular states revealed through perturbed intracellular signaling pathways can identify functional mutations recurrent in cancer subsets. Single-cell proteomics remains to be validated in clinical trials where serial samples before and during treatment can reveal excessive clonal evolution and therapy failure; its use in clinical trials is anticipated to ignite a diagnostic revolution that will better align diagnostics with the current biological understanding of cancer.

High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) for Mass Spectrometry-Based Proteomics

PubMed Central

Swearingen, Kristian E.; Moritz, Robert L.

2013-01-01

SUMMARY High field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, we review recent developments in LC-FAIMS-MS and its application to MS-based proteomics. PMID:23194268

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.

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 other microbes used in this study were clearly identified above the background when analyzed with the large database. This study points to the potential application of this technology for biological threat agent detection but highlights many areas of needed research before the technology will be useful in real world samples.

Quantitative proteomic characterization of redox-dependent post-translational modifications on protein cysteines

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

Duan, Jicheng; Gaffrey, Matthew J.; Qian, Wei-Jun

Protein cysteine thiols play a crucial role in redox signaling, regulation of enzymatic activity and protein function, and maintaining redox homeostasis in living systems. The unique chemical reactivity of thiol groups makes cysteine susceptible to oxidative modifications by reactive oxygen and nitrogen species to form a broad array of reversible and irreversible protein post-translational modifications (PTMs). The reversible modifications in particular are one of the major components of redox signaling and are involved in regulation of various cellular processes under physiological and pathological conditions. The biological significance of these redox PTMs in health and diseases has been increasingly recognized. Herein,more » we review the recent advances of quantitative proteomic approaches for investigating redox PTMs in complex biological systems, including the general considerations of sample processing, various chemical or affinity enrichment strategies, and quantitative approaches. We also highlight a number of redox proteomic approaches that enable effective profiling of redox PTMs for addressing specific biological questions. Although some technological limitations remain, redox proteomics is paving the way towards a better understanding of redox signaling and regulation in human health and diseases.« less

Streptococcus pyogenes Infection and the Human Proteome with a Special Focus on the Immunoglobulin G-cleaving Enzyme IdeS.

PubMed

Karlsson, Christofer A Q; Järnum, Sofia; Winstedt, Lena; Kjellman, Christian; Björck, Lars; Linder, Adam; Malmström, Johan A

2018-06-01

Infectious diseases are characterized by a complex interplay between host and pathogen, but how these interactions impact the host proteome is unclear. Here we applied a combined mass spectrometry-based proteomics strategy to investigate how the human proteome is transiently modified by the pathogen Streptococcus pyogenes , with a particular focus on bacterial cleavage of IgG in vivo In invasive diseases, S. pyogenes evokes a massive host response in blood, whereas superficial diseases are characterized by a local leakage of several blood plasma proteins at the site of infection including IgG. S. pyogenes produces IdeS, a protease cleaving IgG in the lower hinge region and we find highly effective IdeS-cleavage of IgG in samples from local IgG poor microenvironments. The results show that IdeS contributes to the adaptation of S. pyogenes to its normal ecological niches. Additionally, the work identifies novel clinical opportunities for in vivo pathogen detection. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

The amino acid's backup bone - storage solutions for proteomics facilities.

PubMed

Meckel, Hagen; Stephan, Christian; Bunse, Christian; Krafzik, Michael; Reher, Christopher; Kohl, Michael; Meyer, Helmut Erich; Eisenacher, Martin

2014-01-01

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013. Published by Elsevier B.V.

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won

2016-12-06

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

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

PubMed

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

2015-01-01

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

Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio)

PubMed Central

Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V.; Bobe, Julien

2017-01-01

Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine. PMID:29145436

Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio).

PubMed

Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V; Bobe, Julien

2017-01-01

Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine.

Deletion of Cysteine Cathepsins B or L Yields Differential Impacts on Murine Skin Proteome and Degradome*

PubMed Central

Tholen, Stefan; Biniossek, Martin L.; Gansz, Martina; Gomez-Auli, Alejandro; Bengsch, Fee; Noel, Agnes; Kizhakkedathu, Jayachandran N.; Boerries, Melanie; Busch, Hauke; Reinheckel, Thomas; Schilling, Oliver

2013-01-01

Numerous studies highlight the fact that concerted proteolysis is essential for skin morphology and function. The cysteine protease cathepsin L (Ctsl) has been implicated in epidermal proliferation and desquamation, as well as in hair cycle regulation. In stark contrast, mice deficient in cathepsin B (Ctsb) do not display an overt skin phenotype. To understand the systematic consequences of deleting Ctsb or Ctsl, we determined the protein abundances of >1300 proteins and proteolytic cleavage events in skin samples of wild-type, Ctsb−/−, and Ctsl−/− mice via mass-spectrometry-based proteomics. Both protease deficiencies revealed distinct quantitative changes in proteome composition. Ctsl−/− skin revealed increased levels of the cysteine protease inhibitors cystatin B and cystatin M/E, increased cathepsin D, and an accumulation of the extracellular glycoprotein periostin. Immunohistochemistry located periostin predominantly in the hypodermal connective tissue of Ctsl−/− skin. The proteomic identification of proteolytic cleavage sites within skin proteins revealed numerous processing sites that are underrepresented in Ctsl−/− or Ctsb−/− samples. Notably, few of the affected cleavage sites shared the canonical Ctsl or Ctsb specificity, providing further evidence of a complex proteolytic network in the skin. Novel processing sites in proteins such as dermokine and Notch-1 were detected. Simultaneous analysis of acetylated protein N termini showed prototypical mammalian N-alpha acetylation. These results illustrate an influence of both Ctsb and Ctsl on the murine skin proteome and degradome, with the phenotypic consequences of the absence of either protease differing considerably. PMID:23233448

Recent advances and opportunities in proteomic analyses of tumour heterogeneity.

PubMed

Bateman, Nicholas W; Conrads, Thomas P

2018-04-01

Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA).

PubMed

Chaturvedi, Palak; Doerfler, Hannes; Jegadeesan, Sridharan; Ghatak, Arindam; Pressman, Etan; Castillejo, Maria Angeles; Wienkoop, Stefanie; Egelhofer, Volker; Firon, Nurit; Weckwerth, Wolfram

2015-11-06

Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC-MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC-MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.

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

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525

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

PubMed

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

2013-12-01

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

Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology.

PubMed

Wesseling, Hendrik; Guest, Paul C; Lago, Santiago G; Bahn, Sabine

2014-08-01

Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

A novel proteomics sample preparation method for secretome analysis of Hypocrea jecorina growing on insoluble substrates.

PubMed

Bengtsson, Oskar; Arntzen, Magnus Ø; Mathiesen, Geir; Skaugen, Morten; Eijsink, Vincent G H

2016-01-10

Analysis of the secretomes of filamentous fungi growing on insoluble lignocellulosic substrates is of major current interest because of the industrial potential of secreted fungal enzymes. Importantly, such studies can help identifying key enzymes from a large arsenal of bioinformatically detected candidates in fungal genomes. We describe a simple, plate-based method to analyze the secretome of Hypocrea jecorina growing on insoluble substrates that allows harsh sample preparation methods promoting desorption, and subsequent identification, of substrate-bound proteins, while minimizing contamination with non-secreted proteins from leaking or lysed cells. The validity of the method was demonstrated by comparative secretome analysis of wild-type H.jecorina strain QM6a growing on bagasse, birch wood, spruce wood or pure cellulose, using label-fee quantification. The proteomic data thus obtained were consistent with existing data from transcriptomics and proteomics studies and revealed clear differences in the responses to complex lignocellulosic substrates and the response to pure cellulose. This easy method is likely to be generally applicable to filamentous fungi and to other microorganisms growing on insoluble substrates. Copyright © 2015 Elsevier B.V. All rights reserved.

Absolute quantification of Dehalococcoides proteins: enzyme bioindicators of chlorinated ethene dehalorespiration.

PubMed

Werner, Jeffrey J; Ptak, A Celeste; Rahm, Brian G; Zhang, Sheng; Richardson, Ruth E

2009-10-01

The quantification of trace proteins in complex environmental samples and mixed microbial communities would be a valuable monitoring tool in countless applications, including the bioremediation of groundwater contaminated with chlorinated solvents. Measuring the concentrations of specific proteins provides unique information about the activity and physiological state of organisms in a sample. We developed sensitive (< 5 fmol), selective bioindicator assays for the absolute quantification of select proteins used by Dehalococcoides spp. when reducing carbon atoms in the common pollutants trichloroethene (TCE) and tetrachloroethene (PCE). From complex whole-sample digests of two different dechlorinating mixed communities, we monitored the chromatographic peaks of selected tryptic peptides chosen to represent 19 specific Dehalococcoides proteins. This was accomplished using multiple-reaction monitoring (MRM) assays using nano-liquid chromatography-tandem mass spectrometry (nLC-MS/MS), which provided the selectivity, sensitivity and reproducibility required to quantify Dehalococcoides proteins in complex samples. We observed reproducible peak areas (average CV = 0.14 over 4 days, n = 3) and linear responses in standard curves (n = 5, R(2) > 0.98) using synthetic peptide standards spiked into a background matrix of sediment peptides. We detected and quantified TCE reductive dehalogenase (TceA) at 7.6 +/- 1.7 x 10(3) proteins cell(-1) in the KB1 bioaugmentation culture, previously thought to be lacking TceA. Fragmentation data from MS/MS shotgun proteomics experiments were helpful in developing the MRM targets. Similar shotgun proteomics data are emerging in labs around the world for many environmentally relevant microbial proteins, and these data are a valuable resource for the future development of MRM assays. We expect targeted peptide quantification in environmental samples to be a useful tool in environmental monitoring.

Tools for phospho- and glycoproteomics of plasma membranes.

PubMed

Wiśniewski, Jacek R

2011-07-01

Analysis of plasma membrane proteins and their posttranslational modifications is considered as important for identification of disease markers and targets for drug treatment. Due to their insolubility in water, studying of plasma membrane proteins using mass spectrometry has been difficult for a long time. Recent technological developments in sample preparation together with important improvements in mass spectrometric analysis have facilitated analysis of these proteins and their posttranslational modifications. Now, large scale proteomic analyses allow identification of thousands of membrane proteins from minute amounts of sample. Optimized protocols for affinity enrichment of phosphorylated and glycosylated peptides have set new dimensions in the depth of characterization of these posttranslational modifications of plasma membrane proteins. Here, I summarize recent advances in proteomic technology for the characterization of the cell surface proteins and their modifications. In the focus are approaches allowing large scale mapping rather than analytical methods suitable for studying individual proteins or non-complex mixtures.

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

PubMed

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

2017-01-06

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

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

PubMed

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

2011-12-10

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

New Funding Opportunity Announcements (FOAs): Reissuance of Clinical Proteomic Tumor Analysis Consortium (CPTAC) | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute is soliciting applications for the reissuance of its Clinical Proteomic Tumor Analysis Consortium (CPTAC) program.   CPTAC will support broad efforts focused on several cancer types to explore further the complexities of cancer proteomes and their connections to abnormalities in cancer genomes.

CPTC and KIST Join Efforts to Solve Complex Proteomic Issues | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's (NCI) Clinical Proteomic Technologies for Cancer (CPTC) initiative at the National Institutes of Health has entered into a memorandum of understanding (MOU) with the Korea Institute of Science and Technology (KIST). This MOU promotes proteomic technology optimization and standards implementation in large-scale international programs.

Reference Proteome Extracts for Mass Spec Instrument Performance Validation and Method Development

PubMed Central

Rosenblatt, Mike; Urh, Marjeta; Saveliev, Sergei

2014-01-01

Biological samples of high complexity are required to test protein mass spec sample preparation procedures and validate mass spec instrument performance. Total cell protein extracts provide the needed sample complexity. However, to be compatible with mass spec applications, such extracts should meet a number of design requirements: compatibility with LC/MS (free of detergents, etc.)high protein integrity (minimal level of protein degradation and non-biological PTMs)compatibility with common sample preparation methods such as proteolysis, PTM enrichment and mass-tag labelingLot-to-lot reproducibility Here we describe total protein extracts from yeast and human cells that meet the above criteria. Two extract formats have been developed: Intact protein extracts with primary use for sample preparation method development and optimizationPre-digested extracts (peptides) with primary use for instrument validation and performance monitoring

Proteomic technology for biomarker profiling in cancer: an update*

PubMed Central

Alaoui-Jamali, Moulay A.; Xu, Ying-jie

2006-01-01

The progress in the understanding of cancer progression and early detection has been slow and frustrating due to the complex multifactorial nature and heterogeneity of the cancer syndrome. To date, no effective treatment is available for advanced cancers, which remain a major cause of morbidity and mortality. Clearly, there is urgent need to unravel novel biomarkers for early detection. Most of the functional information of the cancer-associated genes resides in the proteome. The later is an exceptionally complex biological system involving several proteins that function through posttranslational modifications and dynamic intermolecular collisions with partners. These protein complexes can be regulated by signals emanating from cancer cells, their surrounding tissue microenvironment, and/or from the host. Some proteins are secreted and/or cleaved into the extracellular milieu and may represent valuable serum biomarkers for diagnosis purpose. It is estimated that the cancer proteome may include over 1.5 million proteins as a result of posttranslational processing and modifications. Such complexity clearly highlights the need for ultra-high resolution proteomic technology for robust quantitative protein measurements and data acquisition. This review is to update the current research efforts in high-resolution proteomic technology for discovery and monitoring cancer biomarkers. PMID:16625706

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

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

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

2012-03-10

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

Deciphering the complexities of the wheat flour proteome using quantitative two-dimensional electrophoresis, three proteases and tandem mass spectrometry

USDA-ARS?s Scientific Manuscript database

Wheat flour is one of the world's major food ingredients, but it is difficult to distinguish and identify the many proteins in a flour sample. The abundant glutamine and proline rich gluten proteins are responsible for many of the unique end-use qualities of wheat flour but it is challenging to dis...

NCI Blog Post: CPTAC, the Complementary Sibling of TCGA (An Interview with Dr. Henry Rodriguez about NCI’s Proteomics Program) | Office of Cancer Clinical Proteomics Research

Cancer.gov

What is proteomics? Proteomics is a highly automated and rapid method for measuring all the proteins in a biological sample. Proteins are the molecules that actually do most of the work inside a cell. When researchers develop cancer drugs, those drugs typically target proteins, so scientists and clinicians really have to understand what the proteins are doing. Proteomics researchers are now able to measure up to 10,000 proteins per tumor sample.

Proteomic Analysis of an α7 Nicotinic Acetylcholine Receptor Interactome

PubMed Central

Paulo, Joao A.; Brucker, William J.; Hawrot, Edward

2009-01-01

The α7 nicotinic acetylcholine receptor (nAChR) is well established as the principal high-affinity α-bungarotoxin-binding protein in the mammalian brain. We isolated carbachol-sensitive α-bungarotoxin-binding complexes from total mouse brain tissue by affinity immobilization followed by selective elution, and these proteins were fractionated by SDS-PAGE. The proteins in subdivided gel lane segments were tryptically digested, and the resulting peptides were analyzed by standard mass spectrometry. We identified 55 proteins in wild-type samples that were not present in comparable brain samples from α7 nAChR knockout mice that had been processed in a parallel fashion. Many of these 55 proteins are novel proteomic candidates for interaction partners of the α7 nAChR, and many are associated with multiple signaling pathways that may be implicated in α7 function in the central nervous system. The newly identified potential protein interactions, together with the general methodology that we introduce for α-bungarotoxin-binding protein complexes, form a new platform for many interesting follow-up studies aimed at elucidating the physiological role of neuronal α7 nAChRs. PMID:19714875

"Omics" of Selenium Biology: A Prospective Study of Plasma Proteome Network Before and After Selenized-Yeast Supplementation in Healthy Men.

PubMed

Sinha, Indu; Karagoz, Kubra; Fogle, Rachel L; Hollenbeak, Christopher S; Zea, Arnold H; Arga, Kazim Y; Stanley, Anne E; Hawkes, Wayne C; Sinha, Raghu

2016-04-01

Low selenium levels have been linked to a higher incidence of cancer and other diseases, including Keshan, Chagas, and Kashin-Beck, and insulin resistance. Additionally, muscle and cardiovascular disorders, immune dysfunction, cancer, neurological disorders, and endocrine function have been associated with mutations in genes encoding for selenoproteins. Selenium biology is complex, and a systems biology approach to study global metabolomics, genomics, and/or proteomics may provide important clues to examining selenium-responsive markers in circulation. In the current investigation, we applied a global proteomics approach on plasma samples collected from a previously conducted, double-blinded placebo controlled clinical study, where men were supplemented with selenized-yeast (Se-Yeast; 300 μg/day, 3.8 μmol/day) or placebo-yeast for 48 weeks. Proteomic analysis was performed by iTRAQ on 8 plasma samples from each arm at baseline and 48 weeks. A total of 161 plasma proteins were identified in both arms. Twenty-two proteins were significantly altered following Se-Yeast supplementation and thirteen proteins were significantly changed after placebo-yeast supplementation in healthy men. The differentially expressed proteins were involved in complement and coagulation pathways, immune functions, lipid metabolism, and insulin resistance. Reconstruction and analysis of protein-protein interaction network around selected proteins revealed several hub proteins. One of the interactions suggested by our analysis, PHLD-APOA4, which is involved in insulin resistance, was subsequently validated by Western blot analysis. Our systems approach illustrates a viable platform for investigating responsive proteomic profile in 'before and after' condition following Se-Yeast supplementation. The nature of proteins identified suggests that selenium may play an important role in complement and coagulation pathways, and insulin resistance.

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

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

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

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

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.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

PubMed

Xu, Ruilian; Tang, Jun; Deng, Quantong; He, Wan; Sun, Xiujie; Xia, Ligang; Cheng, Zhiqiang; He, Lisheng; You, Shuyuan; Hu, Jintao; Fu, Yuxiang; Zhu, Jian; Chen, Yixin; Gao, Weina; He, An; Guo, Zhengyu; Lin, Lin; Li, Hua; Hu, Chaofeng; Tian, Ruijun

2018-05-01

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm 2 and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm 2 and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

Proteome-Wide Profiling of Targets of Cysteine reactive Small Molecules by Using Ethynyl Benziodoxolone Reagents.

PubMed

Abegg, Daniel; Frei, Reto; Cerato, Luca; Prasad Hari, Durga; Wang, Chao; Waser, Jerome; Adibekian, Alexander

2015-09-07

In this study, we present a highly efficient method for proteomic profiling of cysteine residues in complex proteomes and in living cells. Our method is based on alkynylation of cysteines in complex proteomes using a "clickable" alkynyl benziodoxolone bearing an azide group. This reaction proceeds fast, under mild physiological conditions, and with a very high degree of chemoselectivity. The formed azide-capped alkynyl-cysteine adducts are readily detectable by LC-MS/MS, and can be further functionalized with TAMRA or biotin alkyne via CuAAC. We demonstrate the utility of alkynyl benziodoxolones for chemical proteomics applications by identifying the proteomic targets of curcumin, a diarylheptanoid natural product that was and still is part of multiple human clinical trials as anticancer agent. Our results demonstrate that curcumin covalently modifies several key players of cellular signaling and metabolism, most notably the enzyme casein kinase I gamma. We anticipate that this new method for cysteine profiling will find broad application in chemical proteomics and drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hydrophilic Strong Anion Exchange (hSAX) Chromatography for Highly Orthogonal Peptide Separation of Complex Proteomes

PubMed Central

2013-01-01

Due to its compatibility and orthogonality to reversed phase (RP) liquid chromatography (LC) separation, ion exchange chromatography, and mainly strong cation exchange (SCX), has often been the first choice in multidimensional LC experiments in proteomics. Here, we have tested the ability of three strong anion exchanger (SAX) columns differing in their hydrophobicity to fractionate RAW264.7 macrophage cell lysate. IonPac AS24, a strong anion exchange material with ultralow hydrophobicity, demonstrated to be superior to other materials by fractionation and separation of tryptic peptides from both a mixture of 6 proteins as well as mouse cell lysate. The chromatography displayed very high orthogonality and high robustness depending on the hydrophilicity of column chemistry, which we termed hydrophilic strong anion exchange (hSAX). Mass spectrometry analysis of 34 SAX fractions from RAW264.7 macrophage cell lysate digest resulted in an identification of 9469 unique proteins and 126318 distinct peptides in one week of instrument time. Moreover, when compared to an optimized high pH/low pH RP separation approach, the method presented here raised the identification of proteins and peptides by 10 and 28%, respectively. This novel hSAX approach provides robust, reproducible, and highly orthogonal separation of complex protein digest samples for deep coverage proteome analysis. PMID:23294059

Proteomic and transcriptomic analysis of lung tissue in OVA-challenged mice.

PubMed

Lee, Yongjin; Hwang, Yun-Ho; Kim, Kwang-Jin; Park, Ae-Kyung; Paik, Man-Jeong; Kim, Seong Hwan; Lee, Su Ui; Yee, Sung-Tae; Son, Young-Jin

2018-01-01

Asthma is a long term inflammatory disease of the airway of lungs characterized by variable airflow obstruction and bronchospasm. Asthma is caused by a complex combination of environmental and genetic interactions. In this study, we conducted proteomic analysis of samples derived from control and OVA challenged mice for environmental respiratory disease by using 2-D gel electrophoresis. In addition, we explored the genes associated with the environmental substances that cause respiratory disease and conducted RNA-seq by next-generation sequencing. Proteomic analysis revealed 7 up-regulated (keratin KB40, CRP, HSP27, chaperonin containing TCP-1, TCP-10, keratin, and albumin) and 3 down-regulated proteins (PLC-α, PLA2, and precursor ApoA-1). The expression diversity of many genes was found in the lung tissue of OVA challenged moue by RNA-seq. 146 genes were identified as significantly differentially expressed by OVA treatment, and 118 genes of the 146 differentially expressed genes were up-regulated and 28 genes were downregulated. These genes were related to inflammation, mucin production, and airway remodeling. The results presented herein enable diagnosis and the identification of quantitative markers to monitor the progression of environmental respiratory disease using proteomics and genomic approaches.

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

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.

Deep coverage of the beer proteome.

PubMed

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

2017-06-06

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

STRAP PTM: Software Tool for Rapid Annotation and Differential Comparison of Protein Post-Translational Modifications.

PubMed

Spencer, Jean L; Bhatia, Vivek N; Whelan, Stephen A; Costello, Catherine E; McComb, Mark E

2013-12-01

The identification of protein post-translational modifications (PTMs) is an increasingly important component of proteomics and biomarker discovery, but very few tools exist for performing fast and easy characterization of global PTM changes and differential comparison of PTMs across groups of data obtained from liquid chromatography-tandem mass spectrometry experiments. STRAP PTM (Software Tool for Rapid Annotation of Proteins: Post-Translational Modification edition) is a program that was developed to facilitate the characterization of PTMs using spectral counting and a novel scoring algorithm to accelerate the identification of differential PTMs from complex data sets. The software facilitates multi-sample comparison by collating, scoring, and ranking PTMs and by summarizing data visually. The freely available software (beta release) installs on a PC and processes data in protXML format obtained from files parsed through the Trans-Proteomic Pipeline. The easy-to-use interface allows examination of results at protein, peptide, and PTM levels, and the overall design offers tremendous flexibility that provides proteomics insight beyond simple assignment and counting.

Extensive T-Cell Epitope Repertoire Sharing among Human Proteome, Gastrointestinal Microbiome, and Pathogenic Bacteria: Implications for the Definition of Self

PubMed Central

Bremel, Robert D.; Homan, E. Jane

2015-01-01

T-cell receptor binding to MHC-bound peptides plays a key role in discrimination between self and non-self. Only a subset, typically a pentamer, of amino acids in a MHC-bound peptide form the motif exposed to the T-cell receptor. We categorize and compare the T-cell exposed amino acid motif repertoire of the total proteomes of two groups of bacteria, comprising pathogens and gastrointestinal microbiome organisms, with the human proteome and immunoglobulins. Given the maximum 205, or 3.2 million of such motifs that bind T-cell receptors, there is considerable overlap in motif usage. We show that the human proteome, exclusive of immunoglobulins, only comprises three quarters of the possible motifs, of which 65.3% are also present in both composite bacterial proteomes. Very few motifs are unique to the human proteome. Immunoglobulin variable regions carry a broad diversity of T-cell exposed motifs (TCEMs) that provides a stratified random sample of the motifs found in pathogens, microbiome, and the human proteome. Individual bacterial genera and species vary in the content of immunoglobulin and human proteome matched motifs that they carry. Mycobacteria and Burkholderia spp carry a particularly high content of such matched motifs. Some bacteria retain a unique motif signature and motif sharing pattern with the human proteome. The implication is that distinguishing self from non-self does not depend on individual TCEMs, but on a complex and dynamic overlay of signals wherein the same TCEM may play different roles in different organisms, and the frequency with which a particular TCEM appears influences its effect. The patterns observed provide clues to bacterial immune evasion and to strategies for intervention, including vaccine design. The breadth and distinct frequency patterns of the immunoglobulin-derived peptides suggest a role of immunoglobulins in maintaining a broadly responsive T-cell repertoire. PMID:26557118

Designing Successful Proteomics Experiments.

PubMed

Ruderman, Daniel

2017-01-01

Because proteomics experiments are so complex they can readily fail, and do so without clear cause. Using standard experimental design techniques and incorporating quality control can greatly increase the chances of success. This chapter introduces the relevant concepts and provides examples specific to proteomic workflows. Applying these notions to design successful proteomics experiments is straightforward. It can help identify failure causes and greatly increase the likelihood of inter-laboratory reproducibility.

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.

Proteome Dynamics: Revisiting Turnover with a Global Perspective*

PubMed Central

Claydon, Amy J.; Beynon, Robert

2012-01-01

Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals. PMID:23125033

Identification of increased amounts of eppin protein complex components in sperm cells of diabetic and obese individuals by difference gel electrophoresis.

PubMed

Paasch, Uwe; Heidenreich, Falk; Pursche, Theresia; Kuhlisch, Eberhard; Kettner, Karina; Grunewald, Sonja; Kratzsch, Jürgen; Dittmar, Gunnar; Glander, Hans-Jürgen; Hoflack, Bernard; Kriegel, Thomas M

2011-08-01

Metabolic disorders like diabetes mellitus and obesity may compromise the fertility of men and women. To unveil disease-associated proteomic changes potentially affecting male fertility, the proteomes of sperm cells from type-1 diabetic, type-2 diabetic, non-diabetic obese and clinically healthy individuals were comparatively analyzed by difference gel electrophoresis. The adaptation of a general protein extraction procedure to the solubilization of proteins from sperm cells allowed for the resolution of 3187 fluorescent spots in the difference gel electrophoresis image of the master gel, which contained the entirety of solubilized sperm proteins. Comparison of the pathological and reference proteomes by applying an average abundance ratio setting of 1.6 and a p ≤ 0.05 criterion resulted in the identification of 79 fluorescent spots containing proteins that were present at significantly changed levels in the sperm cells. Biometric evaluation of the fluorescence data followed by mass spectrometric protein identification revealed altered levels of 12, 71, and 13 protein species in the proteomes of the type-1 diabetic, type-2 diabetic, and non-diabetic obese patients, respectively, with considerably enhanced amounts of the same set of one molecular form of semenogelin-1, one form of clusterin, and two forms of lactotransferrin in each group of pathologic samples. Remarkably, β-galactosidase-1-like protein was the only protein that was detected at decreased levels in all three pathologic situations. The former three proteins are part of the eppin (epididymal proteinase inhibitor) protein complex, which is thought to fulfill fertilization-related functions, such as ejaculate sperm protection, motility regulation and gain of competence for acrosome reaction, whereas the putative role of the latter protein to function as a glycosyl hydrolase during sperm maturation remains to be explored at the protein/enzyme level. The strikingly similar differences detected in the three groups of pathological sperm proteomes reflect a disease-associated enhanced formation of predominantly proteolytically modified forms of three eppin protein complex components, possibly as a response to enduring hyperglycemia and enhanced oxidative stress.

Global Cell Proteome Profiling, Phospho-signaling and Quantitative 
Proteomics for Identification of New Biomarkers in Acute Myeloid 
Leukemia Patients

PubMed Central

Aasebø, Elise; Forthun, Rakel B.; Berven, Frode; Selheim, Frode; Hernandez-Valladares, Maria

2016-01-01

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging. PMID:26306748

Proteogenomics | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

Comparative and Quantitative Global Proteomics Approaches: An Overview

PubMed Central

Deracinois, Barbara; Flahaut, Christophe; Duban-Deweer, Sophie; Karamanos, Yannis

2013-01-01

Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other. PMID:28250403

CPTAC Releases Cancer Proteome Confirmatory Colon Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory colon study data. The goal of the study is to analyze the proteomes of approximately 100 confirmatory colon tumor patients, which includes tumor and adjacent normal samples, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic and phosphoproteomic profiling.

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.

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

NCI-CPTAC DREAM Proteogenomics Challenge (Registration Now Open) | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, integration of proteomics, genomics, and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

Proteome changes in the initial bacterial colonist during ecological succession in an acid mine drainage biofilm community

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

Mueller, Ryan; Dill, Brian; Pan, Chongle

2011-01-01

Proteomes of acid mine drainage biofilms at different stages of ecological succession were examined to understand microbial responses to changing community membership. We evaluated the degree of reproducibility of the community proteomes between samples of the same growth stage and found stable and predictable protein abundance patterns across time and sampling space, allowing for a set of 50 classifier proteins to be identified for use in predicting growth stages of undefined communities. Additionally, physiological changes in the dominant species, Leptospirillum Group II, were analysed as biofilms mature. During early growth stages, this population responds to abiotic stresses related to growthmore » on the acid mine drainage solution. Enzymes involved in protein synthesis, cell division and utilization of 1- and 2-carbon compounds were more abundant in early growth stages, suggesting rapid growth and a reorganization of metabolism during biofilm initiation. As biofilms thicken and diversify, external stresses arise from competition for dwindling resources, which may inhibit cell division of Leptospirillum Group II through the SOS response. This population also represses translation and synthesizes more complex carbohydrates and amino acids in mature biofilms. These findings provide unprecedented insight into the physiological changes that may result from competitive interactions within communities in natural environments.« less

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

PubMed

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

2012-03-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

Keller, Martin; Hettich, Robert

2009-03-01

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

Simulation of Two Dimensional Electrophoresis and Tandem Mass Spectrometry for Teaching Proteomics

ERIC Educational Resources Information Center

Fisher, Amanda; Sekera, Emily; Payne, Jill; Craig, Paul

2012-01-01

In proteomics, complex mixtures of proteins are separated (usually by chromatography or electrophoresis) and identified by mass spectrometry. We have created 2DE Tandem MS, a computer program designed for use in the biochemistry, proteomics, or bioinformatics classroom. It contains two simulations--2D electrophoresis and tandem mass spectrometry.…

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

PubMed

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

2007-01-01

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

Identification of Phosphorylated Proteins on a Global Scale.

PubMed

Iliuk, Anton

2018-05-31

Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) has enabled researchers to analyze complex biological samples with unprecedented depth. It facilitates the identification and quantification of modifications within thousands of proteins in a single large-scale proteomic experiment. Analysis of phosphorylation, one of the most common and important post-translational modifications, has particularly benefited from such progress in the field. Here, detailed protocols are provided for a few well-regarded, common sample preparation methods for an effective phosphoproteomic experiment. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Biochemical Fractionation and Stable Isotope Dilution Liquid Chromatography-mass Spectrometry for Targeted and Microdomain-specific Protein Quantification in Human Postmortem Brain Tissue*

PubMed Central

MacDonald, Matthew L.; Ciccimaro, Eugene; Prakash, Amol; Banerjee, Anamika; Seeholzer, Steven H.; Blair, Ian A.; Hahn, Chang-Gyu

2012-01-01

Synaptic architecture and its adaptive changes require numerous molecular events that are both highly ordered and complex. A majority of neuropsychiatric illnesses are complex trait disorders, in which multiple etiologic factors converge at the synapse via many signaling pathways. Investigating the protein composition of synaptic microdomains from human patient brain tissues will yield valuable insights into the interactions of risk genes in many disorders. These types of studies in postmortem tissues have been limited by the lack of proper study paradigms. Thus, it is necessary not only to develop strategies to quantify protein and post-translational modifications at the synapse, but also to rigorously validate them for use in postmortem human brain tissues. In this study we describe the development of a liquid chromatography-selected reaction monitoring method, using a stable isotope-labeled neuronal proteome standard prepared from the brain tissue of a stable isotope-labeled mouse, for the multiplexed quantification of target synaptic proteins in mammalian samples. Additionally, we report the use of this method to validate a biochemical approach for the preparation of synaptic microdomain enrichments from human postmortem prefrontal cortex. Our data demonstrate that a targeted mass spectrometry approach with a true neuronal proteome standard facilitates accurate and precise quantification of over 100 synaptic proteins in mammalian samples, with the potential to quantify over 1000 proteins. Using this method, we found that protein enrichments in subcellular fractions prepared from human postmortem brain tissue were strikingly similar to those prepared from fresh mouse brain tissue. These findings demonstrate that biochemical fractionation methods paired with targeted proteomic strategies can be used in human brain tissues, with important implications for the study of neuropsychiatric disease. PMID:22942359

Proteomic Profiles of Adipose and Liver Tissues from an Animal Model of Metabolic Syndrome Fed Purple Vegetables

PubMed Central

Ayoub, Hala M; McDonald, Mary Ruth; Sullivan, James Alan; Tsao, Rong; Meckling, Kelly A

2018-01-01

Metabolic Syndrome (MetS) is a complex disorder that predisposes an individual to Cardiovascular Diseases and type 2 Diabetes Mellitus. Proteomics and bioinformatics have proven to be an effective tool to study complex diseases and mechanisms of action of nutrients. We previously showed that substitution of the majority of carbohydrate in a high fat diet by purple potatoes (PP) or purple carrots (PC) improved insulin sensitivity and hypertension in an animal model of MetS (obese Zucker rats) compared to a control sucrose-rich diet. In the current study, we used TMT 10plex mass tag combined with LC-MS/MS technique to study proteomic modulation in the liver (n = 3 samples/diet) and adipose tissue (n = 3 samples/diet) of high fat diet-fed rats with or without substituting sucrose for purple vegetables, followed by functional enrichment analysis, in an attempt to elucidate potential molecular mechanisms responsible for the phenotypic changes seen with purple vegetable feeding. Protein folding, lipid metabolism and cholesterol efflux were identified as the main modulated biological themes in adipose tissue, whereas lipid metabolism, carbohydrate metabolism and oxidative stress were the main modulated themes in liver. We propose that enhanced protein folding, increased cholesterol efflux and higher free fatty acid (FFA) re-esterification are mechanisms by which PP and PC positively modulate MetS pathologies in adipose tissue, whereas, decreased de novo lipogenesis, oxidative stress and FFA uptake, are responsible for the beneficial effects in liver. In conclusion, we provide molecular evidence for the reported metabolic health benefits of purple carrots and potatoes and validate that these vegetables are good choices to replace other simple carbohydrate sources for better metabolic health. PMID:29642414

Comparative Proteomics of Human Monkeypox and Vaccinia Intracellular Mature and Extracellular Enveloped Virions

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

Manes, Nathan P.; Estep, Ryan D.; Mottaz, Heather M.

2008-03-07

Orthopoxviruses are the largest and most complex of the animal viruses. In response to the recent emergence of monkeypox in Africa and the threat of smallpox bioterrorism, virulent (monkeypox virus) and benign (vaccinia virus) orthopoxviruses were proteomically compared with the goal of identifying proteins required for pathogenesis. Orthopoxviruses were grown in HeLa cells to two different viral forms (intracellular mature virus and extracellular enveloped virus), purified by sucrose gradient ultracentrifugation, denatured using RapiGest™ surfactant, and digested with trypsin. Unfractionated samples and strong cation exchange HPLC fractions were analyzed by reversed-phase LC-MS/MS, and analyses of the MS/MS spectra using SEQUEST® andmore » X! Tandem resulted in the identification of hundreds of monkeypox, vaccinia, and copurified host proteins. The unfractionated samples were additionally analyzed by LC-MS on an LTQ-Orbitrap™, and the accurate mass and elution time tag approach was used to perform quantitative comparisons. Possible pathophysiological roles of differentially expressed orthopoxvirus genes are discussed.« less

Functional proteomics outlines the complexity of breast cancer molecular subtypes.

PubMed

Gámez-Pozo, Angelo; Trilla-Fuertes, Lucía; Berges-Soria, Julia; Selevsek, Nathalie; López-Vacas, Rocío; Díaz-Almirón, Mariana; Nanni, Paolo; Arevalillo, Jorge M; Navarro, Hilario; Grossmann, Jonas; Gayá Moreno, Francisco; Gómez Rioja, Rubén; Prado-Vázquez, Guillermo; Zapater-Moros, Andrea; Main, Paloma; Feliú, Jaime; Martínez Del Prado, Purificación; Zamora, Pilar; Ciruelos, Eva; Espinosa, Enrique; Fresno Vara, Juan Ángel

2017-08-30

Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.

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.

Characterization of Native Protein Complexes and Protein Isoform Variation Using Size-fractionation-based Quantitative Proteomics*

PubMed Central

Kirkwood, Kathryn J.; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I.

2013-01-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community. PMID:24043423

Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics.

PubMed

Kirkwood, Kathryn J; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I

2013-12-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community.

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification.

PubMed

Liu, Ming-Qi; Zeng, Wen-Feng; Fang, Pan; Cao, Wei-Qian; Liu, Chao; Yan, Guo-Quan; Zhang, Yang; Peng, Chao; Wu, Jian-Qiang; Zhang, Xiao-Jin; Tu, Hui-Jun; Chi, Hao; Sun, Rui-Xiang; Cao, Yong; Dong, Meng-Qiu; Jiang, Bi-Yun; Huang, Jiang-Ming; Shen, Hua-Li; Wong, Catherine C L; He, Si-Min; Yang, Peng-Yuan

2017-09-05

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15 N/ 13 C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

Exploring the context of the lung proteome within the airway mucosa following allergen challenge.

PubMed

Fehniger, Thomas E; Sato-Folatre, José-Gabriel; Malmström, Johan; Berglund, Magnus; Lindberg, Claes; Brange, Charlotte; Lindberg, Henrik; Marko-Varga, György

2004-01-01

The lung proteome is a dynamic collection of specialized proteins related to pulmonary function. Many cells of different derivations, activation states, and levels of maturity contribute to the changing environment, which produces the lung proteome. Inflammatory cells reacting to environmental challenge, for example from allergens, produce and secrete proteins which have profound effects on both resident and nonresident cells located in airways, alveoli, and the vascular tree which provides blood cells to the parenchyma alveolar bed for gas exchange. In an experimental model of allergic airway inflammation, we have compared control and allergen challenged lung compartments to determine global protein expression patterns using 2D-gel electrophoresis and subsequent spot identification by MS/MS mass spectrometry. We have then specifically isolated the epithelial mucosal layer, which lines conducting airways, from control and allergen challenged lungs, using laser capture technology and performed proteome identification on these selected cell samples. A central component of our investigations has been to contextually relate the histological features of the dynamic pulmonary environment to the changes in protein expression observed following challenge. Our results provide new information of the complexity of the submucosa/epithelium interface and the mechanisms behind the transformation of airway epithelium from normal steady states to functionally activated states.

CPTAC Prospective Biospecimen Collection Solicitation | Office of Cancer Clinical Proteomics Research

Cancer.gov

A new funding opportunity in support of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) seeks to prospectively procure tumor samples, collected for proteomics investigation.

Affinity proteomics to study endogenous protein complexes: Pointers, pitfalls, preferences and perspectives

PubMed Central

LaCava, John; Molloy, Kelly R.; Taylor, Martin S.; Domanski, Michal; Chait, Brian T.; Rout, Michael P.

2015-01-01

Dissecting and studying cellular systems requires the ability to specifically isolate distinct proteins along with the co-assembled constituents of their associated complexes. Affinity capture techniques leverage high affinity, high specificity reagents to target and capture proteins of interest along with specifically associated proteins from cell extracts. Affinity capture coupled to mass spectrometry (MS)-based proteomic analyses has enabled the isolation and characterization of a wide range of endogenous protein complexes. Here, we outline effective procedures for the affinity capture of protein complexes, highlighting best practices and common pitfalls. PMID:25757543

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

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

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading tomore » a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.« less

CPTAC Releases Largest-Ever Breast Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have released a dataset of proteins and  phosphopeptides identified through deep proteomic and phosphoproteomic analysis of breast tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).

The Multinational Arabidopsis Steering Subcommittee for Proteomics Assembles the Largest Proteome Database Resource for Plant Systems Biology

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

Weckwerth, Wolfram; Baginsky, Sacha; Van Wijk, Klass

2009-12-01

In the past 10 years, we have witnessed remarkable advances in the field of plant molecular biology. The rapid development of proteomic technologies and the speed with which these techniques have been applied to the field have altered our perception of how we can analyze proteins in complex systems. At nearly the same time, the availability of the complete genome for the model plant Arabidopsis thaliana was released; this effort provides an unsurpassed resource for the identification of proteins when researchers use MS to analyze plant samples. Recognizing the growth in this area, the Multinational Arabidopsis Steering Committee (MASC) establishedmore » a subcommittee for A. thaliana proteomics in 2006 with the objective of consolidating databases, technique standards, and experimentally validated candidate genes and functions. Since the establishment of the Multinational Arabidopsis Steering Subcommittee for Proteomics (MASCP), many new approaches and resources have become available. Recently, the subcommittee established a webpage to consolidate this information (www.masc-proteomics.org). It includes links to plant proteomic databases, general information about proteomic techniques, meeting information, a summary of proteomic standards, and other relevant resources. Altogether, this website provides a useful resource for the Arabidopsis proteomics community. In the future, the website will host discussions and investigate the cross-linking of databases. The subcommittee members have extensive experience in arabidopsis proteomics and collectively have produced some of the most extensive proteomics data sets for this model plant (Table S1 in the Supporting Information has a list of resources). The largest collection of proteomics data from a single study in A. thaliana was assembled into an accessible database (AtProteome; http://fgcz-atproteome.unizh.ch/index.php) and was recently published by the Baginsky lab.1 The database provides links to major Arabidopsis online resources, and raw data have been deposited in PRIDE and PRIDE BioMart. Included in this database is an Arabidopsis proteome map that provides evidence for the expression of {approx}50% of all predicted gene models, including several alternative gene models that are not represented in The Arabidopsis Information Resource (TAIR) protein database. A set of organ-specific biomarkers is provided, as well as organ-specific proteotypic peptides for 4105 proteins that can be used to facilitate targeted quantitative proteomic surveys. In the future, the AtProteome database will be linked to additional existing resources developed by MASCP members, such as PPDB, ProMEX, and SUBA. The most comprehensive study on the Arabidopsis chloroplast proteome, which includes information on chloroplast sorting signals, posttranslational modifications (PTMs), and protein abundances (analyzed by high-accuracy MS [Orbitrap]), was recently published by the van Wijk lab.2 These and previous data are available via the plant proteome database (PPDB; http://ppdb.tc.cornell.edu) for A. thaliana and maize. PPDB provides genome-wide experimental and functional characterization of the A. thaliana and maize proteomes, including PTMs and subcellular localization information, with an emphasis on leaf and plastid proteins. Maize and Arabidopsis proteome entries are directly linked via internal BLAST alignments within PPDB. Direct links for each protein to TAIR, SUBA, ProMEX, and other resources are also provided.« less

The role of proteomics in studies of protein moonlighting.

PubMed

Beynon, Robert J; Hammond, Dean; Harman, Victoria; Woolerton, Yvonne

2014-12-01

The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

The application of proteomics in different aspects of hepatocellular carcinoma research.

PubMed

Xing, Xiaohua; Liang, Dong; Huang, Yao; Zeng, Yongyi; Han, Xiao; Liu, Xiaolong; Liu, Jingfeng

2016-08-11

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, which is causing the second leading cancer-related death worldwide. With the significant advances of high-throughput protein analysis techniques, the proteomics offered an extremely useful and versatile analytical platform for biomedical researches. In recent years, different proteomic strategies have been widely applied in the various aspects of HCC studies, ranging from screening the early diagnostic and prognostic biomarkers to in-depth investigating the underlying molecular mechanisms. In this review, we would like to systematically summarize the current applications of proteomics in hepatocellular carcinoma study, and discuss the challenges of applying proteomics in study clinical samples, as well as discuss the possible application of proteomics in precision medicine. In this review, we have systematically summarized the current applications of proteomics in hepatocellular carcinoma study, ranging from screening biomarkers to in-depth investigating the underlying molecular mechanisms. In addition, we have discussed the challenges of applying proteomics in study clinical samples, as well as the possible applications of proteomics in precision medicine. We believe that this review would help readers to be better familiar with the recent progresses of clinical proteomics, especially in the field of hepatocellular carcinoma research. Copyright © 2016 Elsevier B.V. All rights reserved.

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

DOE PAGES

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; ...

2017-09-01

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap),more » leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.« less

Proteomic analysis of single mammalian cells enabled by microfluidic nanodroplet sample preparation and ultrasensitive nanoLC-MS.

PubMed

Zhu, Ying; Clair, Geremy; Chrisler, William; Shen, Yufeng; Zhao, Rui; Shukla, Anil; Moore, Ronald; Misra, Ravi; Pryhuber, Gloria; Smith, Richard; Ansong, Charles; Kelly, Ryan T

2018-05-24

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analysed by ultrasensitive nanoLC-MS. An average of ~670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

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

PubMed

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

2017-06-23

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

CPTAC Biospecimen Collection Solicitation | Office of Cancer Clinical Proteomics Research

Cancer.gov

A funding opportunity in support of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) seeks to prospectively procure tumor samples, collected for proteomics investigation. The scope of work under this Statement of Work encompasses the activities needed to prospectively procure high quality, clinically annotated human tumor samples, blood and plasma, and when feasible, normal tissue from volunteer patients suffering from colon, ovarian, and breast cancer.

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.

Online combination of reversed-phase/reversed-phase and porous graphitic carbon liquid chromatography for multicomponent separation of proteomics and glycoproteomics samples.

PubMed

Lam, Maggie P Y; Lau, Edward; Siu, S O; Ng, Dominic C M; Kong, Ricky P W; Chiu, Philip C N; Yeung, William S B; Lo, Clive; Chu, Ivan K

2011-11-01

In this paper, we describe an online combination of reversed-phase/reversed-phase (RP-RP) and porous graphitic carbon (PGC) liquid chromatography (LC) for multicomponent analysis of proteomics and glycoproteomics samples. The online RP-RP portion of this system provides comprehensive 2-D peptide separation based on sequence hydrophobicity at pH 2 and 10. Hydrophilic components (e.g. glycans, glycopeptides) that are not retained by RP are automatically diverted downstream to a PGC column for further trapping and separation. Furthermore, the RP-RP/PGC system can provide simultaneous extension of the hydropathy range and peak capacity for analysis. Using an 11-protein mixture, we found that the system could efficiently separate native peptides and released N-glycans from a single sample. We evaluated the applicability of the system to the analysis of complex biological samples using 25 μg of the lysate of a human choriocarcinoma cell line (BeWo), confidently identifying a total of 1449 proteins from a single experiment and up to 1909 distinct proteins from technical triplicates. The PGC fraction increased the sequence coverage through the inclusion of additional hydrophilic sequences that accounted for up to 6.9% of the total identified peptides from the BeWo lysate, with apparent preference for the detection of hydrophilic motifs and proteins. In addition, RP-RP/PGC is applicable to the analysis of complex glycomics samples, as demonstrated by our analysis of a concanavalin A-extracted glycoproteome from human serum; in total, 134 potentially N-glycosylated serum proteins, 151 possible N-glycosylation sites, and more than 40 possible N-glycan structures recognized by concanavalin A were simultaneously detected. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the Helix Propensity in Generalized Born Solvent Descriptions of Modeling the Dark Proteome

DTIC Science & Technology

2017-01-10

benchmarks of conformational sampling methods and their all-atom force fields plus solvent descriptions to accurately model structural transitions on a...atom simulations of proteins is the replacement of explicit water interactions with a continuum description of treating implicitly the bulk physical... structure was reported by Amarasinghe and coworkers (Leung et al., 2015) of the Ebola nucleoprotein NP in complex with a 28-residue peptide extracted

A Simple Method for Rapid Depletion of Rubisco from Soybean (Glycine max) Leaf for Proteomic Analysis of Lower Abundance Proteins

USDA-ARS?s Scientific Manuscript database

2-DE analysis of complex plant proteomes has limited dynamic resolution because only abundant proteins can be detected. Proteomic assessment of the low abundance proteins within leaf tissue is difficult when it is comprised of 30 – 50% of the CO2 fixation enzyme Rubisco. Resolution can be improved t...

Proteome Studies of Filamentous Fungi

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

Baker, Scott E.; Panisko, Ellen A.

2011-04-20

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide breadth of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, non-gel basedmore » proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of different variations on the general method and technologies for identifying peptides in a given sample. We present a method that can serve as a “baseline” for proteomic studies of fungi.« less

Proteome studies of filamentous fungi.

PubMed

Baker, Scott E; Panisko, Ellen A

2011-01-01

The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide variety of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, nongel-based proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of variations on the general methods and technologies for identifying peptides in a given sample. We present a method that can serve as a "baseline" for proteomic studies of fungi.

Complex and extensive post-transcriptional regulation revealed by integrative proteomic and transcriptomic analysis of metabolite stress response in Clostridium acetobutylicum.

PubMed

Venkataramanan, Keerthi P; Min, Lie; Hou, Shuyu; Jones, Shawn W; Ralston, Matthew T; Lee, Kelvin H; Papoutsakis, E Terry

2015-01-01

Clostridium acetobutylicum is a model organism for both clostridial biology and solvent production. The organism is exposed to its own toxic metabolites butyrate and butanol, which trigger an adaptive stress response. Integrative analysis of proteomic and RNAseq data may provide novel insights into post-transcriptional regulation. The identified iTRAQ-based quantitative stress proteome is made up of 616 proteins with a 15 % genome coverage. The differentially expressed proteome correlated poorly with the corresponding differential RNAseq transcriptome. Up to 31 % of the differentially expressed proteins under stress displayed patterns opposite to those of the transcriptome, thus suggesting significant post-transcriptional regulation. The differential proteome of the translation machinery suggests that cells employ a different subset of ribosomal proteins under stress. Several highly upregulated proteins but with low mRNA levels possessed mRNAs with long 5'UTRs and strong RBS scores, thus supporting the argument that regulatory elements on the long 5'UTRs control their translation. For example, the oxidative stress response rubrerythrin was upregulated only at the protein level up to 40-fold without significant mRNA changes. We also identified many leaderless transcripts, several displaying different transcriptional start sites, thus suggesting mRNA-trimming mechanisms under stress. Downregulation of Rho and partner proteins pointed to changes in transcriptional elongation and termination under stress. The integrative proteomic-transcriptomic analysis demonstrated complex expression patterns of a large fraction of the proteome. Such patterns could not have been detected with one or the other omic analyses. Our analysis proposes the involvement of specific molecular mechanisms of post-transcriptional regulation to explain the observed complex stress response.

Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis.

PubMed

Mitra, Vikram; Govorukhina, Natalia; Zwanenburg, Gooitzen; Hoefsloot, Huub; Westra, Inge; Smilde, Age; Reijmers, Theo; van der Zee, Ate G J; Suits, Frank; Bischoff, Rainer; Horvatovich, Péter

2016-04-19

Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level, (2) stopping trypsin digestion with acid, and (3) the trypsin/protein ratio. This provides guidelines for the experimentalist to keep the ratio of trypsin/protein constant and to control the trypsin reaction by stopping it with acid at an accurately set pH. The hemolysis level cannot be controlled tightly as it depends on the status of a patient's blood (e.g., red blood cells are more fragile in patients undergoing chemotherapy) and the care with which blood was sampled (e.g., by avoiding shear stress). However, its level can be determined with a simple UV spectrophotometric measurement and samples with extreme levels or the peaks affected by hemolysis can be discarded from further analysis. The loadings of the ASCA model led to peptide peaks that were most affected by a given factor, for example, to hemoglobin-derived peptides in the case of the hemolysis level. Peak intensity differences for these peptides were assessed by means of extracted ion chromatograms confirming the results of the ASCA model.

CPTAC Releases Largest-Ever Colorectal Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

On September 4, 2013, NCI’s Clinical Proteomics Tumor Analysis Consortium (CPTAC) publicly released proteomic data produced from colorectal tumor samples previously analyzed by The Cancer Genome Atlas (TCGA).  This is the initial release of proteomic tumor data designed to complement genomic data on the same tumors. The data is publicly available at the CPTAC data portal.

CPTAC Releases Largest-Ever Ovarian Cancer Proteome Dataset from Previously Genome Characterized Tumors | Office of Cancer Clinical Proteomics Research

Cancer.gov

National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) scientists have just released a comprehensive dataset of the proteomic analysis of high grade serous ovarian tumor samples, previously genomically analyzed by The Cancer Genome Atlas (TCGA).  This is one of the largest public datasets covering the proteome, phosphoproteome and glycoproteome with complementary deep genomic sequencing data on the same tumor.

Optimizing of MALDI-ToF-based low-molecular-weight serum proteome pattern analysis in detection of breast cancer patients; the effect of albumin removal on classification performance.

PubMed

Pietrowska, M; Marczak, L; Polanska, J; Nowicka, E; Behrent, K; Tarnawski, R; Stobiecki, M; Polanski, A; Widlak, P

2010-01-01

Mass spectrometry-based analysis of the serum proteome allows identifying multi-peptide patterns/signatures specific for blood of cancer patients, thus having high potential value for cancer diagnostics. However, because of problems with optimization and standardization of experimental and computational design, none of identified proteome patterns/signatures was approved for diagnostics in clinical practice as yet. Here we compared two methods of serum sample preparation for mass spectrometry-based proteome pattern analysis aimed to identify biomarkers that could be used in early detection of breast cancer patients. Blood samples were collected in a group of 92 patients diagnosed at early (I and II) stages of the disease before the start of therapy, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and analyzed using MALDI-ToF spectrometry, either directly or after membrane filtration (50 kDa cut-off) to remove albumin and other large serum proteins. Mass spectra of the low-molecular-weight fraction (2-10 kDa) of the serum proteome were resolved using the Gaussian mixture decomposition, and identified spectral components were used to build classifiers that differentiated samples from breast cancer patients and healthy persons. Mass spectra of complete serum and membrane-filtered albumin-depleted samples have apparently different structure and peaks specific for both types of samples could be identified. The optimal classifier built for the complete serum specimens consisted of 8 spectral components, and had 81% specificity and 72% sensitivity, while that built for the membrane-filtered samples consisted of 4 components, and had 80% specificity and 81% sensitivity. We concluded that pre-processing of samples to remove albumin might be recommended before MALDI-ToF mass spectrometric analysis of the low-molecular-weight components of human serum Keywords: albumin removal; breast cancer; clinical proteomics; mass spectrometry; pattern analysis; serum proteome.

Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

PubMed Central

Feist, Peter; Hummon, Amanda B.

2015-01-01

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

Environmental Microbial Community Proteomics: Status, Challenges and Perspectives.

PubMed

Wang, Da-Zhi; Kong, Ling-Fen; Li, Yuan-Yuan; Xie, Zhang-Xian

2016-08-05

Microbial community proteomics, also termed metaproteomics, is an emerging field within the area of microbiology, which studies the entire protein complement recovered directly from a complex environmental microbial community at a given point in time. Although it is still in its infancy, microbial community proteomics has shown its powerful potential in exploring microbial diversity, metabolic potential, ecological function and microbe-environment interactions. In this paper, we review recent advances achieved in microbial community proteomics conducted in diverse environments, such as marine and freshwater, sediment and soil, activated sludge, acid mine drainage biofilms and symbiotic communities. The challenges facing microbial community proteomics are also discussed, and we believe that microbial community proteomics will greatly enhance our understanding of the microbial world and its interactions with the environment.

Integrated proteomic and genomic analysis of colorectal cancer

Cancer.gov

Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

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

PubMed

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

2018-04-17

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

[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.

Mathematical biodescriptors of proteomics maps: background and applications.

PubMed

Basak, Subhash C; Gute, Brian D

2008-05-01

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

Scientific Approaches | Office of Cancer Clinical Proteomics Research

Cancer.gov

CPTAC employs two complementary scientific approaches, a "Targeting Genome to Proteome" (Targeting G2P) approach and a "Mapping Proteome to Genome" (Mapping P2G) approach, in order to address biological questions from data generated on a sample.

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.

Proteomic analysis of tissue samples in translational breast cancer research.

PubMed

Gromov, Pavel; Moreira, José M A; Gromova, Irina

2014-06-01

In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis, and both prognosis and prediction of outcome of chemotherapy. The purpose of this review is to critically appraise what has been achieved to date using proteomic technologies and to bring forward novel strategies - based on the analysis of clinically relevant samples - that promise to accelerate the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens.

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples

PubMed Central

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-01-01

The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine. PMID:28248241

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples.

PubMed

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-10-17

The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

Milk Bottom-Up Proteomics: Method Optimization

PubMed Central

Vincent, Delphine; Ezernieks, Vilnis; Elkins, Aaron; Nguyen, Nga; Moate, Peter J.; Cocks, Benjamin G.; Rochfort, Simone

2016-01-01

Milk is a complex fluid whose proteome displays a diverse set of proteins of high abundance such as caseins and medium to low abundance whey proteins such as ß-lactoglobulin, lactoferrin, immunoglobulins, glycoproteins, peptide hormones, and enzymes. A sample preparation method that enables high reproducibility and throughput is key in reliably identifying proteins present or proteins responding to conditions such as a diet, health or genetics. Using skim milk samples from Jersey and Holstein-Friesian cows, we compared three extraction procedures which have not previously been applied to samples of cows' milk. Method A (urea) involved a simple dilution of the milk in a urea-based buffer, method B (TCA/acetone) involved a trichloroacetic acid (TCA)/acetone precipitation, and method C (methanol/chloroform) involved a tri-phasic partition method in chloroform/methanol solution. Protein assays, SDS-PAGE profiling, and trypsin digestion followed by nanoHPLC-electrospray ionization-tandem mass spectrometry (nLC-ESI-MS/MS) analyses were performed to assess their efficiency. Replicates were used at each analytical step (extraction, digestion, injection) to assess reproducibility. Mass spectrometry (MS) data are available via ProteomeXchange with identifier PXD002529. Overall 186 unique accessions, major and minor proteins, were identified with a combination of methods. Method C (methanol/chloroform) yielded the best resolved SDS-patterns and highest protein recovery rates, method A (urea) yielded the greatest number of accessions, and, of the three procedures, method B (TCA/acetone) was the least compatible of all with a wide range of downstream analytical procedures. Our results also highlighted breed differences between the proteins in milk of Jersey and Holstein-Friesian cows. PMID:26793233

Unlocking Proteomic Heterogeneity in Complex Diseases through Visual Analytics

PubMed Central

Bhavnani, Suresh K.; Dang, Bryant; Bellala, Gowtham; Divekar, Rohit; Visweswaran, Shyam; Brasier, Allan; Kurosky, Alex

2015-01-01

Despite years of preclinical development, biological interventions designed to treat complex diseases like asthma often fail in phase III clinical trials. These failures suggest that current methods to analyze biomedical data might be missing critical aspects of biological complexity such as the assumption that cases and controls come from homogeneous distributions. Here we discuss why and how methods from the rapidly evolving field of visual analytics can help translational teams (consisting of biologists, clinicians, and bioinformaticians) to address the challenge of modeling and inferring heterogeneity in the proteomic and phenotypic profiles of patients with complex diseases. Because a primary goal of visual analytics is to amplify the cognitive capacities of humans for detecting patterns in complex data, we begin with an overview of the cognitive foundations for the field of visual analytics. Next, we organize the primary ways in which a specific form of visual analytics called networks have been used to model and infer biological mechanisms, which help to identify the properties of networks that are particularly useful for the discovery and analysis of proteomic heterogeneity in complex diseases. We describe one such approach called subject-protein networks, and demonstrate its application on two proteomic datasets. This demonstration provides insights to help translational teams overcome theoretical, practical, and pedagogical hurdles for the widespread use of subject-protein networks for analyzing molecular heterogeneities, with the translational goal of designing biomarker-based clinical trials, and accelerating the development of personalized approaches to medicine. PMID:25684269

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders.

PubMed

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-04-28

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions.

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

PubMed

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

2017-06-06

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

A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer. | Office of Cancer Genomics

Cancer.gov

Adenosine (A) to inosine (I) RNA editing introduces many nucleotide changes in cancer transcriptomes. However, due to the complexity of post-transcriptional regulation, the contribution of RNA editing to proteomic diversity in human cancers remains unclear. Here, we performed an integrated analysis of TCGA genomic data and CPTAC proteomic data. Despite limited site diversity, we demonstrate that A-to-I RNA editing contributes to proteomic diversity in breast cancer through changes in amino acid sequences. We validate the presence of editing events at both RNA and protein levels.

Proteomic Analysis of Connexin 43 Reveals Novel Interactors Related to Osteoarthritis*

PubMed Central

Gago-Fuentes, Raquel; Fernández-Puente, Patricia; Megias, Diego; Carpintero-Fernández, Paula; Mateos, Jesus; Acea, Benigno; Fonseca, Eduardo; Blanco, Francisco Javier; Mayan, Maria Dolores

2015-01-01

We have previously reported that articular chondrocytes in tissue contain long cytoplasmic arms that physically connect two distant cells. Cell-to-cell communication occurs through connexin channels termed Gap Junction (GJ) channels, which achieve direct cellular communication by allowing the intercellular exchange of ions, small RNAs, nutrients, and second messengers. The Cx43 protein is overexpressed in several human diseases and inflammation processes and in articular cartilage from patients with osteoarthritis (OA). An increase in the level of Cx43 is known to alter gene expression, cell signaling, growth, and cell proliferation. The interaction of proteins with the C-terminal tail of connexin 43 (Cx43) directly modulates GJ-dependent and -independent functions. Here, we describe the isolation of Cx43 complexes using mild extraction conditions and immunoaffinity purification. Cx43 complexes were extracted from human primary articular chondrocytes isolated from healthy donors and patients with OA. The proteomic content of the native complexes was determined using LC-MS/MS, and protein associations with Cx43 were validated using Western blot and immunolocalization experiments. We identified >100 Cx43-associated proteins including previously uncharacterized proteins related to nucleolar functions, RNA transport, and translation. We also identified several proteins involved in human diseases, cartilage structure, and OA as novel functional Cx43 interactors, which emphasized the importance of Cx43 in the normal physiology and structural and functional integrity of chondrocytes and articular cartilage. Gene Ontology (GO) terms of the proteins identified in the OA samples showed an enrichment of Cx43-interactors related to cell adhesion, calmodulin binding, the nucleolus, and the cytoskeleton in OA samples compared with healthy samples. However, the mitochondrial proteins SOD2 and ATP5J2 were identified only in samples from healthy donors. The identification of Cx43 interactors will provide clues to the functions of Cx43 in human cells and its roles in the development of several diseases, including OA. PMID:25903580

iTRAQ-based Quantitative Proteomics Study in Patients with Refractory Mycoplasma pneumoniae Pneumonia.

PubMed

Yu, Jia-Lu; Song, Qi-Fang; Xie, Zhi-Wei; Jiang, Wen-Hui; Chen, Jia-Hui; Fan, Hui-Feng; Xie, Ya-Ping; Lu, Gen

2017-09-25

Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia in children and young adults. Although MP pneumonia is usually benign and self-limited, in some cases it can develop into life-threating refractory MP pneumonia (RMPP). However, the pathogenesis of RMPP is poorly understood. The identification and characterization of proteins related to RMPP could provide a proof of principle to facilitate appropriate diagnostic and therapeutic strategies for treating paients with MP. In this study, we used a quantitative proteomic technique (iTRAQ) to analyze MP-related proteins in serum samples from 5 patients with RMPP, 5 patients with non-refractory MP pneumonia (NRMPP), and 5 healthy children. Functional classification, sub-cellular localization, and protein interaction network analysis were carried out based on protein annotation through evolutionary relationship (PANTHER) and Cytoscape analysis. A total of 260 differentially expressed proteins were identified in the RMPP and NRMPP groups. Compared to the control group, the NRMPP and RMPP groups showed 134 (70 up-regulated and 64 down-regulated) and 126 (63 up-regulated and 63 down-regulated) differentially expressed proteins, respectively. The complex functional classification and protein interaction network of the identified proteins reflected the complex pathogenesis of RMPP. Our study provides the first comprehensive proteome map of RMPP-related proteins from MP pneumonia. These profiles may be useful as part of a diagnostic panel, and the identified proteins provide new insights into the pathological mechanisms underlying RMPP.

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera)

PubMed Central

2012-01-01

Background Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. Results We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Conclusions Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation. PMID:23021491

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera).

PubMed

Parker, Robert; Guarna, M Marta; Melathopoulos, Andony P; Moon, Kyung-Mee; White, Rick; Huxter, Elizabeth; Pernal, Stephen F; Foster, Leonard J

2012-06-29

Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation.

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.

Plasma proteomic changes during hypothermic and normothermic cardiopulmonary bypass in aortic surgeries

PubMed Central

ODA, TEIJI; YAMAGUCHI, AKANE; YOKOYAMA, MASAO; SHIMIZU, KOJI; TOYOTA, KOSAKU; NIKAI, TETSURO; MATSUMOTO, KEN-ICHI

2014-01-01

Deep hypothermic circulatory arrest (DHCA) is a protective method against brain ischemia in aortic surgery. However, the possible effects of DHCA on the plasma proteins remain to be determined. In the present study, we used novel high-throughput technology to compare the plasma proteomes during DHCA (22°C) with selective cerebral perfusion (SCP, n=7) to those during normothermic cardiopulmonary bypass (CPB, n=7). Three plasma samples per patient were obtained during CPB: T1, prior to cooling; T2, during hypothermia; T3, after rewarming for the DHCA group and three corresponding points for the normothermic group. A proteomic analysis was performed using isobaric tag for relative and absolute quantification (iTRAQ) labeling tandem mass spectrometry to assess quantitative protein changes. In total, the analysis identified 262 proteins. The bioinformatics analysis revealed a significant upregulation of complement activation at T2 in normothermic CPB, which was suppressed in DHCA. These findings were confirmed by the changes of the terminal complement complex (SC5b-9) levels. At T3, however, the level of SC5b-9 showed a greater increase in DHCA compared to normothermic CPB, while 48 proteins were significantly downregulated in DHCA. The results demonstrated that DHCA and rewarming potentially exert a significant effect on the plasma proteome in patients undergoing aortic surgery. PMID:25050567

Lack of β, β-carotene -9’, 10’-oxygenase 2 leads to hepatic mitochondrial dysfunction and cellular oxidative stress in mice

PubMed Central

Wu, Lei; Guo, Xin; Hartson, Steven D.; Davis, Mary Abby; He, Hui; Medeiros, Denis M.; Wang, Weiqun; Clarke, Stephen L.; Lucas, Edralin; Smith, Brenda J.; von Lintig, Johannes; Lin, Dingbo

2017-01-01

Scope β,β-carotene-9’,10’-dioxygenase 2 (BCO2) is a carotenoid cleavage enzyme localized to the inner mitochondrial membrane in mammals. This study was aimed to assess the impact of genetic ablation of BCO2 on hepatic oxidative stress through mitochondrial function in mice. Methods and Results Liver samples from 6 week old male BCO2−/− knockout (KO) and isogenic wild-type (WT) mice were subjected to proteomics and functional activity assays. Compared to the WT, KO mice consumed more food (by 18 %) yet displayed significantly lower body weight (by 12 %). Mitochondrial proteomic results demonstrated that loss of BCO2 was associated with quantitative changes of the mitochondrial proteome mainly shown by suppressed expression of enzymes and/or proteins involved in fatty acid β–oxidation, the tricarboxylic acid cycle, and the electron transport chain (ETC). The mitochondrial basal respiratory rate, proton leak, and ETC complex II capacity were significantly elevated in the livers of KO compared to WT mice. Moreover, elevated reactive oxygen species and increased mitochondrial protein carbonylation were also demonstrated in liver of KO mice. Conclusions Loss of BCO2 induces mitochondrial hyperactivation, mitochondrial stress and changes of the mitochondrial proteome, leading to mitochondrial energy insufficiency. BCO2 appears to be critical for proper hepatic mitochondrial function. PMID:27991717

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

PubMed

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

2016-10-07

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

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

Liu, Xing; Xu, Yanli; Meng, Qian

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP andmore » NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.« less

Compositional complexity of the mitochondrial proteome of a unicellular eukaryote (Acanthamoeba castellanii, supergroup Amoebozoa) rivals that of animals, fungi, and plants.

PubMed

Gawryluk, Ryan M R; Chisholm, Kenneth A; Pinto, Devanand M; Gray, Michael W

2014-09-23

We present a combined proteomic and bioinformatic investigation of mitochondrial proteins from the amoeboid protist Acanthamoeba castellanii, the first such comprehensive investigation in a free-living member of the supergroup Amoebozoa. This protist was chosen both for its phylogenetic position (as a sister to animals and fungi) and its ecological ubiquity and physiological flexibility. We report 1033 A. castellanii mitochondrial protein sequences, 709 supported by mass spectrometry data (676 nucleus-encoded and 33 mitochondrion-encoded), including two previously unannotated mtDNA-encoded proteins, which we identify as highly divergent mitochondrial ribosomal proteins. Other notable findings include duplicate proteins for all of the enzymes of the tricarboxylic acid (TCA) cycle-which, along with the identification of a mitochondrial malate synthase-isocitrate lyase fusion protein, suggests the interesting possibility that the glyoxylate cycle operates in A. castellanii mitochondria. Additionally, the A. castellanii genome encodes an unusually high number (at least 29) of mitochondrion-targeted pentatricopeptide repeat (PPR) proteins, organellar RNA metabolism factors in other organisms. We discuss several key mitochondrial pathways, including DNA replication, transcription and translation, protein degradation, protein import and Fe-S cluster biosynthesis, highlighting similarities and differences in these pathways in other eukaryotes. In compositional and functional complexity, the mitochondrial proteome of A. castellanii rivals that of multicellular eukaryotes. Comprehensive proteomic surveys of mitochondria have been undertaken in a limited number of predominantly multicellular eukaryotes. This phylogenetically narrow perspective constrains and biases our insights into mitochondrial function and evolution, as it neglects protists, which account for most of the evolutionary and functional diversity within eukaryotes. We report here the first comprehensive investigation of the mitochondrial proteome in a member (A. castellanii) of the eukaryotic supergroup Amoebozoa. Through a combination of tandem mass spectrometry (MS/MS) and in silico data mining, we have retrieved 1033 candidate mitochondrial protein sequences, 709 having MS support. These data were used to reconstruct the metabolic pathways and protein complexes of A. castellanii mitochondria, and were integrated with data from other characterized mitochondrial proteomes to augment our understanding of mitochondrial proteome evolution. Our results demonstrate the power of combining direct proteomic and bioinformatic approaches in the discovery of novel mitochondrial proteins, both nucleus-encoded and mitochondrion-encoded, and highlight the compositional complexity of the A. castellanii mitochondrial proteome, which rivals that of animals, fungi and plants. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2011-01-01

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

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

PubMed Central

Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

2013-01-01

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

SERPINE 1 Links Obesity and Diabetes: A Pilot Study

PubMed Central

Kaur, Punit; Reis, Michael D.; Couchman, Glen R.; Forjuoh, Samuel N.; Greene, John F.; Asea, Alexzander

2010-01-01

In the past decade there has been a dramatic increase in the number of Americans considered obese. Over this same period, the number of individuals diagnosed with diabetes has increased by over 40%. Interestingly, in a great number of cases individuals considered obese develop diabetes later on. Although a link between obesity and diabetes has been suggested, conclusive scientific evidence is thus far just beginning to emerge. The present pilot study is designed to identify a possible link between obesity and diabetes. The plasma proteome is a desirable biological sample due to their accessibility and representative complexity due, in part, to the wide dynamic range of protein concentrations, which lead to the discovery of new protein markers. Here we present the results for the specific depletion of 14 high-abundant proteins from the plasma samples of obese and diabetic patients. Comparative proteomic profiling of plasma from individuals with either diabetes or obesity and individuals with both obesity and diabetes revealed SERPINE 1 as a possible candidate protein of interest, which might be a link between obesity and diabetes. PMID:21113241

SERPINE 1 Links Obesity and Diabetes: A Pilot Study.

PubMed

Kaur, Punit; Reis, Michael D; Couchman, Glen R; Forjuoh, Samuel N; Greene, John F; Asea, Alexzander

2010-06-01

In the past decade there has been a dramatic increase in the number of Americans considered obese. Over this same period, the number of individuals diagnosed with diabetes has increased by over 40%. Interestingly, in a great number of cases individuals considered obese develop diabetes later on. Although a link between obesity and diabetes has been suggested, conclusive scientific evidence is thus far just beginning to emerge. The present pilot study is designed to identify a possible link between obesity and diabetes. The plasma proteome is a desirable biological sample due to their accessibility and representative complexity due, in part, to the wide dynamic range of protein concentrations, which lead to the discovery of new protein markers. Here we present the results for the specific depletion of 14 high-abundant proteins from the plasma samples of obese and diabetic patients. Comparative proteomic profiling of plasma from individuals with either diabetes or obesity and individuals with both obesity and diabetes revealed SERPINE 1 as a possible candidate protein of interest, which might be a link between obesity and diabetes.

The UniProtKB guide to the human proteome

PubMed Central

Breuza, Lionel; Poux, Sylvain; Estreicher, Anne; Famiglietti, Maria Livia; Magrane, Michele; Tognolli, Michael; Bridge, Alan; Baratin, Delphine; Redaschi, Nicole

2016-01-01

Advances in high-throughput and advanced technologies allow researchers to routinely perform whole genome and proteome analysis. For this purpose, they need high-quality resources providing comprehensive gene and protein sets for their organisms of interest. Using the example of the human proteome, we will describe the content of a complete proteome in the UniProt Knowledgebase (UniProtKB). We will show how manual expert curation of UniProtKB/Swiss-Prot is complemented by expert-driven automatic annotation to build a comprehensive, high-quality and traceable resource. We will also illustrate how the complexity of the human proteome is captured and structured in UniProtKB. Database URL: www.uniprot.org PMID:26896845

CPTAC Accelerates Precision Proteomics Biomedical Research | Office of Cancer Clinical Proteomics Research

Cancer.gov

The accurate quantitation of proteins or peptides using Mass Spectrometry (MS) is gaining prominence in the biomedical research community as an alternative method for analyte measurement. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigators have been at the forefront in the promotion of reproducible MS techniques, through the development and application of standardized proteomic methods for protein quantitation on biologically relevant samples.

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

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

Diminished superoxide generation is associated with respiratory chain dysfunction and changes in the mitochondrial proteome of sensory neurons from diabetic rats.

PubMed

Akude, Eli; Zherebitskaya, Elena; Chowdhury, Subir K Roy; Smith, Darrell R; Dobrowsky, Rick T; Fernyhough, Paul

2011-01-01

Impairments in mitochondrial function have been proposed to play a role in the etiology of diabetic sensory neuropathy. We tested the hypothesis that mitochondrial dysfunction in axons of sensory neurons in type 1 diabetes is due to abnormal activity of the respiratory chain and an altered mitochondrial proteome. Proteomic analysis using stable isotope labeling with amino acids in cell culture (SILAC) determined expression of proteins in mitochondria from dorsal root ganglia (DRG) of control, 22-week-old streptozotocin (STZ)-diabetic rats, and diabetic rats treated with insulin. Rates of oxygen consumption and complex activities in mitochondria from DRG were measured. Fluorescence imaging of axons of cultured sensory neurons determined the effect of diabetes on mitochondrial polarization status, oxidative stress, and mitochondrial matrix-specific reactive oxygen species (ROS). Proteins associated with mitochondrial dysfunction, oxidative phosphorylation, ubiquinone biosynthesis, and the citric acid cycle were downregulated in diabetic samples. For example, cytochrome c oxidase subunit IV (COX IV; a complex IV protein) and NADH dehydrogenase Fe-S protein 3 (NDUFS3; a complex I protein) were reduced by 29 and 36% (P < 0.05), respectively, in diabetes and confirmed previous Western blot studies. Respiration and mitochondrial complex activity was significantly decreased by 15 to 32% compared with control. The axons of diabetic neurons exhibited oxidative stress and depolarized mitochondria, an aberrant adaption to oligomycin-induced mitochondrial membrane hyperpolarization, but reduced levels of intramitochondrial superoxide compared with control. Abnormal mitochondrial function correlated with a downregulation of mitochondrial proteins, with components of the respiratory chain targeted in lumbar DRG in diabetes. The reduced activity of the respiratory chain was associated with diminished superoxide generation within the mitochondrial matrix and did not contribute to oxidative stress in axons of diabetic neurons. Alternative pathways involving polyol pathway activity appear to contribute to raised ROS in axons of diabetic neurons under high glucose concentration.

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

Aspartate aminotransferase is potently inhibited by copper complexes: Exploring copper complex-binding proteome.

PubMed

Jia, Yuqi; Lu, Liping; Yuan, Caixia; Feng, Sisi; Zhu, Miaoli

2017-05-01

Recent researches indicated that a copper complex-binding proteome that potently interacted with copper complexes and then influenced cellular metabolism might exist in organism. In order to explore the copper complex-binding proteome, a copper chelating ion-immobilized affinity chromatography (Cu-IMAC) column and mass spectrometry were used to separate and identify putative Cu-binding proteins in primary rat hepatocytes. A total of 97 putative Cu-binding proteins were isolated and identified. Five higher abundance proteins, aspartate aminotransferase (AST), malate dehydrogenase (MDH), catalase (CAT), calreticulin (CRT) and albumin (Alb) were further purified using a SP-, and (or) Q-Sepharose Fast Flow column. The interaction between the purified proteins and selected 11 copper complexes and CuCl 2 was investigated. The enzymes inhibition tests demonstrated that AST was potently inhibited by copper complexes while MDH and CAT were weakly inhibited. Schiff-based copper complexes 6 and 7 potently inhibited AST with the IC 50 value of 3.6 and 7.2μM, respectively and exhibited better selectivity over MDH and CAT. Fluorescence titration results showed the two complexes tightly bound to AST with binding constant of 3.89×10 6 and 3.73×10 6 M -1 , respectively and a stoichiometry ratio of 1:1. Copper complex 6 was able to enter into HepG2 cells and further inhibit intracellular AST activity. Copyright © 2017 Elsevier Inc. All rights reserved.

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders

PubMed Central

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-01-01

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions. PMID:28452939

Three dimensional liquid chromatography coupling ion exchange chromatography/hydrophobic interaction chromatography/reverse phase chromatography for effective protein separation in top-down proteomics.

PubMed

Valeja, Santosh G; Xiu, Lichen; Gregorich, Zachery R; Guner, Huseyin; Jin, Song; Ge, Ying

2015-01-01

To address the complexity of the proteome in mass spectrometry (MS)-based top-down proteomics, multidimensional liquid chromatography (MDLC) strategies that can effectively separate proteins with high resolution and automation are highly desirable. Although various MDLC methods that can effectively separate peptides from protein digests exist, very few MDLC strategies, primarily consisting of 2DLC, are available for intact protein separation, which is insufficient to address the complexity of the proteome. We recently demonstrated that hydrophobic interaction chromatography (HIC) utilizing a MS-compatible salt can provide high resolution separation of intact proteins for top-down proteomics. Herein, we have developed a novel 3DLC strategy by coupling HIC with ion exchange chromatography (IEC) and reverse phase chromatography (RPC) for intact protein separation. We demonstrated that a 3D (IEC-HIC-RPC) approach greatly outperformed the conventional 2D IEC-RPC approach. For the same IEC fraction (out of 35 fractions) from a crude HEK 293 cell lysate, a total of 640 proteins were identified in the 3D approach (corresponding to 201 nonredundant proteins) as compared to 47 in the 2D approach, whereas simply prolonging the gradients in RPC in the 2D approach only led to minimal improvement in protein separation and identifications. Therefore, this novel 3DLC method has great potential for effective separation of intact proteins to achieve deep proteome coverage in top-down proteomics.

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

PubMed

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

2013-10-01

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

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

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

2004-11-01

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

Urinary proteomics in renal pathophysiology: Impact of proteinuria.

PubMed

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

2015-06-01

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

Low-molecular-weight color pI markers to monitor on-line the peptide focusing process in OFFGEL fractionation.

PubMed

Michelland, Sylvie; Bourgoin-Voillard, Sandrine; Cunin, Valérie; Tollance, Axel; Bertolino, Pascal; Slais, Karel; Seve, Michel

2017-08-01

High-throughput mass spectrometry-based proteomic analysis requires peptide fractionation to simplify complex biological samples and increase proteome coverage. OFFGEL fractionation technology became a common method to separate peptides or proteins using isoelectric focusing in an immobilized pH gradient. However, the OFFGEL focusing process may be further optimized and controlled in terms of separation time and pI resolution. Here we evaluated OFFGEL technology to separate peptides from different samples in the presence of low-molecular-weight (LMW) color pI markers to visualize the focusing process. LMW color pI markers covering a large pH range were added to the peptide mixture before OFFGEL fractionation using a 24-wells device encompassing the pH range 3-10. We also explored the impact of LMW color pI markers on peptide fractionation labeled previously for iTRAQ. Then, fractionated peptides were separated by RP_HPLC prior to MS analysis using MALDI-TOF/TOF mass spectrometry in MS and MS/MS modes. Here we report the performance of the peptide focusing process in the presence of LMW color pI markers as on-line trackers during the OFFGEL process and the possibility to use them as pI controls for peptide focusing. This method improves the workflow for peptide fractionation in a bottom-up proteomic approach with or without iTRAQ labeling. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metaproteomics as a Complementary Approach to Gut Microbiota in Health and Disease

NASA Astrophysics Data System (ADS)

Petriz, Bernardo A.; Franco, Octávio L.

2017-01-01

Classic studies on phylotype profiling are limited to the identification of microbial constituents, where information is lacking about the molecular interaction of these bacterial communities with the host genome and the possible outcomes in host biology. A range of OMICs approaches have provided great progress linking the microbiota to health and disease. However, the investigation of this context through proteomic mass spectrometry-based tools is still being improved. Therefore, metaproteomics or community proteogenomics has emerged as a complementary approach to metagenomic data, as a field in proteomics aiming to perform large-scale characterization of proteins from environmental microbiota such as the human gut. The advances in molecular separation methods coupled with mass spectrometry (e.g. LC-MS/MS) and proteome bioinformatics have been fundamental in these novel large-scale metaproteomic studies, which have further been performed in a wide range of samples including soil, plant and human environments. Metaproteomic studies will make major progress if a comprehensive database covering the genes and expresses proteins from all gut microbial species is developed. To this end, we here present some of the main limitations of metaproteomic studies in complex microbiota environments such as the gut, also addressing the up-to-date pipelines in sample preparation prior to fractionation/separation and mass spectrometry analysis. In addition, a novel approach to the limitations of metagenomic databases is also discussed. Finally, prospects are addressed regarding the application of metaproteomic analysis using a unified host-microbiome gene database and other meta-OMICs platforms.

Characterization of individual mouse cerebrospinal fluid proteomes

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

Smith, Jeffrey S.; Angel, Thomas E.; Chavkin, Charles

2014-03-20

Analysis of cerebrospinal fluid (CSF) offers key insight into the status of the central nervous system. Characterization of murine CSF proteomes can provide a valuable resource for studying central nervous system injury and disease in animal models. However, the small volume of CSF in mice has thus far limited individual mouse proteome characterization. Through non-terminal CSF extractions in C57Bl/6 mice and high-resolution liquid chromatography-mass spectrometry analysis of individual murine samples, we report the most comprehensive proteome characterization of individual murine CSF to date. Utilizing stringent protein inclusion criteria that required the identification of at least two unique peptides (1% falsemore » discovery rate at the peptide level) we identified a total of 566 unique proteins, including 128 proteins from three individual CSF samples that have been previously identified in brain tissue. Our methods and analysis provide a mechanism for individual murine CSF proteome analysis.« less

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

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

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

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

P2P proteomics -- data sharing for enhanced protein identification

PubMed Central

2012-01-01

Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories. PMID:22293032

Availability of MudPIT data for classification of biological samples.

PubMed

Silvestre, Dario Di; Zoppis, Italo; Brambilla, Francesca; Bellettato, Valeria; Mauri, Giancarlo; Mauri, Pierluigi

2013-01-14

Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins. Globally, protein and peptide data allowed a better discriminant informative content than experimental mass spectra (overall accuracy higher than 87% in both collection 1 and 2). These results indicate that sequencing of peptides and proteins reduces the experimental noise affecting the raw mass spectra, and allows the extraction of more informative features available for the effective classification of samples. In addition, proteins and peptides features selected by SVM matched for 80% with the differentially expressed proteins identified by the MAProMa software. These findings confirm the availability of the most label-free quantitative methods based on processing of spectral count and SEQUEST-based SCORE values. On the other hand, it stresses the usefulness of MudPIT data for a correct grouping of sample phenotypes, by applying both supervised and unsupervised learning algorithms. This capacity permit the evaluation of actual samples and it is a good starting point to translate proteomic methodology to clinical application.

Megadalton Complexes in the Chloroplast Stroma of Arabidopsis thaliana Characterized by Size Exclusion Chromatography, Mass Spectrometry, and Hierarchical Clustering*

PubMed Central

Olinares, Paul Dominic B.; Ponnala, Lalit; van Wijk, Klaas J.

2010-01-01

To characterize MDa-sized macromolecular chloroplast stroma protein assemblies and to extend coverage of the chloroplast stroma proteome, we fractionated soluble chloroplast stroma in the non-denatured state by size exclusion chromatography with a size separation range up to ∼5 MDa. To maximize protein complex stability and resolution of megadalton complexes, ionic strength and composition were optimized. Subsequent high accuracy tandem mass spectrometry analysis (LTQ-Orbitrap) identified 1081 proteins across the complete native mass range. Protein complexes and assembly states above 0.8 MDa were resolved using hierarchical clustering, and protein heat maps were generated from normalized protein spectral counts for each of the size exclusion chromatography fractions; this complemented previous analysis of stromal complexes up to 0.8 MDa (Peltier, J. B., Cai, Y., Sun, Q., Zabrouskov, V., Giacomelli, L., Rudella, A., Ytterberg, A. J., Rutschow, H., and van Wijk, K. J. (2006) The oligomeric stromal proteome of Arabidopsis thaliana chloroplasts. Mol. Cell. Proteomics 5, 114–133). This combined experimental and bioinformatics analyses resolved chloroplast ribosomes in different assembly and functional states (e.g. 30, 50, and 70 S), which enabled the identification of plastid homologues of prokaryotic ribosome assembly factors as well as proteins involved in co-translational modifications, targeting, and folding. The roles of these ribosome-associating proteins will be discussed. Known RNA splice factors (e.g. CAF1/WTF1/RNC1) as well as uncharacterized proteins with RNA-binding domains (pentatricopeptide repeat, RNA recognition motif, and chloroplast ribosome maturation), RNases, and DEAD box helicases were found in various sized complexes. Chloroplast DNA (>3 MDa) was found in association with the complete heteromeric plastid-encoded DNA polymerase complex, and a dozen other DNA-binding proteins, e.g. DNA gyrase, topoisomerase, and various DNA repair enzymes. The heteromeric ≥5-MDa pyruvate dehydrogenase complex and the 0.8–1-MDa acetyl-CoA carboxylase complex associated with uncharacterized biotin carboxyl carrier domain proteins constitute the entry point to fatty acid metabolism in leaves; we suggest that their large size relates to the need for metabolic channeling. Protein annotations and identification data are available through the Plant Proteomics Database, and mass spectrometry data are available through Proteomics Identifications database. PMID:20423899

Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline

NASA Astrophysics Data System (ADS)

Rardin, Matthew J.

2018-04-01

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g., detergents) necessitating a variety of sample cleanup procedures. Efforts to understand and mitigate sample contamination are a continual source of disruption with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, I developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows rapid assessment of sample integrity and indicates potential sources of contamination. [Figure not available: see fulltext.

The Escherichia coli Peripheral Inner Membrane Proteome*

PubMed Central

Papanastasiou, Malvina; Orfanoudaki, Georgia; Koukaki, Marina; Kountourakis, Nikos; Sardis, Marios Frantzeskos; Aivaliotis, Michalis; Karamanou, Spyridoula; Economou, Anastassios

2013-01-01

Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with biological membrane surfaces that we are only beginning to decipher. PMID:23230279

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

PubMed

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

2017-12-01

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

A Proteomics Analysis of the Effects of Chronic Hemiparetic Stroke on Troponin T Expression in Human Vastus Lateralis

PubMed Central

Rabek, Jeffrey P.; Hafer-Macko, Charlene E.; Amaning, James K.; DeFord, James H.; Dimayuga, Vincent L.; Madsen, Mark A.; Macko, Richard F.

2009-01-01

Stroke disability is attributed to upper motor neuron deficits resulting from ischemic brain injury. We have developed proteome maps of the Vastus lateralis to examine the effects of ischemic brain injury on paretic skeletal muscle myofilament proteins. Proteomics analyses from seven hemiparetic stroke patients have detected a decrease of three troponin T isoforms in the paretic muscle suggesting that myosin–actin interactions may be attenuated. We propose that ischemic brain injury may prevent troponin T participation in complex formation thereby affecting the protein interactions associated with excitation–contraction coupling. We have also detected a novel skeletal troponin T isoform that has a C-terminal variation. Our data suggest that the decreased slow troponin T isoform pools in the paretic limb may contribute to the gait deficit after stroke. The complexity of the neurological deficit on Vastus lateralis is suggested by the multiple changes in proteins detected by our proteomics mapping. PMID:19447848

Combining proteomics and metabolite analyses to unravel cadmium stress-response in poplar leaves.

PubMed

Kieffer, Pol; Planchon, Sébastien; Oufir, Mouhssin; Ziebel, Johanna; Dommes, Jacques; Hoffmann, Lucien; Hausman, Jean-François; Renaut, Jenny

2009-01-01

A proteomic analysis of poplar leaves exposed to cadmium, combined with biochemical analysis of pigments and carbohydrates revealed changes in primary carbon metabolism. Proteomic results suggested that photosynthesis was slightly affected. Together with a growth inhibition, photoassimilates were less needed for developmental processes and could be stored in the form of hexoses or complex sugars, acting also as osmoprotectants. Simultaneously, mitochondrial respiration was upregulated, providing energy needs of cadmium-exposed plants.

Proteomic profiling of human plasma for cancer biomarker discovery.

PubMed

Huang, Zhao; Ma, Linguang; Huang, Canhua; Li, Qifu; Nice, Edouard C

2017-03-01

Over the past decades, substantial advances have been made in both the early diagnosis and accurate prognosis of many cancers because of the impressive development of novel proteomic strategies. However, it remains difficult to standardize proteomic approaches. In addition, the heterogeneity of proteins in distinct tissues results in incomplete population of the whole proteome, which inevitably limits its clinical practice. As one of the most complex proteomes in the human body, the plasma proteome contains secreted proteins originating from multiple organs and tissues, making it a favorable matrix for comprehensive biomarker discovery. Here, we will discuss the roles of plasma proteome profiling in cancer biomarker discovery and validation, and highlight both the inherent advantages and disadvantages. Although several hurdles lay ahead, further advances in this technology will greatly increase our understanding of cancer biology, reveal new biomarkers and biomarker panels, and open a new avenue for more efficient early diagnosis and surveillance of cancer, leading toward personalized medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feasibility of investigating differential proteomic expression in depression: implications for biomarker development in mood disorders

PubMed Central

Frye, M A; Nassan, M; Jenkins, G D; Kung, S; Veldic, M; Palmer, B A; Feeder, S E; Tye, S J; Choi, D S; Biernacka, J M

2015-01-01

The objective of this study was to determine whether proteomic profiling in serum samples can be utilized in identifying and differentiating mood disorders. A consecutive sample of patients with a confirmed diagnosis of unipolar (UP n=52) or bipolar depression (BP-I n=46, BP-II n=49) and controls (n=141) were recruited. A 7.5-ml blood sample was drawn for proteomic multiplex profiling of 320 proteins utilizing the Myriad RBM Discovery Multi-Analyte Profiling platform. After correcting for multiple testing and adjusting for covariates, growth differentiation factor 15 (GDF-15), hemopexin (HPX), hepsin (HPN), matrix metalloproteinase-7 (MMP-7), retinol-binding protein 4 (RBP-4) and transthyretin (TTR) all showed statistically significant differences among groups. In a series of three post hoc analyses correcting for multiple testing, MMP-7 was significantly different in mood disorder (BP-I+BP-II+UP) vs controls, MMP-7, GDF-15, HPN were significantly different in bipolar cases (BP-I+BP-II) vs controls, and GDF-15, HPX, HPN, RBP-4 and TTR proteins were all significantly different in BP-I vs controls. Good diagnostic accuracy (ROC-AUC⩾0.8) was obtained most notably for GDF-15, RBP-4 and TTR when comparing BP-I vs controls. While based on a small sample not adjusted for medication state, this discovery sample with a conservative method of correction suggests feasibility in using proteomic panels to assist in identifying and distinguishing mood disorders, in particular bipolar I disorder. Replication studies for confirmation, consideration of state vs trait serial assays to delineate proteomic expression of bipolar depression vs previous mania, and utility studies to assess proteomic expression profiling as an advanced decision making tool or companion diagnostic are encouraged. PMID:26645624

Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

PubMed Central

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N.; Carter, Jeff; Dalby, Andrew B.; Eaton, Bruce E.; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Koch, Tad H.; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K.; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M.; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I.; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D.; Vrkljan, Mike; Walker, Jeffrey J.; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K.; Wolfson, Alexey; Wolk, Steven K.; Zhang, Chi; Zichi, Dom

2010-01-01

Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine. PMID:21165148

A Mouse to Human Search for Plasma Proteome Changes Associated with Pancreatic Tumor Development

PubMed Central

Faca, Vitor M; Song, Kenneth S; Wang, Hong; Zhang, Qing; Krasnoselsky, Alexei L; Newcomb, Lisa F; Plentz, Ruben R; Gurumurthy, Sushma; Redston, Mark S; Pitteri, Sharon J; Pereira-Faca, Sandra R; Ireton, Renee C; Katayama, Hiroyuki; Glukhova, Veronika; Phanstiel, Douglas; Brenner, Dean E; Anderson, Michelle A; Misek, David; Scholler, Nathalie; Urban, Nicole D; Barnett, Matt J; Edelstein, Cim; Goodman, Gary E; Thornquist, Mark D; McIntosh, Martin W; DePinho, Ronald A; Bardeesy, Nabeel; Hanash, Samir M

2008-01-01

Background The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. Methods and Findings Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. Conclusions Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection. PMID:18547137

Proteomic Analysis of the Soybean Symbiosome Identifies New Symbiotic Proteins*

PubMed Central

Clarke, Victoria C.; Loughlin, Patrick C.; Gavrin, Aleksandr; Chen, Chi; Brear, Ella M.; Day, David A.; Smith, Penelope M.C.

2015-01-01

Legumes form a symbiosis with rhizobia in which the plant provides an energy source to the rhizobia bacteria that it uses to fix atmospheric nitrogen. This nitrogen is provided to the legume plant, allowing it to grow without the addition of nitrogen fertilizer. As part of the symbiosis, the bacteria in the infected cells of a new root organ, the nodule, are surrounded by a plant-derived membrane, the symbiosome membrane, which becomes the interface between the symbionts. Fractions containing the symbiosome membrane (SM) and material from the lumen of the symbiosome (peribacteroid space or PBS) were isolated from soybean root nodules and analyzed using nongel proteomic techniques. Bicarbonate stripping and chloroform-methanol extraction of isolated SM were used to reduce complexity of the samples and enrich for hydrophobic integral membrane proteins. One hundred and ninety-seven proteins were identified as components of the SM, with an additional fifteen proteins identified from peripheral membrane and PBS protein fractions. Proteins involved in a range of cellular processes such as metabolism, protein folding and degradation, membrane trafficking, and solute transport were identified. These included a number of proteins previously localized to the SM, such as aquaglyceroporin nodulin 26, sulfate transporters, remorin, and Rab7 homologs. Among the proteome were a number of putative transporters for compounds such as sulfate, calcium, hydrogen ions, peptide/dicarboxylate, and nitrate, as well as transporters for which the substrate is not easy to predict. Analysis of the promoter activity for six genes encoding putative SM proteins showed nodule specific expression, with five showing expression only in infected cells. Localization of two proteins was confirmed using GFP-fusion experiments. The data have been deposited to the ProteomeXchange with identifier PXD001132. This proteome will provide a rich resource for the study of the legume-rhizobium symbiosis. PMID:25724908

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

PubMed Central

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

2008-01-01

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

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

PubMed Central

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

2015-01-01

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

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

DOE PAGES

Marlow, Jeffery; Skennerton, Connor T.; Li, Zhou; ...

2016-04-29

Marine methane seep habitats represent an important control on the global flux of methane between the subsurface and water column reservoirs. Meta-omics studies have begun to outline community-wide metabolic potential, but expression patterns of proteins that enact sulfate-mediated anaerobic methane oxidation in seeps are poorly characterized. Proteomic stable isotope probing (proteomic SIP) offers an additional layer of information for characterizing phylogenetically specific, functionally relevant activity in mixed microbial communities. Here we applied proteomic SIP to 15NH4+ and CH4 amended seep sediment microcosms in an attempt to track the protein synthesis of slow-growing, low-energy microbial systems. Across all samples, 3495 proteinsmore » were identified, 21% of which were 15N-labeled. We observed active synthesis (15N enrichment) of all proteins believed to be involved in sulfate reduction and reverse methanogenesis including methylenetetrahydromethanopterin reductase (Mer). The abundance and phylogenetic range of methyl-coenzyme M reductase (Mcr) orthologs produced during incubation experiments suggests that seeps provide sufficient niches for multiple organisms performing analogous metabolisms. Twenty-eight previously unreported post-translational modifications of McrA were measured, indicating dynamic enzymatic machinery and offering a dimension of functional diversity beyond gene-dictated sequence. RNA polymerase associated with putative sulfur-oxidizing Epsilonproteobacteria and aerobic Gammaproteobacteria were more abundant among pre-incubation proteins, suggesting diminished metabolic activity in long-term anoxic, sulfidic experimental incubations. Twenty-six proteins of unknown function were detected in all proteomic experiments and actively expressed in labeled experiments, suggesting that they play important roles in methane seep ecosystems. The addition of stable isotope probing to environmental proteomics experiments provides a mechanism to begin to assess the degree to which diagnostic meatbolic proteins are long-lived or acively synthesized in complex, slow-growing microbial communities. Our work here demonstrates that sediment-hosted microbial assemblages in marine methane seeps are dynamic, heterogeneous systems with broad functional diversity.« less

Protein Equalizer Technology : the quest for a "democratic proteome".

PubMed

Righetti, Pier Giorgio; Boschetti, Egisto; Lomas, Lee; Citterio, Attilio

2006-07-01

No proteome can be considered "democratic", but rather "oligarchic", since a few proteins dominate the landscape and often obliterate the signal of the rare ones. This is the reason why most scientists lament that, in proteome analysis, the same set of abundant proteins is seen again and again. A host of pre-fractionation techniques have been described, but all of them, one way or another, are besieged by problems, in that they are based on a "depletion principle", i.e. getting rid of the unwanted species. Yet "democracy" calls not for killing the enemy, but for giving "equal rights" to all people. One way to achieve that would be the use of "Protein Equalizer Technology" for reducing protein concentration differences. This comprises a diverse library of combinatorial ligands coupled to spherical porous beads. When these beads come into contact with complex proteomes (e.g. human urine and serum, egg white, and any cell lysate, for that matter) of widely differing protein composition and relative abundances, they are able to "equalize" the protein population, by sharply reducing the concentration of the most abundant components, while simultaneously enhancing the concentration of the most dilute species. It is felt that this novel method could offer a strong step forward in bringing the "unseen proteome" (due to either low abundance and/or presence of interference) within the detection capabilities of current proteomics detection methods. Examples are given of equalization of human urine and serum samples, resulting in the discovery of a host of proteins never reported before. Additionally, these beads can be used to remove host cell proteins from purified recombinant proteins or protein purified from natural sources that are intended for human consumption. These proteins typically reach purities of the order of 98%: higher purities often become prohibitively expensive. Yet, if incubated with "equalizer beads", these last impurities can be effectively removed at a small cost and with minute losses of the main, valuable product.

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

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

Marlow, Jeffery; Skennerton, Connor T.; Li, Zhou

Marine methane seep habitats represent an important control on the global flux of methane between the subsurface and water column reservoirs. Meta-omics studies have begun to outline community-wide metabolic potential, but expression patterns of proteins that enact sulfate-mediated anaerobic methane oxidation in seeps are poorly characterized. Proteomic stable isotope probing (proteomic SIP) offers an additional layer of information for characterizing phylogenetically specific, functionally relevant activity in mixed microbial communities. Here we applied proteomic SIP to 15NH4+ and CH4 amended seep sediment microcosms in an attempt to track the protein synthesis of slow-growing, low-energy microbial systems. Across all samples, 3495 proteinsmore » were identified, 21% of which were 15N-labeled. We observed active synthesis (15N enrichment) of all proteins believed to be involved in sulfate reduction and reverse methanogenesis including methylenetetrahydromethanopterin reductase (Mer). The abundance and phylogenetic range of methyl-coenzyme M reductase (Mcr) orthologs produced during incubation experiments suggests that seeps provide sufficient niches for multiple organisms performing analogous metabolisms. Twenty-eight previously unreported post-translational modifications of McrA were measured, indicating dynamic enzymatic machinery and offering a dimension of functional diversity beyond gene-dictated sequence. RNA polymerase associated with putative sulfur-oxidizing Epsilonproteobacteria and aerobic Gammaproteobacteria were more abundant among pre-incubation proteins, suggesting diminished metabolic activity in long-term anoxic, sulfidic experimental incubations. Twenty-six proteins of unknown function were detected in all proteomic experiments and actively expressed in labeled experiments, suggesting that they play important roles in methane seep ecosystems. The addition of stable isotope probing to environmental proteomics experiments provides a mechanism to begin to assess the degree to which diagnostic meatbolic proteins are long-lived or acively synthesized in complex, slow-growing microbial communities. Our work here demonstrates that sediment-hosted microbial assemblages in marine methane seeps are dynamic, heterogeneous systems with broad functional diversity.« less

Secretomic survey of Trichoderma harzianum grown on plant biomass substrates.

PubMed

Gómez-Mendoza, Diana Paola; Junqueira, Magno; do Vale, Luis Henrique Ferreira; Domont, Gilberto Barbosa; Ferreira Filho, Edivaldo Ximenes; Sousa, Marcelo Valle de; Ricart, Carlos André Ornelas

2014-04-04

The present work aims at characterizing T. harzianum secretome when the fungus is grown in synthetic medium supplemented with one of the four substrates: glucose, cellulose, xylan, and sugarcane bagasse (SB). The characterization was done by enzymatic assays and proteomic analysis using 2-DE/MALDI-TOF and gel-free shotgun LC-MS/MS. The results showed that SB induced the highest cellulolytic and xylanolytic activities when compared with the other substrates, while remarkable differences in terms of number and distribution of protein spots in 2-DE gels were also observed among the samples. Additionally, treatment of the secretomes with PNGase F revealed that most spot trails in 2-DE gels corresponded to N-glycosylated proteoforms. The LC-MS/MS analysis of the samples identified 626 different protein groups, including carbohydrate-active enzymes and accessory, noncatalytic, and cell-wall-associated proteins. Although the SB-induced secretome displayed the highest cellulolytic and xylanolytic activities, it did not correspond to a higher proteome complexity because CM-cellulose-induced secretome was significantly more diverse. Among the identified proteins, 73% were exclusive to one condition, while only 5% were present in all samples. Therefore, this study disclosed the variation of T. harzianum secretome in response to different substrates and revealed the diversity of the fungus enzymatic toolbox.

Comparison of analytical methods for profiling N- and O-linked glycans from cultured cell lines

PubMed Central

Togayachi, Akira; Azadi, Parastoo; Ishihara, Mayumi; Geyer, Rudolf; Galuska, Christina; Geyer, Hildegard; Kakehi, Kazuaki; Kinoshita, Mitsuhiro; Karlsson, Niclas G.; Jin, Chunsheng; Kato, Koichi; Yagi, Hirokazu; Kondo, Sachiko; Kawasaki, Nana; Hashii, Noritaka; Kolarich, Daniel; Stavenhagen, Kathrin; Packer, Nicolle H.; Thaysen-Andersen, Morten; Nakano, Miyako; Taniguchi, Naoyuki; Kurimoto, Ayako; Wada, Yoshinao; Tajiri, Michiko; Yang, Pengyuan; Cao, Weiqian; Li, Hong; Rudd, Pauline M.; Narimatsu, Hisashi

2016-01-01

The Human Disease Glycomics/Proteome Initiative (HGPI) is an activity in the Human Proteome Organization (HUPO) supported by leading researchers from international institutes and aims at development of disease-related glycomics/glycoproteomics analysis techniques. Since 2004, the initiative has conducted three pilot studies. The first two were N- and O-glycan analyses of purified transferrin and immunoglobulin-G and assessed the most appropriate analytical approach employed at the time. This paper describes the third study, which was conducted to compare different approaches for quantitation of N- and O-linked glycans attached to proteins in crude biological samples. The preliminary analysis on cell pellets resulted in wildly varied glycan profiles, which was probably the consequence of variations in the pre-processing sample preparation methodologies. However, the reproducibility of the data was not improved dramatically in the subsequent analysis on cell lysate fractions prepared in a specified method by one lab. The study demonstrated the difficulty of carrying out a complete analysis of the glycome in crude samples by any single technology and the importance of rigorous optimization of the course of analysis from preprocessing to data interpretation. It suggests that another collaborative study employing the latest technologies in this rapidly evolving field will help to realize the requirements of carrying out the large-scale analysis of glycoproteins in complex cell samples. PMID:26511985

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

PubMed

Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C

2013-10-01

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.

Differential proteomics study of platelets in asymptomatic constitutional macrothrombocytopenia: altered levels of cytoskeletal proteins.

PubMed

Karmakar, Shilpita; Saha, Sutapa; Banerjee, Debasis; Chakrabarti, Abhijit

2015-01-01

Harris platelet syndrome (HPS), also known as asymptomatic constitutional macrothrombocytopenia (ACMT), is an autosomal dominant platelet disorder characterized by mild-to-severe thrombocytopenia and giant platelets with normal platelet aggregation and absence of bleeding symptoms. We have attempted a comparative proteomics study for profiling of platelet proteins in healthy vs. pathological states to discover characteristic protein expression changes in macrothrombocytes and decipher the factors responsible for the functionally active yet morphologically distinct platelets. We have used 2-D gel-based protein separation techniques coupled with MALDI-ToF/ToF-based mass spectrometric identification and characterization of the proteins to investigate the differential proteome profiling of platelet proteins isolated from the peripheral blood samples of patients and normal volunteers. Our study revealed altered levels of actin-binding proteins such as myosin light chain, coactosin-like protein, actin-related protein 2/3 complex, and transgelin2 that hint toward the cytoskeletal changes necessary to maintain the structural and functional integrity of macrothrombocytes. We have also observed over expressed levels of peroxiredoxin2 that signifies the prevailing oxidative stress in these cells. Additionally, altered levels of protein disulfide isomerase and transthyretin provide insights into the measures adapted by the macrothrombocytes to maintain their normal functional activity. This first proteomics study of platelets from ACMT may provide an understanding of the structural stability and normal functioning of these platelets in spite of their large size. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

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

PubMed

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

2015-03-01

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

Proteomics analysis suggests broad functional changes in potato leaves triggered by phosphites and a complex indirect mode of action against Phytophthora infestans.

PubMed

Lim, Sanghyun; Borza, Tudor; Peters, Rick D; Coffin, Robert H; Al-Mughrabi, Khalil I; Pinto, Devanand M; Wang-Pruski, Gefu

2013-11-20

Phosphite (salts of phosphorous acid; Phi)-based fungicides are increasingly used in controlling oomycete pathogens, such as the late blight agent Phytophthora infestans. In plants, low amounts of Phi induce pathogen resistance through an indirect mode of action. We used iTRAQ-based quantitative proteomics to investigate the effects of phosphite on potato plants before and after infection with P. infestans. Ninety-three (62 up-regulated and 31 down-regulated) differentially regulated proteins, from a total of 1172 reproducibly identified proteins, were identified in the leaf proteome of Phi-treated potato plants. Four days post-inoculation with P. infestans, 16 of the 31 down-regulated proteins remained down-regulated and 42 of the 62 up-regulated proteins remained up-regulated, including 90% of the defense proteins. This group includes pathogenesis-related, stress-responsive, and detoxification-related proteins. Callose deposition and ultrastructural analyses of leaf tissues after infection were used to complement the proteomics approach. This study represents the first comprehensive proteomics analysis of the indirect mode of action of Phi, demonstrating broad effects on plant defense and plant metabolism. The proteomics data and the microscopy study suggest that Phi triggers a hypersensitive response that is responsible for induced resistance of potato leaves against P. infestans. Phosphie triggers complex functional changes in potato leaves that are responsible for the induced resistance against Phytophthora infestans. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Proteomics of filamentous fungi.

PubMed

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

2007-09-01

Proteomic analysis, defined here as the global assessment of cellular proteins expressed in a particular biological state, is a powerful tool that can provide a systematic understanding of events at the molecular level. Proteomic studies of filamentous fungi have only recently begun to appear in the literature, despite the prevalence of these organisms in the biotechnology industry, and their importance as both human and plant pathogens. Here, we review recent publications that have used a proteomic approach to develop a better understanding of filamentous fungi, highlighting sample preparation methods and whole-cell cytoplasmic proteomics, as well as subproteomics of cell envelope, mitochondrial and secreted proteins.

Proteomic analysis highlights the molecular complexities of native Kv4 channel macromolecular complexes.

PubMed

Marionneau, Céline; Townsend, R Reid; Nerbonne, Jeanne M

2011-04-01

Voltage-gated K(+) (Kv) channels are key determinants of membrane excitability in the nervous and cardiovascular systems, functioning to control resting membrane potentials, shape action potential waveforms and influence the responses to neurotransmitters and neurohormones. Consistent with this functional diversity, multiple types of Kv currents, with distinct biophysical properties and cellular/subcellular distributions, have been identified. Rapidly activating and inactivating Kv currents, typically referred to as I(A) (A-type) in neurons, for example, regulate repetitive firing rates, action potential back-propagation (into dendrites) and modulate synaptic responses. Currents with similar properties, referred to as I(to,f) (fast transient outward), expressed in cardiomyocytes, control the early phase of myocardial action potential repolarization. A number of studies have demonstrated critical roles for pore-forming (α) subunits of the Kv4 subfamily in the generation of native neuronal I(A) and cardiac I(to,f) channels. Studies in heterologous cells have also suggested important roles for a number of Kv channel accessory and regulatory proteins in the generation of functional I(A) and I(to,f) channels. Quantitative mass spectrometry-based proteomic analysis is increasingly recognized as a rapid and, importantly, unbiased, approach to identify the components of native macromolecular protein complexes. The recent application of proteomic approaches to identify the components of native neuronal (and cardiac) Kv4 channel complexes has revealed even greater complexity than anticipated. The continued emphasis on development of improved biochemical and analytical proteomic methods seems certain to accelerate progress and to provide important new insights into the molecular determinants of native ion channel protein complexes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

A DATABASE FOR TRACKING TOXICOGENOMIC SAMPLES AND PROCEDURES WITH GENOMIC, PROTEOMIC AND METABONOMIC COMPONENTS

EPA Science Inventory

A Database for Tracking Toxicogenomic Samples and Procedures with Genomic, Proteomic and Metabonomic Components
Wenjun Bao1, Jennifer Fostel2, Michael D. Waters2, B. Alex Merrick2, Drew Ekman3, Mitchell Kostich4, Judith Schmid1, David Dix1
Office of Research and Developmen...

Proteome Characterization Centers - TCGA

Cancer.gov

The centers, a component of NCI’s Clinical Proteomic Tumor Analysis Consortium, will analyze a subset of TCGA samples to define proteins translated from cancer genomes and their related biological processes.

The proteomic complexity and rise of the primordial ancestor of diversified life

PubMed Central

2011-01-01

Background The last universal common ancestor represents the primordial cellular organism from which diversified life was derived. This urancestor accumulated genetic information before the rise of organismal lineages and is considered to be either a simple 'progenote' organism with a rudimentary translational apparatus or a more complex 'cenancestor' with almost all essential biological processes. Recent comparative genomic studies support the latter model and propose that the urancestor was similar to modern organisms in terms of gene content. However, most of these studies were based on molecular sequences, which are fast evolving and of limited value for deep evolutionary explorations. Results Here we engage in a phylogenomic study of protein domain structure in the proteomes of 420 free-living fully sequenced organisms. Domains were defined at the highly conserved fold superfamily (FSF) level of structural classification and an iterative phylogenomic approach was used to reconstruct max_set and min_set FSF repertoires as upper and lower bounds of the urancestral proteome. While the functional make up of the urancestral sets was complex, they represent only 5-11% of the 1,420 FSFs of extant proteomes and their make up and reuse was at least 5 and 3 times smaller than proteomes of free-living organisms, repectively. Trees of proteomes reconstructed directly from FSFs or from molecular functions, which included the max_set and min_set as articial taxa, showed that urancestors were always placed at their base and rooted the tree of life in Archaea. Finally, a molecular clock of FSFs suggests the min_set reflects urancestral genetic make up more reliably and confirms diversified life emerged about 2.9 billion years ago during the start of planet oxygenation. Conclusions The minimum urancestral FSF set reveals the urancestor had advanced metabolic capabilities, was especially rich in nucleotide metabolism enzymes, had pathways for the biosynthesis of membrane sn1,2 glycerol ester and ether lipids, and had crucial elements of translation, including a primordial ribosome with protein synthesis capabilities. It lacked however fundamental functions, including transcription, processes for extracellular communication, and enzymes for deoxyribonucleotide synthesis. Proteomic history reveals the urancestor is closer to a simple progenote organism but harbors a rather complex set of modern molecular functions. PMID:21612591

Next-Generation Proteomics and Its Application to Clinical Breast Cancer Research.

PubMed

Mardamshina, Mariya; Geiger, Tamar

2017-10-01

Proteomics technology aims to map the protein landscapes of biological samples, and it can be applied to a variety of samples, including cells, tissues, and body fluids. Because the proteins are the main functional molecules in the cells, their levels reflect much more accurately the cellular phenotype and the regulatory processes within them than gene levels, mutations, and even mRNA levels. With the advancement in the technology, it is possible now to obtain comprehensive views of the biological systems and to study large patient cohorts in a streamlined manner. In this review we discuss the technological advancements in mass spectrometry-based proteomics, which allow analysis of breast cancer tissue samples, leading to the first large-scale breast cancer proteomics studies. Furthermore, we discuss the technological developments in blood-based biomarker discovery, which provide the basis for future development of assays for routine clinical use. Although these are only the first steps in implementation of proteomics into the clinic, extensive collaborative work between these worlds will undoubtedly lead to major discoveries and advances in clinical practice. Copyright © 2017 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

CPTC and NIST-sponsored Yeast Reference Material Now Publicly Available | Office of Cancer Clinical Proteomics Research

Cancer.gov

The yeast protein extract (RM8323) developed by National Institute of Standards and Technology (NIST) under the auspices of NCI's CPTC initiative is currently available to the public at https://www-s.nist.gov/srmors/view_detail.cfm?srm=8323. The yeast proteome offers researchers a unique biological reference material. RM8323 is the most extensively characterized complex biological proteome and the only one associated with several large-scale studies to estimate protein abundance across a wide concentration range.

Scientific Workflow Management in Proteomics

PubMed Central

de Bruin, Jeroen S.; Deelder, André M.; Palmblad, Magnus

2012-01-01

Data processing in proteomics can be a challenging endeavor, requiring extensive knowledge of many different software packages, all with different algorithms, data format requirements, and user interfaces. In this article we describe the integration of a number of existing programs and tools in Taverna Workbench, a scientific workflow manager currently being developed in the bioinformatics community. We demonstrate how a workflow manager provides a single, visually clear and intuitive interface to complex data analysis tasks in proteomics, from raw mass spectrometry data to protein identifications and beyond. PMID:22411703

VIDEO: Dr. Henry Rodriguez - Proteogenomics in Cancer Medicine | Office of Cancer Clinical Proteomics Research

Cancer.gov

Dr. Henry Rodriguez, director of the Office of Cancer Clinical Proteomics Research (OCCPR) at NCI, speaks with ecancer television at WIN 2017 about the translation of the proteins expressed in a patient's tumor into a map for druggable targets. By combining genomic and proteomic information (proteogenomics), leading scientists are gaining new insights into ways to detect and treat cancer due to a more complete and unified understanding of complex biological processes.

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

PubMed Central

2012-01-01

Background Accurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis. Methods Biopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots. Results A total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein). Conclusions A distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC. PMID:22726388

Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

PubMed

Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

2012-12-01

To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Advanced proteomic liquid chromatography

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

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-10-26

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput.

Detection of Zn2+ release in nitric oxide treated cells and proteome: dependence on fluorescent sensor and proteomic sulfhydryl groups.

PubMed

Karim, Mohammad R; Petering, David H

2017-04-19

Nitric oxide (NO) is both an important regulatory molecule in biological systems and a toxic xenobiotic. Its oxidation products react with sulfhydryl groups and either nitrosylate or oxidize them. The aerobic reaction of NO supplied by diethylamine NONOate (DEA-NO) with pig kidney LLC-PK 1 cells and Zn-proteins within the isolated proteome was examined with three fluorescent zinc sensors, zinquin (ZQ), TSQ, and FluoZin-3 (FZ-3). Observations of Zn 2+ labilization from Zn-proteins depended on the specific sensor used. Upon cellular exposure to DEA-NO, ZQ sequestered about 13% of the proteomic Zn 2+ as Zn(ZQ) 2 and additional Zn 2+ as proteome·Zn-ZQ ternary complexes. TSQ, a sensor structurally related to ZQ with lower affinity for Zn 2+ , did not form Zn(TSQ) 2 . Instead, Zn 2+ mobilized by DEA-NO was exclusively bound as proteome·Zn-TSQ adducts. Analogous reactions of proteome with ZQ or TSQ in vitro displayed qualitatively similar products. Titration of native proteome with Zn 2+ in the presence of ZQ resulted in the sole formation of proteome·Zn-ZQ species. This result suggested that sulfhydryl groups are involved in non-specific proteomic binding of mobile Zn 2+ and that the appearance of Zn(ZQ) 2 after exposure of cells and proteome to DEA-NO resulted from a reduction in proteomic sulfhydryl ligands, favoring the formation of Zn(ZQ) 2 instead of proteome·Zn-ZQ. With the third sensor, FluoZin-3, neither Zn-FZ-3 nor proteome·Zn-FZ-3 was detected during the reaction of proteome with DEA-NO. Instead, it reacted independently with DEA-NO with a modest enhancement of fluorescence.

Knowledge Translation: Moving Proteomics Science to Innovation in Society.

PubMed

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

2016-06-01

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

The Proteome of the Isolated Chlamydia trachomatis Containing Vacuole Reveals a Complex Trafficking Platform Enriched for Retromer Components

PubMed Central

Fischer, Martina; Jehmlich, Nico; Rose, Laura; Koch, Sophia; Laue, Michael; Renard, Bernhard Y.; Schmidt, Frank; Heuer, Dagmar

2015-01-01

Chlamydia trachomatis is an important human pathogen that replicates inside the infected host cell in a unique vacuole, the inclusion. The formation of this intracellular bacterial niche is essential for productive Chlamydia infections. Despite its importance for Chlamydia biology, a holistic view on the protein composition of the inclusion, including its membrane, is currently missing. Here we describe the host cell-derived proteome of isolated C. trachomatis inclusions by quantitative proteomics. Computational analysis indicated that the inclusion is a complex intracellular trafficking platform that interacts with host cells’ antero- and retrograde trafficking pathways. Furthermore, the inclusion is highly enriched for sorting nexins of the SNX-BAR retromer, a complex essential for retrograde trafficking. Functional studies showed that in particular, SNX5 controls the C. trachomatis infection and that retrograde trafficking is essential for infectious progeny formation. In summary, these findings suggest that C. trachomatis hijacks retrograde pathways for effective infection. PMID:26042774

Proteomic Approaches and Identification of Novel Therapeutic Targets for Alcoholism

PubMed Central

Gorini, Giorgio; Adron Harris, R; Dayne Mayfield, R

2014-01-01

Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction. PMID:23900301

Proteomic analysis of heat treated bitter gourd (Momordica charantia L. var. Hong Kong Green) using 2D-DIGE.

PubMed

Ng, Zhi Xiang; Chua, Kek Heng; Kuppusamy, Umah Rani

2014-04-01

This study aimed to investigate the changes in the proteome of bitter gourd prior to and after subjecting to boiling and microwaving. A comparative analysis of the proteome profiles of raw and thermally treated bitter gourds was performed using 2D-DIGE. The protein content and number of protein spots in raw sample was higher when compared to the cooked samples. Qualitative analysis revealed that 103 (boiled sample) and 110 (microwaved sample) protein spots were up regulated whereas 120 (boiled sample) and 107 (microwaved sample) protein spots were down regulated. Ten protein spots with the highest significant fold change in the cooked samples were involved in carbohydrate/energy metabolisms and stress responses. Small heat shock proteins, superoxide dismutase, quinone oxidoreductase, UDP-glucose pyrophosphorylase and phosphoglycerate kinase play a role in heat-stress-mediated protection of bitter gourd. This study suggests that appropriate heat treatment (cooking methods) can lead to induction of selected proteins in bitter gourd. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

PubMed

Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

DOE PAGES

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui; ...

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

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

PubMed Central

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

2008-01-01

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

Quantitative proteomic analysis of human testis reveals system-wide molecular and cellular pathways associated with non-obstructive azoospermia.

PubMed

Alikhani, Mehdi; Mirzaei, Mehdi; Sabbaghian, Marjan; Parsamatin, Pouria; Karamzadeh, Razieh; Adib, Samane; Sodeifi, Niloofar; Gilani, Mohammad Ali Sadighi; Zabet-Moghaddam, Masoud; Parker, Lindsay; Wu, Yunqi; Gupta, Vivek; Haynes, Paul A; Gourabi, Hamid; Baharvand, Hossein; Salekdeh, Ghasem Hosseini

2017-06-06

Male infertility accounts for half of the infertility problems experienced by couples. Azoospermia, having no measurable level of sperm in seminal fluid, is one of the known conditions resulting in male infertility. In order to elucidate the complex molecular mechanisms causing male azoospermia, label-free quantitative shotgun proteomics was carried out on testicular tissue specimens from patients with obstructive azoospermia and non-obstructive azoospermia, including maturation arrest (MA) and Sertoli cell only syndrome (SCOS). The abundance of 520 proteins was significantly changed across three groups of samples. We were able to identify several functional biological pathways enriched in azoospermia samples and confirm selected differentially abundant proteins, using multiple histological methods. The results revealed that cell cycle and proteolysis, and RNA splicing were the most significant biological processes impaired by the substantial suppression of proteins related to the aforementioned categories in SCOS tissues. In the MA patient testes, generation of precursor metabolites and energy as well as oxidation-reduction were the most significantly altered processes. Novel candidate proteins identified in this study include key transcription factors, many of which have not previously been shown to be associated with azoospermia. Our findings can provide substantial insights into the molecular regulation of spermatogenesis and human reproduction. The obtained data showed a drastic suppression of proteins involved in spliceosome, cell cycle and proteasome proteins, as well as energy and metabolic production in Sertoli cell only syndrome testis tissue, and to a lesser extent in maturation arrest samples. Moreover, we identified new transcription factors that are highly down-regulated in SCOS and MA patients, thus helping to understand the molecular complexity of spermatogenesis in male infertility. Our findings provide novel candidate protein targets associated with SCOS or MA azoospermia. Copyright © 2017 Elsevier B.V. All rights reserved.

Chemical-Biological Properties of Zinc Sensors TSQ and Zinquin: Formation of Sensor-Zn-Protein Adducts versus Zn(Sensor)2 Complexes.

PubMed

Nowakowski, Andrew B; Meeusen, Jeffrey W; Menden, Heather; Tomasiewicz, Henry; Petering, David H

2015-12-21

Fluorescent zinc sensors are the most commonly used tool to study the intracellular mobile zinc status within cellular systems. Previously, we have shown that the quinoline-based sensors Zinquin and 6-methoxy-8-p-toluenesulfonamido-quinoline (TSQ) predominantly form ternary adducts with members of the Zn-proteome. Here, the chemistries of these sensors are further characterized, including how Zn(sensor)2 complexes may react in an intracellular environment. We demonstrate that these sensors are typically used in higher concentrations than needed to obtain maximum signal. Exposing cells to either Zn(Zinquin)2 or Zn(TSQ)2 resulted in efficient cellular uptake and the formation of sensor-Zn-protein adducts as evidenced by both a fluorescence spectral shift toward that of ternary adducts and the localization of the fluorescence signal within the proteome after gel filtration of cellular lysates. Likewise, reacting Zn(sensor)2 with the Zn-proteome from LLC-PK1 cells resulted in the formation of sensor-Zn-protein ternary adducts that could be inhibited by first saturating the Zn- proteome with excess sensor. Further, a native SDS-PAGE analysis of the Zn-proteome reacted with either the sensor or the Zn(sensor)2 complex revealed that both reactions result in the formation of a similar set of sensor-Zn-protein fluorescent products. The results of this experiment also demonstrated that TSQ and Zinquin react with different members of the Zn-proteome. Reactions with the model apo-Zn-protein bovine serum albumin showed that both Zn(TSQ)2 and Zn(Zinquin)2 reacted to form ternary adducts with its apo-Zn-binding site. Moreover, incubating Zn(sensor)2 complexes with non-zinc binding proteins failed to elicit a spectral shift in the fluorescence spectrum, supporting the premise that blue-shifted emission spectra are due to sensor-Zn-protein ternary adducts. It was concluded that Zn(sensors)2 species do not play a significant role in the overall reaction between these sensors and intact cells. In turn, this study further supports the formation of sensor-Zn-protein adducts as the principal observed fluorescent product during experiments employing these two sensors.

In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion.

PubMed

Beer, Lynn A; Ky, Bonnie; Barnhart, Kurt T; Speicher, David W

2017-01-01

Identification of cancer and other disease biomarkers in human plasma has been exceptionally challenging due to the complex nature of plasma and the presence of a moderate number of high- and medium-abundance proteins which mask low-abundance proteins of interest. As a result, immunoaffinity depletion formats combining multiple antibodies to target the most abundant plasma proteins have become the first stage in most plasma proteome discovery schemes. This protocol describes the use of tandem IgY 14 and SuperMix immunoaffinity depletion to reproducibly remove >99% of total plasma protein. This greatly increases the depth of analysis of human plasma proteomes. Depleted plasma samples can then be analyzed in a single high-resolution LC-MS/MS run on a Q Exactive Plus mass spectrometer, followed by label-free quantitation. If greater depth of analysis is desired, the depleted plasma can be further fractionated by separating the sample for a short distance on a 1D SDS gel and cutting the gel into uniform slices prior to trypsin digestion. Alternatively, the depleted plasma can be reduced, alkylated, and digested with trypsin followed by high-pH reversed-phase HPLC separation.

Inactivation of West Nile Virus in Serum with Heat, Ionic Detergent, and Reducing Agent for Proteomic Applications (Open Access Publisher’s Version)

DTIC Science & Technology

2017-05-19

LightCycler® 96 desktop software. Positive and negative samples were identified using the “ Qualitative Detection” analysis function using the default...Institute of Infectious Diseases, Fort Detrick, MD 21702, United States A R T I C L E I N F O Keywords: West Nile virus Virus inactivation Sample buffer... samples using a commercially available SDS- PAGE sample buffer for proteomic studies. Using this method, we demonstrate its utility by identification

The Seminal fluid proteome of the polyandrous Red junglefowl offers insights into the molecular basis of fertility, reproductive ageing and domestication

PubMed Central

Borziak, Kirill; Álvarez-Fernández, Aitor; L. Karr, Timothy; Pizzari, Tommaso; Dorus, Steve

2016-01-01

Seminal fluid proteins (SFPs) are emerging as fundamental contributors to sexual selection given their role in post-mating reproductive events, particularly in polyandrous species where the ejaculates of different males compete for fertilisation. SFP identification however remains taxonomically limited and little is known about avian SFPs, despite extensive work on sexual selection in birds. We characterize the SF proteome of the polyandrous Red junglefowl, Gallus gallus, the wild species that gave rise to the domestic chicken. We identify 1,141 SFPs, including proteins involved in immunity and antimicrobial defences, sperm maturation, and fertilisation, revealing a functionally complex SF proteome. This includes a predominant contribution of blood plasma proteins that is conserved with human SF. By comparing the proteome of young and old males with fast or slow sperm velocity in a balanced design, we identify proteins associated with ageing and sperm velocity, and show that old males that retain high sperm velocity have distinct proteome characteristics. SFP comparisons with domestic chickens revealed both qualitative and quantitative differences likely associated with domestication and artificial selection. Collectively, these results shed light onto the functional complexity of avian SF, and provide a platform for molecular studies of fertility, reproductive ageing, and domestication. PMID:27804984

The Seminal fluid proteome of the polyandrous Red junglefowl offers insights into the molecular basis of fertility, reproductive ageing and domestication.

PubMed

Borziak, Kirill; Álvarez-Fernández, Aitor; L Karr, Timothy; Pizzari, Tommaso; Dorus, Steve

2016-11-02

Seminal fluid proteins (SFPs) are emerging as fundamental contributors to sexual selection given their role in post-mating reproductive events, particularly in polyandrous species where the ejaculates of different males compete for fertilisation. SFP identification however remains taxonomically limited and little is known about avian SFPs, despite extensive work on sexual selection in birds. We characterize the SF proteome of the polyandrous Red junglefowl, Gallus gallus, the wild species that gave rise to the domestic chicken. We identify 1,141 SFPs, including proteins involved in immunity and antimicrobial defences, sperm maturation, and fertilisation, revealing a functionally complex SF proteome. This includes a predominant contribution of blood plasma proteins that is conserved with human SF. By comparing the proteome of young and old males with fast or slow sperm velocity in a balanced design, we identify proteins associated with ageing and sperm velocity, and show that old males that retain high sperm velocity have distinct proteome characteristics. SFP comparisons with domestic chickens revealed both qualitative and quantitative differences likely associated with domestication and artificial selection. Collectively, these results shed light onto the functional complexity of avian SF, and provide a platform for molecular studies of fertility, reproductive ageing, and domestication.

Hydroxytyrosol and its complex forms (secoiridoids) modulate aorta and heart proteome in healthy rats: Potential cardio-protective effects.

PubMed

Catalán, Úrsula; Rubió, Laura; López de Las Hazas, Maria-Carmen; Herrero, Pol; Nadal, Pedro; Canela, Núria; Pedret, Anna; Motilva, Maria-José; Solà, Rosa

2016-10-01

Hydroxytyrosol (HT) is the major phenolic compound in virgin olive oil (VOO) in both free and complex forms (secoiridoids; SEC). Proteomics of cardiovascular tissues such as aorta or heart represents a promising tool to uncover the mechanisms of action of phenolic compounds in healthy animals. Twelve female Wistar rats were separated into three groups: a standard diet and two diets supplemented in phenolic compounds (HT and SEC) adjusted to 5 mg/kg/day during 21 days. Proteomic analyses of aorta and heart tissues were performed by nano-LC and MS. Ingenuity Pathway Analysis was used to generate interaction networks. HT or SEC modulated aorta and heart proteome compared to the standard diet. The top-scored networks were related to Cardiovascular System. HT and SEC downregulated proteins related to proliferation and migration of endothelial cells and occlusion of blood vessels in aorta and proteins related to heart failure in heart tissue. SEC showed higher fold change values compared to HT, attributed to higher concentration of HT detected in heart tissue. Changes at proteomic level in cardiovascular tissues may partially account for the underlying mechanisms of VOO phenols cardiovascular protection being the SEC effects higher than free HT. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

Capillary electrophoresis interfaced with a mass spectrometer (CE-MS): technical considerations and applicability for biomarker studies in animals.

PubMed

Albalat, Amaya; Husi, Holger; Siwy, Justyna; Nally, Jarlath E; McLauglin, Mark; Eckersall, Peter D; Mullen, William

2014-02-01

Proteomics is a growing field that has the potential to be applied to many biology-related disciplines. However, the study of the proteome has proven to be very challenging due to its high level of complexity when compared to genome and transcriptome data. In order to analyse this level of complexity, high resolution separation of peptides/proteins are needed together with high resolution analysers. Currently, liquid chromatography and capillary electrophoresis (CE) are the two most widely used separation techniques that can be coupled on-line with a mass spectrometer (MS). In CE, proteins/ peptides are separated according to their size, charge and shape leading to high resolving power. Although further progress in the area of sensitivity, throughput and proteome coverage are expected, MS-based proteomics have developed to a level at which they are habitually applied to study a wide range of biological questions. The aim of this review is to present CE-MS as a proteomic analytical platform for biomarker research that could be used in farm animal and veterinary studies. This is a MS-analytical platform that has been widely used for biomarker research in the biomedical field but its application in animal proteomic studies is relatively novel. The review will focus on introducing the CE-MS platform and the primary considerations for its application to biomarker research. Furthermore, current applications but more importantly potential application in the field of farm animals and veterinary science will be presented and discussed.

Top-down Proteomics in Health and Disease: Challenges and Opportunities

PubMed Central

Gregorich, Zachery R.; Ge, Ying

2014-01-01

Proteomics is essential for deciphering how molecules interact as a system and for understanding the functions of cellular systems in human disease; however, the unique characteristics of the human proteome, which include a high dynamic range of protein expression and extreme complexity due to a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses challenging. An emerging “top-down” mass spectrometry (MS)-based proteomics approach, which provides a “bird’s eye” view of all proteoforms, has unique advantages for the assessment of PTMs and sequence variations. Recently, a number of studies have showcased the potential of top-down proteomics for unraveling of disease mechanisms and discovery of new biomarkers. Nevertheless, the top-down approach still faces significant challenges in terms of protein solubility, separation, and the detection of large intact proteins, as well as the under-developed data analysis tools. Consequently, new technological developments are urgently needed to advance the field of top-down proteomics. Herein, we intend to provide an overview of the recent applications of top-down proteomics in biomedical research. Moreover, we will outline the challenges and opportunities facing top-down proteomics strategies aimed at understanding and diagnosing human diseases. PMID:24723472

Birth of plant proteomics in India: a new horizon.

PubMed

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

2015-09-08

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

Proteomics for understanding miRNA biology

PubMed Central

Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh

2013-01-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164

The role of targeted chemical proteomics in pharmacology

PubMed Central

Sutton, Chris W

2012-01-01

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351

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

PubMed Central

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

2016-01-01

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

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

DOE PAGES

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

2016-11-18

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

Ionotropic AMPA-type glutamate and metabotropic GABAB receptors: determining cellular physiology by proteomes.

PubMed

Bettler, Bernhard; Fakler, Bernd

2017-08-01

Ionotropic AMPA-type glutamate receptors and G-protein-coupled metabotropic GABA B receptors are key elements of neurotransmission whose cellular functions are determined by their protein constituents. Over the past couple of years unbiased proteomic approaches identified comprehensive sets of protein building blocks of these two types of neurotransmitter receptors in the brain (termed receptor proteomes). This provided the opportunity to match receptor proteomes with receptor physiology and to study the structural organization, regulation and function of native receptor complexes in an unprecedented manner. In this review we discuss the principles of receptor architecture and regulation emerging from the functional characterization of the proteomes of AMPA and GABA B receptors. We also highlight progress in unraveling the role of unexpected protein components for receptor physiology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Advanced proteomic liquid chromatography

PubMed Central

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-01-01

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput. PMID:22840822

Proteomics of the Human Placenta: Promises and Realities

PubMed Central

Robinson, J.M.; Ackerman, W.E.; Kniss, D.A.; Takizawa, T.; Vandré, D.D.

2015-01-01

Proteomics is an area of study that sets as its ultimate goal the global analysis of all of the proteins expressed in a biological system of interest. However, technical limitations currently hamper proteome-wide analyses of complex systems. In a more practical sense, a desired outcome of proteomics research is the translation of large protein data sets into formats that provide meaningful information regarding clinical conditions (e.g., biomarkers to serve as diagnostic and/or prognostic indicators of disease). Herein, we discuss placental proteomics by describing existing studies, pointing out their strengths and weaknesses. In so doing, we strive to inform investigators interested in this area of research about the current gap between hyperbolic promises and realities. Additionally, we discuss the utility of proteomics in discovery-based research, particularly as regards the capacity to unearth novel insights into placental biology. Importantly, when considering under studied systems such as the human placenta and diseases associated with abnormalities in placental function, proteomics can serve as a robust ‘shortcut’ to obtaining information unlikely to be garnered using traditional approaches. PMID:18222537

The online Tabloid Proteome: an annotated database of protein associations

PubMed Central

Turan, Demet; Tavernier, Jan

2018-01-01

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

Misclassification Errors in Unsupervised Classification Methods. Comparison Based on the Simulation of Targeted Proteomics Data

PubMed Central

Andreev, Victor P; Gillespie, Brenda W; Helfand, Brian T; Merion, Robert M

2016-01-01

Unsupervised classification methods are gaining acceptance in omics studies of complex common diseases, which are often vaguely defined and are likely the collections of disease subtypes. Unsupervised classification based on the molecular signatures identified in omics studies have the potential to reflect molecular mechanisms of the subtypes of the disease and to lead to more targeted and successful interventions for the identified subtypes. Multiple classification algorithms exist but none is ideal for all types of data. Importantly, there are no established methods to estimate sample size in unsupervised classification (unlike power analysis in hypothesis testing). Therefore, we developed a simulation approach allowing comparison of misclassification errors and estimating the required sample size for a given effect size, number, and correlation matrix of the differentially abundant proteins in targeted proteomics studies. All the experiments were performed in silico. The simulated data imitated the expected one from the study of the plasma of patients with lower urinary tract dysfunction with the aptamer proteomics assay Somascan (SomaLogic Inc, Boulder, CO), which targeted 1129 proteins, including 330 involved in inflammation, 180 in stress response, 80 in aging, etc. Three popular clustering methods (hierarchical, k-means, and k-medoids) were compared. K-means clustering performed much better for the simulated data than the other two methods and enabled classification with misclassification error below 5% in the simulated cohort of 100 patients based on the molecular signatures of 40 differentially abundant proteins (effect size 1.5) from among the 1129-protein panel. PMID:27524871

Comparative Proteomic Analysis of Hymenolepis diminuta Cysticercoid and Adult Stages

PubMed Central

Sulima, Anna; Savijoki, Kirsi; Bień, Justyna; Näreaho, Anu; Sałamatin, Rusłan; Conn, David Bruce; Młocicki, Daniel

2018-01-01

Cestodiases are common parasitic diseases of animals and humans. As cestodes have complex lifecycles, hexacanth larvae, metacestodes (including cysticercoids), and adults produce proteins allowing them to establish invasion and to survive in the hostile environment of the host. Hymenolepis diminuta is the most commonly used model cestode in experimental parasitology. The aims of the present study were to perform a comparative proteomic analysis of two consecutive developmental stages of H. diminuta (cysticercoid and adult) and to distinguish proteins which might be characteristic for each of the stages from those shared by both stages. Somatic proteins of H. diminuta were isolated from 6-week-old cysticercoids and adult tapeworms. Cysticercoids were obtained from experimentally infected beetles, Tenebrio molitor, whereas adult worms were collected from experimentally infected rats. Proteins were separated by GeLC-MS/MS (one dimensional gel electrophoresis coupled with liquid chromatography and tandem mass spectrometry). Additionally protein samples were digested in-liquid and identified by LC-MS/MS. The identified proteins were classified according to molecular function, cellular components and biological processes. Our study showed a number of differences and similarities in the protein profiles of cysticercoids and adults; 233 cysticercoid and 182 adult proteins were identified. From these proteins, 131 were present only in the cysticercoid and 80 only in the adult stage samples. Both developmental stages shared 102 proteins; among which six represented immunomodulators and one is a potential drug target. In-liquid digestion and LC-MS/MS complemented and confirmed some of the GeLC-MS/MS identifications. Possible roles and functions of proteins identified with both proteomic approaches are discussed. PMID:29379475

Cardiovascular Redox and Ox Stress Proteomics

PubMed Central

Kumar, Vikas; Calamaras, Timothy Dean; Haeussler, Dagmar; Colucci, Wilson Steven; Cohen, Richard Alan; McComb, Mark Errol; Pimentel, David

2012-01-01

Abstract Significance: Oxidative post-translational modifications (OPTMs) have been demonstrated as contributing to cardiovascular physiology and pathophysiology. These modifications have been identified using antibodies as well as advanced proteomic methods, and the functional importance of each is beginning to be understood using transgenic and gene deletion animal models. Given that OPTMs are involved in cardiovascular pathology, the use of these modifications as biomarkers and predictors of disease has significant therapeutic potential. Adequate understanding of the chemistry of the OPTMs is necessary to determine what may occur in vivo and which modifications would best serve as biomarkers. Recent Advances: By using mass spectrometry, advanced labeling techniques, and antibody identification, OPTMs have become accessible to a larger proportion of the scientific community. Advancements in instrumentation, database search algorithms, and processing speed have allowed MS to fully expand on the proteome of OPTMs. In addition, the role of enzymatically reversible OPTMs has been further clarified in preclinical models. Critical Issues: The identification of OPTMs suffers from limitations in analytic detection based on the methodology, instrumentation, sample complexity, and bioinformatics. Currently, each type of OPTM requires a specific strategy for identification, and generalized approaches result in an incomplete assessment. Future Directions: Novel types of highly sensitive MS instrumentation that allow for improved separation and detection of modified proteins and peptides have been crucial in the discovery of OPTMs and biomarkers. To further advance the identification of relevant OPTMs in advanced search algorithms, standardized methods for sample processing and depository of MS data will be required. Antioxid. Redox Signal. 17, 1528–1559. PMID:22607061

Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment.

PubMed

Welker, F

2018-02-20

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized between moderately divergent proteomes, as indicated by almost complete recovery of informative positions in the search against the chimpanzee proteome (≈90%, 6-8 Ma). This provides a bioinformatic background to future phylogenetic and proteomic analysis of ancient hominin proteomes, including the future description of novel hominin amino acid sequences, but also has negative implications for the study of fast-evolving proteins in hominins, non-hominin animals, and ancient bacterial proteins in evolutionary contexts.

Metabolites associated with adaptation of microorganisms to an acidophilic, metal-rich environment identified by stable-isotope-enabled metabolomics.

PubMed

Mosier, Annika C; Justice, Nicholas B; Bowen, Benjamin P; Baran, Richard; Thomas, Brian C; Northen, Trent R; Banfield, Jillian F

2013-03-12

Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities. Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.

Nanospray FAIMS Fractionation Provides Significant Increases in Proteome Coverage of Unfractionated Complex Protein Digests*

PubMed Central

Swearingen, Kristian E.; Hoopmann, Michael R.; Johnson, Richard S.; Saleem, Ramsey A.; Aitchison, John D.; Moritz, Robert L.

2012-01-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that can be used to reduce sample complexity and increase dynamic range in tandem mass spectrometry experiments. FAIMS fractionates ions in the gas-phase according to characteristic differences in mobilities in electric fields of different strengths. Undesired ion species such as solvated clusters and singly charged chemical background ions can be prevented from reaching the mass analyzer, thus decreasing chemical noise. To date, there has been limited success using the commercially available Thermo Fisher FAIMS device with both standard ESI and nanoLC-MS. We have modified a Thermo Fisher electrospray source to accommodate a fused silica pulled tip capillary column for nanospray ionization, which will enable standard laboratories access to FAIMS technology. Our modified source allows easily obtainable stable spray at flow rates of 300 nL/min when coupled with FAIMS. The modified electrospray source allows the use of sheath gas, which provides a fivefold increase in signal obtained when nanoLC is coupled to FAIMS. In this work, nanoLC-FAIMS-MS and nanoLC-MS were compared by analyzing a tryptic digest of a 1:1 mixture of SILAC-labeled haploid and diploid yeast to demonstrate the performance of nanoLC-FAIMS-MS, at different compensation voltages, for post-column fractionation of complex protein digests. The effective dynamic range more than doubled when FAIMS was used. In total, 10,377 unique stripped peptides and 1649 unique proteins with SILAC ratios were identified from the combined nanoLC-FAIMS-MS experiments, compared with 6908 unique stripped peptides and 1003 unique proteins with SILAC ratios identified from the combined nanoLC-MS experiments. This work demonstrates how a commercially available FAIMS device can be combined with nanoLC to improve proteome coverage in shotgun and targeted type proteomics experiments. PMID:22186714

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics*

PubMed Central

Cai, Wenxuan; Guner, Huseyin; Gregorich, Zachery R.; Chen, Albert J.; Ayaz-Guner, Serife; Peng, Ying; Valeja, Santosh G.; Liu, Xiaowen; Ge, Ying

2016-01-01

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics. PMID:26598644

How many proteins can be identified in a 2DE gel spot within an analysis of a complex human cancer tissue proteome?

PubMed

Zhan, Xianquan; Yang, Haiyan; Peng, Fang; Li, Jianglin; Mu, Yun; Long, Ying; Cheng, Tingting; Huang, Yuda; Li, Zhao; Lu, Miaolong; Li, Na; Li, Maoyu; Liu, Jianping; Jungblut, Peter R

2018-04-01

Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Proteomic Approach for the Identification of Up-Regulated Proteins Involved in the Metabolic Process of the Leiomyoma.

PubMed

Ura, Blendi; Scrimin, Federica; Arrigoni, Giorgio; Franchin, Cinzia; Monasta, Lorenzo; Ricci, Giuseppe

2016-04-09

Uterine leiomyoma is the most common benign smooth muscle cell tumor of the uterus. Proteomics is a powerful tool for the analysis of complex mixtures of proteins. In our study, we focused on proteins that were upregulated in the leiomyoma compared to the myometrium. Paired samples of eight leiomyomas and adjacent myometrium were obtained and submitted to two-dimensional gel electrophoresis (2-DE) and mass spectrometry for protein identification and to Western blotting for 2-DE data validation. The comparison between the patterns revealed 24 significantly upregulated (p < 0.05) protein spots, 12 of which were found to be associated with the metabolic processes of the leiomyoma and not with the normal myometrium. The overexpression of seven proteins involved in the metabolic processes of the leiomyoma was further validated by Western blotting and 2D Western blotting. Four of these proteins have never been associated with the leiomyoma before. The 2-DE approach coupled with mass spectrometry, which is among the methods of choice for comparative proteomic studies, identified a number of proteins overexpressed in the leiomyoma and involved in several biological processes, including metabolic processes. A better understanding of the mechanism underlying the overexpression of these proteins may be important for therapeutic purposes.

A Proteomic Approach for the Identification of Up-Regulated Proteins Involved in the Metabolic Process of the Leiomyoma

PubMed Central

Ura, Blendi; Scrimin, Federica; Arrigoni, Giorgio; Franchin, Cinzia; Monasta, Lorenzo; Ricci, Giuseppe

2016-01-01

Uterine leiomyoma is the most common benign smooth muscle cell tumor of the uterus. Proteomics is a powerful tool for the analysis of complex mixtures of proteins. In our study, we focused on proteins that were upregulated in the leiomyoma compared to the myometrium. Paired samples of eight leiomyomas and adjacent myometrium were obtained and submitted to two-dimensional gel electrophoresis (2-DE) and mass spectrometry for protein identification and to Western blotting for 2-DE data validation. The comparison between the patterns revealed 24 significantly upregulated (p < 0.05) protein spots, 12 of which were found to be associated with the metabolic processes of the leiomyoma and not with the normal myometrium. The overexpression of seven proteins involved in the metabolic processes of the leiomyoma was further validated by Western blotting and 2D Western blotting. Four of these proteins have never been associated with the leiomyoma before. The 2-DE approach coupled with mass spectrometry, which is among the methods of choice for comparative proteomic studies, identified a number of proteins overexpressed in the leiomyoma and involved in several biological processes, including metabolic processes. A better understanding of the mechanism underlying the overexpression of these proteins may be important for therapeutic purposes. PMID:27070597

Unparalleled sample treatment throughput for proteomics workflows relying on ultrasonic energy.

PubMed

Jorge, Susana; Araújo, J E; Pimentel-Santos, F M; Branco, Jaime C; Santos, Hugo M; Lodeiro, Carlos; Capelo, J L

2018-02-01

We report on the new microplate horn ultrasonic device as a powerful tool to speed proteomics workflows with unparalleled throughput. 96 complex proteomes were digested at the same time in 4min. Variables such as ultrasonication time, ultrasonication amplitude, and protein to enzyme ratio were optimized. The "classic" method relying on overnight protein digestion (12h) and the sonoreactor-based method were also employed for comparative purposes. We found the protein digestion efficiency homogeneously distributed in the entire microplate horn surface using the following conditions: 4min sonication time and 25% amplitude. Using this approach, patients with lymphoma and myeloma were classified using principal component analysis and a 2D gel-mass spectrometry based approach. Furthermore, we demonstrate the excellent performance by using MALDI-mass spectrometry based profiling as a fast way to classify patients with rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Finally, the speed and simplicity of this method were demonstrated by clustering 90 patients with knee osteoarthritis disease (30), with a prosthesis (30, control group) and healthy individuals (30) with no history of joint disease. Overall, the new approach allows profiling a disease in just one week while allows to match the minimalism rules as outlined by Halls. Copyright © 2017 Elsevier B.V. All rights reserved.

Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome

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

Wang, Hong; Yang, Yanling; Li, Yuxin

2015-02-06

Development of high resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse phase column (100 μm x 150 cm) coupled with Q Exactive MS. The column was capable of achieving a peak capacity of approximately 700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was about 6 micrograms of peptides, although the column allowed loading as many as 20 micrograms. Gas phasemore » fractionation of peptide ions further increased the number of peptide identification by ~10%. Moreover, the combination of basic pH LC pre-fractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a postmortem brain sample of Alzheimer’s disease. As deep RNA sequencing of the same specimen suggested that ~16,000 genes were expressed, current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.« less

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

PubMed

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

2017-02-10

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

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

Vascular Sap Proteomics: Providing Insight into Long-Distance Signaling during Stress

PubMed Central

Carella, Philip; Wilson, Daniel C.; Kempthorne, Christine J.; Cameron, Robin K.

2016-01-01

The plant vascular system, composed of the xylem and phloem, is important for the transport of water, mineral nutrients, and photosynthate throughout the plant body. The vasculature is also the primary means by which developmental and stress signals move from one organ to another. Due to practical and technological limitations, proteomics analysis of xylem and phloem sap has been understudied in comparison to accessible sample types such as leaves and roots. However, recent advances in sample collection techniques and mass spectrometry technology are making it possible to comprehensively analyze vascular sap proteomes. In this mini-review, we discuss the emerging field of vascular sap proteomics, with a focus on recent comparative studies to identify vascular proteins that may play roles in long-distance signaling and other processes during stress responses in plants. PMID:27242852

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

PubMed

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

2012-06-06

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

A comparative proteomic characterization and nutritional assessment of naturally- and artificially-cultivated Cordyceps sinensis.

PubMed

Zhang, Xu; Liu, Qun; Zhou, Wei; Li, Ping; Alolga, Raphael N; Qi, Lian-Wen; Yin, Xiaojian

2018-06-15

Cordyceps sinensis has gained increasing attention due to its nutritional and medicinal properties. Herein, we employed label-free quantitative mass spectrometry to explore the proteome differences between naturally- and artificially-cultivated C. sinensis. A total of 22,829 peptides with confidence ≥95%, corresponding to 2541 protein groups were identified from the caterpillar bodies/stromata of 12 naturally- and artificially-cultivated samples of C. sinensis. Among them, 165 proteins showed significant differences between the samples of natural and artificial cultivation. These proteins were mainly involved in energy production/conversion, amino acid transport/metabolism, and transcription regulation. The proteomic results were confirmed by the identification of 4 significantly changed metabolites, thus, lysine, threonine, serine, and arginine via untargeted metabolomics. The change tendencies of these metabolites were partly in accordance with changes in abundance of the proteins, which was upstream of their synthetic pathways. In addition, the nutritional value in terms of the levels of nucleosides, nucleotides, and adenosine between the artificially- and naturally-cultivated samples was virtually same. These proteomic data will be useful for understanding the medicinal value of C. sinensis and serve as reference for its artificial cultivation. C. sinensis is a precious and valued medicinal product, the current basic proteome dataset would provide useful information to understand its development/infection processes as well as help to artificially cultivate it. This work would also provide basic proteome profile for further study of C. sinensis. Copyright © 2018. Published by Elsevier B.V.

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

Comparative Proteomic Analysis of Whole-Gut Lavage Fluid and Pancreatic Juice Reveals a Less Invasive Method of Sampling Pancreatic Secretions

PubMed Central

Rocker, Jana M; Tan, Marcus C; Thompson, Lee W; Contreras, Carlo M; DiPalma, Jack A; Pannell, Lewis K

2016-01-01

OBJECTIVES: There are currently no reliable, non-invasive screening tests for pancreatic ductal adenocarcinoma. The fluid secreted from the pancreatic ductal system (“pancreatic juice”) has been well-studied as a potential source of cancer biomarkers. However, it is invasive to collect. We recently observed that the proteomic profile of intestinal effluent from the bowel in response to administration of an oral bowel preparation solution (also known as whole-gut lavage fluid, WGLF) contains large amounts of pancreas-derived proteins. We therefore hypothesized that the proteomic profile is similar to that of pancreatic juice. In this study, we compared the proteomic profiles of 77 patients undergoing routine colonoscopy with the profiles of 19 samples of pure pancreatic juice collected during surgery. METHODS: WGLF was collected from patients undergoing routine colonoscopy, and pancreatic juice was collected from patients undergoing pancreatic surgery. Protein was isolated from both samples using an optimized method and analyzed by LC-MS/MS. Identified proteins were compared between samples and groups to determine similarity of the two fluids. We then compared our results with literature reports of pancreatic juice-based studies to determine similarity. RESULTS: We found 104 proteins in our pancreatic juice samples, of which 90% were also found in our WGLF samples. The majority (67%) of the total proteins found in the WGLF were common to pancreatic juice, with intestine-specific proteins making up a smaller proportion. CONCLUSIONS: WGLF and pancreatic juice appear to have similar proteomic profiles. This supports the notion that WGLF is a non-invasive, surrogate bio-fluid for pancreatic juice. Further studies are required to further elucidate its role in the diagnosis of pancreatic cancer. PMID:27228405

Mining the human urine proteome for monitoring renal transplant injury

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

Sigdel, Tara K.; Gao, Yuqian; He, Jintang

The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used inmore » the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.« less

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.

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.

Mitochondrial proteomic profile of complex IV deficiency fibroblasts: rearrangement of oxidative phosphorylation complex/supercomplex and other metabolic pathways.

PubMed

Salvador-Severo, Karina; Gómez-Caudillo, Leopoldo; Quezada, Héctor; García-Trejo, José de Jesús; Cárdenas-Conejo, Alan; Vázquez-Memije, Martha Elisa; Minauro-Sanmiguel, Fernando

Mitochondriopathies are multisystem diseases affecting the oxidative phosphorylation (OXPHOS) system. Skin fibroblasts are a good model for the study of these diseases. Fibroblasts with a complex IV mitochondriopathy were used to determine the molecular mechanism and the main affected functions in this disease. Skin fibroblast were grown to assure disease phenotype. Mitochondria were isolated from these cells and their proteome extracted for protein identification. Identified proteins were validated with the MitoMiner database. Disease phenotype was corroborated on skin fibroblasts, which presented a complex IV defect. The mitochondrial proteome of these cells showed that the most affected proteins belonged to the OXPHOS system, mainly to the complexes that form supercomplexes or respirosomes (I, III, IV, and V). Defects in complex IV seemed to be due to assembly issues, which might prevent supercomplexes formation and efficient substrate channeling. It was also found that this mitochondriopathy affects other processes that are related to DNA genetic information flow (replication, transcription, and translation) as well as beta oxidation and tricarboxylic acid cycle. These data, as a whole, could be used for the better stratification of these diseases, as well as to optimize management and treatment options. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

The Escherichia coli Proteome: Past, Present, and Future Prospects†

PubMed Central

Han, Mee-Jung; Lee, Sang Yup

2006-01-01

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects. PMID:16760308

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

PubMed

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

2018-04-17

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

A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins

PubMed Central

Raiszadeh, Michelle M.; Ross, Mark M.; Russo, Paul S.; Schaepper, Mary Ann H.; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D.; Kabbani, Nadine; Petricoin, Emanuel F.; Liotta, Lance A.; Kirsch, Wolff M.

2012-01-01

Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet*

PubMed Central

Keller, Andrew; Bader, Samuel L.; Shteynberg, David; Hood, Leroy; Moritz, Robert L.

2015-01-01

Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users. PMID:25713123

Targeted Proteomics Approach for Precision Plant Breeding.

PubMed

Chawade, Aakash; Alexandersson, Erik; Bengtsson, Therese; Andreasson, Erik; Levander, Fredrik

2016-02-05

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.

Quantitative Proteomics Analysis of Streptomyces coelicolor Development Demonstrates That Onset of Secondary Metabolism Coincides with Hypha Differentiation*

PubMed Central

Manteca, Angel; Sanchez, Jesus; Jung, Hye R.; Schwämmle, Veit; Jensen, Ole N.

2010-01-01

Streptomyces species produce many clinically important secondary metabolites, including antibiotics and antitumorals. They have a complex developmental cycle, including programmed cell death phenomena, that makes this bacterium a multicellular prokaryotic model. There are two differentiated mycelial stages: an early compartmentalized vegetative mycelium (first mycelium) and a multinucleated reproductive mycelium (second mycelium) arising after programmed cell death processes. In the present study, we made a detailed proteomics analysis of the distinct developmental stages of solid confluent Streptomyces coelicolor cultures using iTRAQ (isobaric tags for relative and absolute quantitation) labeling and LC-MS/MS. A new experimental approach was developed to obtain homogeneous samples at each developmental stage (temporal protein analysis) and also to obtain membrane and cytosolic protein fractions (spatial protein analysis). A total of 345 proteins were quantified in two biological replicates. Comparative bioinformatics analyses revealed the switch from primary to secondary metabolism between the initial compartmentalized mycelium and the multinucleated hyphae. PMID:20224110

Joining Forces: Integrating Proteomics and Cross-linking with the Mass Spectrometry of Intact Complexes*

PubMed Central

Stengel, Florian; Aebersold, Ruedi; Robinson, Carol V.

2012-01-01

Protein assemblies are critical for cellular function and understanding their physical organization is the key aim of structural biology. However, applying conventional structural biology approaches is challenging for transient, dynamic, or polydisperse assemblies. There is therefore a growing demand for hybrid technologies that are able to complement classical structural biology methods and thereby broaden our arsenal for the study of these important complexes. Exciting new developments in the field of mass spectrometry and proteomics have added a new dimension to the study of protein-protein interactions and protein complex architecture. In this review, we focus on how complementary mass spectrometry-based techniques can greatly facilitate structural understanding of protein assemblies. PMID:22180098

Mass spectrometry and animal science: protein identification strategies and particularities of farm animal species.

PubMed

Soares, Renata; Franco, Catarina; Pires, Elisabete; Ventosa, Miguel; Palhinhas, Rui; Koci, Kamila; Martinho de Almeida, André; Varela Coelho, Ana

2012-07-19

Proteomic approaches are gaining increasing importance in the context of all fields of animal and veterinary sciences, including physiology, productive characterization, and disease/parasite tolerance, among others. Proteomic studies mainly aim the proteome characterization of a certain organ, tissue, cell type or organism, either in a specific condition or comparing protein differential expression within two or more selected situations. Due to the high complexity of samples, usually total protein extracts, proteomics relies heavily on separation procedures, being 2D-electrophoresis and HPLC the most common, as well as on protein identification using mass spectrometry (MS) based methodologies. Despite the increasing importance of MS in the context of animal and veterinary science studies, the usefulness of such tools is still poorly perceived by the animal science community. This is primarily due to the limited knowledge on mass spectrometry by animal scientists. Additionally, confidence and success in protein identification is hindered by the lack of information in public databases for most of farm animal species and their pathogens, with the exception of cattle (Bos taurus), pig (Sus scrofa) and chicken (Gallus gallus). In this article, we will briefly summarize the main methodologies available for protein identification using mass spectrometry providing a case study of specific applications in the field of animal science. We will also address the difficulties inherent to protein identification using MS, with particular reference to experiments using animal species poorly described in public databases. Additionally, we will suggest strategies to increase the rate of successful identifications when working with farm animal species. Copyright © 2012 Elsevier B.V. All rights reserved.

Time-course human urine proteomics in space-flight simulation experiments.

PubMed

Binder, Hans; Wirth, Henry; Arakelyan, Arsen; Lembcke, Kathrin; Tiys, Evgeny S; Ivanisenko, Vladimir A; Kolchanov, Nikolay A; Kononikhin, Alexey; Popov, Igor; Nikolaev, Evgeny N; Pastushkova, Lyudmila; Larina, Irina M

2014-01-01

Long-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved. We studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals. The protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

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

Qian, Chen; Hettich, Robert L.

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

DOE PAGES

Qian, Chen; Hettich, Robert L.

2017-05-24

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Proteomics of exhaled breath: methodological nuances and pitfalls.

PubMed

Kurova, Viktoria S; Anaev, Eldar C; Kononikhin, Alexey S; Fedorchenko, Kristina Yu; Popov, Igor A; Kalupov, Timothey L; Bratanov, Dmitriy O; Nikolaev, Eugenie N; Varfolomeev, Sergey D

2009-01-01

The analysis of exhaled breath condensate (EBC) can be an alternative to traditional endoscopic sampling of lower respiratory tract secretions. This is a simple non-invasive method of diagnosing respiratory diseases, in particular, respiratory inflammatory processes. Samples were collected with a special device-condenser (ECoScreen, VIASYS Healthcare, Germany), then treated with trypsin according to the proteomics protocol for standard protein mixtures and analyzed by nanoflow high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) with a 7-Tesla Finnigan LTQ-FT mass spectrometer (Thermo Electron, Germany). Mascot software (Matrixscience) was used for screening the database NCBInr for proteins corresponding to the peptide maps that were obtained. EBCs from 17 young healthy non-smoking donors were collected. Different methods for concentrating protein were compared in order to optimize EBC preparations for proteomic analysis. The procedure that was chosen allowed identification of proteins exhaled by healthy people. The major proteins in the condensates were cytoskeletal keratins. Another 12 proteins were identified in EBC from healthy non-smokers. Some keratins were found in the ambient air and may be considered exogenous components of exhaled air. Knowledge of the normal proteome of exhaled breath allows one to look for biomarkers of different disease states in EBC. Proteins in ambient air can be identified in the respiratory tract and should be excluded from the analysis of the proteome of EBC. The results obtained allowed us to choose the most effective procedure of sample preparation when working with samples containing very low protein concentrations.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

PubMed

Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

2009-10-06

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences

PubMed Central

Holmes, Christina; Carlson, Siobhan M.; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-01

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics. PMID:27134568

Drought-Responsive Mechanisms in Plant Leaves Revealed by Proteomics.

PubMed

Wang, Xiaoli; Cai, Xiaofeng; Xu, Chenxi; Wang, Quanhua; Dai, Shaojun

2016-10-18

Plant drought tolerance is a complex trait that requires a global view to understand its underlying mechanism. The proteomic aspects of plant drought response have been extensively investigated in model plants, crops and wood plants. In this review, we summarize recent proteomic studies on drought response in leaves to reveal the common and specialized drought-responsive mechanisms in different plants. Although drought-responsive proteins exhibit various patterns depending on plant species, genotypes and stress intensity, proteomic analyses show that dominant changes occurred in sensing and signal transduction, reactive oxygen species scavenging, osmotic regulation, gene expression, protein synthesis/turnover, cell structure modulation, as well as carbohydrate and energy metabolism. In combination with physiological and molecular results, proteomic studies in leaves have helped to discover some potential proteins and/or metabolic pathways for drought tolerance. These findings provide new clues for understanding the molecular basis of plant drought tolerance.

Drought-Responsive Mechanisms in Plant Leaves Revealed by Proteomics

PubMed Central

Wang, Xiaoli; Cai, Xiaofeng; Xu, Chenxi; Wang, Quanhua; Dai, Shaojun

2016-01-01

Plant drought tolerance is a complex trait that requires a global view to understand its underlying mechanism. The proteomic aspects of plant drought response have been extensively investigated in model plants, crops and wood plants. In this review, we summarize recent proteomic studies on drought response in leaves to reveal the common and specialized drought-responsive mechanisms in different plants. Although drought-responsive proteins exhibit various patterns depending on plant species, genotypes and stress intensity, proteomic analyses show that dominant changes occurred in sensing and signal transduction, reactive oxygen species scavenging, osmotic regulation, gene expression, protein synthesis/turnover, cell structure modulation, as well as carbohydrate and energy metabolism. In combination with physiological and molecular results, proteomic studies in leaves have helped to discover some potential proteins and/or metabolic pathways for drought tolerance. These findings provide new clues for understanding the molecular basis of plant drought tolerance. PMID:27763546

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences.

PubMed

Holmes, Christina; Carlson, Siobhan M; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-02

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics.

Life without complex I: proteome analyses of an Arabidopsis mutant lacking the mitochondrial NADH dehydrogenase complex

PubMed Central

Fromm, Steffanie; Senkler, Jennifer; Eubel, Holger; Peterhänsel, Christoph; Braun, Hans-Peter

2016-01-01

The mitochondrial NADH dehydrogenase complex (complex I) is of particular importance for the respiratory chain in mitochondria. It is the major electron entry site for the mitochondrial electron transport chain (mETC) and therefore of great significance for mitochondrial ATP generation. We recently described an Arabidopsis thaliana double-mutant lacking the genes encoding the carbonic anhydrases CA1 and CA2, which both form part of a plant-specific ‘carbonic anhydrase domain’ of mitochondrial complex I. The mutant lacks complex I completely. Here we report extended analyses for systematically characterizing the proteome of the ca1ca2 mutant. Using various proteomic tools, we show that lack of complex I causes reorganization of the cellular respiration system. Reduced electron entry into the respiratory chain at the first segment of the mETC leads to induction of complexes II and IV as well as alternative oxidase. Increased electron entry at later segments of the mETC requires an increase in oxidation of organic substrates. This is reflected by higher abundance of proteins involved in glycolysis, the tricarboxylic acid cycle and branched-chain amino acid catabolism. Proteins involved in the light reaction of photosynthesis, the Calvin cycle, tetrapyrrole biosynthesis, and photorespiration are clearly reduced, contributing to the significant delay in growth and development of the double-mutant. Finally, enzymes involved in defense against reactive oxygen species and stress symptoms are much induced. These together with previously reported insights into the function of plant complex I, which were obtained by analysing other complex I mutants, are integrated in order to comprehensively describe ‘life without complex I’. PMID:27122571

Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry*

PubMed Central

Hewel, Johannes A.; Liu, Jian; Onishi, Kento; Fong, Vincent; Chandran, Shamanta; Olsen, Jonathan B.; Pogoutse, Oxana; Schutkowski, Mike; Wenschuh, Holger; Winkler, Dirk F. H.; Eckler, Larry; Zandstra, Peter W.; Emili, Andrew

2010-01-01

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including “label-free” quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations. PMID:20467045

Impact of pretreated Switchgrass and biomass carbohydrates on Clostridium thermocellum ATCC 27405 cellulosome composition: a quantitative proteomic analysis.

PubMed

Raman, Babu; Pan, Chongle; Hurst, Gregory B; Rodriguez, Miguel; McKeown, Catherine K; Lankford, Patricia K; Samatova, Nagiza F; Mielenz, Jonathan R

2009-01-01

Economic feasibility and sustainability of lignocellulosic ethanol production requires the development of robust microorganisms that can efficiently degrade and convert plant biomass to ethanol. The anaerobic thermophilic bacterium Clostridium thermocellum is a candidate microorganism as it is capable of hydrolyzing cellulose and fermenting the hydrolysis products to ethanol and other metabolites. C. thermocellum achieves efficient cellulose hydrolysis using multiprotein extracellular enzymatic complexes, termed cellulosomes. In this study, we used quantitative proteomics (multidimensional LC-MS/MS and (15)N-metabolic labeling) to measure relative changes in levels of cellulosomal subunit proteins (per CipA scaffoldin basis) when C. thermocellum ATCC 27405 was grown on a variety of carbon sources [dilute-acid pretreated switchgrass, cellobiose, amorphous cellulose, crystalline cellulose (Avicel) and combinations of crystalline cellulose with pectin or xylan or both]. Cellulosome samples isolated from cultures grown on these carbon sources were compared to (15)N labeled cellulosome samples isolated from crystalline cellulose-grown cultures. In total from all samples, proteomic analysis identified 59 dockerin- and 8 cohesin-module containing components, including 16 previously undetected cellulosomal subunits. Many cellulosomal components showed differential protein abundance in the presence of non-cellulose substrates in the growth medium. Cellulosome samples from amorphous cellulose, cellobiose and pretreated switchgrass-grown cultures displayed the most distinct differences in composition as compared to cellulosome samples from crystalline cellulose-grown cultures. While Glycoside Hydrolase Family 9 enzymes showed increased levels in the presence of crystalline cellulose, and pretreated switchgrass, in particular, GH5 enzymes showed increased levels in response to the presence of cellulose in general, amorphous or crystalline. Overall, the quantitative results suggest a coordinated substrate-specific regulation of cellulosomal subunit composition in C. thermocellum to better suit the organism's needs for growth under different conditions. To date, this study provides the most comprehensive comparison of cellulosomal compositional changes in C. thermocellum in response to different carbon sources. Such studies are vital to engineering a strain that is best suited to grow on specific substrates of interest and provide the building blocks for constructing designer cellulosomes with tailored enzyme composition for industrial ethanol production.

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.

Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer*

PubMed Central

Gallien, Sebastien; Duriez, Elodie; Crone, Catharina; Kellmann, Markus; Moehring, Thomas; Domon, Bruno

2012-01-01

There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein quantification methods in complex samples and address the pressing demand of systems biology or biomarker evaluation studies. PMID:22962056

Antibody Protein Array Analysis of the Tear Film Cytokines

PubMed Central

Li, Shimin; Sack, Robert; Vijmasi, Trinka; Sathe, Sonal; Beaton, Ann; Quigley, David; Gallup, Marianne; McNamara, Nancy A.

2013-01-01

Purpose Many bioactive proteins including cytokines are reported to increase in dry eye disease although the specific profile and concentration of inflammatory mediators varies considerably from study to study. In part this variability results from inherent difficulties in quantifying low abundance proteins in a limited sample volume using relatively low sensitivity dot ELISA methods. Additional complexity comes with the use of pooled samples collected using a variety of techniques and intrinsic variation in the diurnal pattern of individual tear proteins. The current study describes a recent advance in the area of proteomics that has allowed the identification of dozens of low abundance proteins in human tear samples. Methods Commercially available stationary phase antibody protein arrays were adapted to improve suitability for use in small volume biological fluid analysis with particular emphasis on tear film proteomics. Arrays were adapted to allow simultaneous screening for a panel of inflammatory cytokines in low volume tear samples collected from individual eyes. Results A preliminary study comparing tear array results in a small population of Sjögren’s syndrome patients was conducted. The multiplex microplate array assays of cytokines in tear fluid present an unanticipated challenge due to the unique nature of tear fluid. The presence of factors that exhibit an affinity for plastic, capture antibodies and IgG and create a complex series of matrix effects profoundly impacting the reliability of dot ELISA, including with elevated levels of background reactivity and reduction in capacity to bind targeted protein. Conclusions Preliminary results using tears collected from patients with Sjögren’s syndrome reveal methodological advantages of protein array technology and support the concept that autoimmune-mediated dry eye disease has an inflammatory component. They also emphasize the inherent difficulties one can face when interpreting the results of micro-well arrays that result from blooming effects, matrix effects, image saturation and cross-talk between capture and probe antibodies that can greatly reduce signal-to-noise and limit the ability to obtain meaningful results. PMID:18677223

IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomic biomarker discovery

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

Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.

2012-02-01

Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up tomore » 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.« less

Quantitative proteomics and dynamic imaging of the nucleolus reveal distinct responses to UV and ionizing radiation.

PubMed

Moore, Henna M; Bai, Baoyan; Boisvert, François-Michel; Latonen, Leena; Rantanen, Ville; Simpson, Jeremy C; Pepperkok, Rainer; Lamond, Angus I; Laiho, Marikki

2011-10-01

The nucleolus is a nuclear organelle that coordinates rRNA transcription and ribosome subunit biogenesis. Recent proteomic analyses have shown that the nucleolus contains proteins involved in cell cycle control, DNA processing and DNA damage response and repair, in addition to the many proteins connected with ribosome subunit production. Here we study the dynamics of nucleolar protein responses in cells exposed to stress and DNA damage caused by ionizing and ultraviolet (UV) radiation in diploid human fibroblasts. We show using a combination of imaging and quantitative proteomics methods that nucleolar substructure and the nucleolar proteome undergo selective reorganization in response to UV damage. The proteomic responses to UV include alterations of functional protein complexes such as the SSU processome and exosome, and paraspeckle proteins, involving both decreases and increases in steady state protein ratios, respectively. Several nonhomologous end-joining proteins (NHEJ), such as Ku70/80, display similar fast responses to UV. In contrast, nucleolar proteomic responses to IR are both temporally and spatially distinct from those caused by UV, and more limited in terms of magnitude. With the exception of the NHEJ and paraspeckle proteins, where IR induces rapid and transient changes within 15 min of the damage, IR does not alter the ratios of most other functional nucleolar protein complexes. The rapid transient decrease of NHEJ proteins in the nucleolus indicates that it may reflect a response to DNA damage. Our results underline that the nucleolus is a specific stress response organelle that responds to different damage and stress agents in a unique, damage-specific manner.

Proteomic approaches to study the pig intestinal system.

PubMed

Soler, Laura; Niewold, Theo A; Moreno, Ángela; Garrido, Juan Jose

2014-03-01

One of the major challenges in pig production is managing digestive health to maximize feed conversion and growth rates, but also to minimize treatment costs and to warrant public health. There is a great interest in the development of useful tools for intestinal health monitoring and the investigation of possible prophylactic/ therapeutic intervention pathways. A great variety of in vivo and in vitro intestinal models of study have been developed in the recent years. The understanding of such a complex system as the intestinal system (IS), and the study of its physiology and pathology is not an easy task. Analysis of such a complex system requires the use of systems biology techniques, like proteomics. However, for a correct interpretation of results and to maximize analysis performance, a careful selection of the IS model of study and proteomic platform is required. The study of the IS system is especially important in the pig, a species whose farming requires a very careful management of husbandry procedures regarding feeding and nutrition. The incorrect management of the pig digestive system leads directly to economic losses related suboptimal growth and feed utilization and/or the appearance of intestinal infections, in particular diarrhea. Furthermore, this species is the most suitable experimental model for human IS studies. Proteomics has risen as one of the most promising approaches to study the pig IS. In this review, we describe the most useful models of IS research in porcine and the different proteomic platforms available. An overview of the recent findings in pig IS proteomics is also provided.

MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

PubMed

Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-10-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

MStern Blotting–High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates*

PubMed Central

Berger, Sebastian T.; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-01-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. PMID:26223766

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

PubMed

Arntzen, Magnus Ø; Thiede, Bernd

2012-02-01

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

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

PubMed Central

Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

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

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

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

PubMed

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

2015-08-25

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

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

PubMed

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

2014-03-01

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

Isolation and Preparation of Extracellular Proteins from Lignocellulose Degrading Fungi for Comparative Proteomic Studies Using Mass Spectrometry.

PubMed

Gruninger, Robert J; Tsang, Adrian; McAllister, Tim A

2017-01-01

Fungi utilize a unique mechanism of nutrient acquisition involving extracellular digestion. To understand the biology of these microbes, it is important to identify and characterize the function of proteins that are secreted and involved in this process. Mass spectrometry-based proteomics is a powerful tool to study complex mixtures of proteins and understand how the proteins produced by an organism change in response to different conditions. Many fungi are efficient decomposers of plant cell wall, and anaerobic fungi are well recognized for their ability to digest lignocellulose. Here, we outline a protocol for the enrichment and isolation of proteins secreted by anaerobic fungi after growth on simple (glucose) and complex (straw and alfalfa hay) carbon sources. We provide detailed instruction on generating protein fragments and preparing these for proteomic analysis using reversed phase chromatography and mass spectrometry.

Design and Initial Characterization of the SC-200 Proteomics Standard Mixture

PubMed Central

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald

2011-01-01

Abstract High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels. PMID:21250827

Design and initial characterization of the SC-200 proteomics standard mixture.

PubMed

Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald; Kolker, Eugene

2011-01-01

High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels.

Proteomics: a new approach to the study of disease.

PubMed

Chambers, G; Lawrie, L; Cash, P; Murray, G I

2000-11-01

The global analysis of cellular proteins has recently been termed proteomics and is a key area of research that is developing in the post-genome era. Proteomics uses a combination of sophisticated techniques including two-dimensional (2D) gel electrophoresis, image analysis, mass spectrometry, amino acid sequencing, and bio-informatics to resolve comprehensively, to quantify, and to characterize proteins. The application of proteomics provides major opportunities to elucidate disease mechanisms and to identify new diagnostic markers and therapeutic targets. This review aims to explain briefly the background to proteomics and then to outline proteomic techniques. Applications to the study of human disease conditions ranging from cancer to infectious diseases are reviewed. Finally, possible future advances are briefly considered, especially those which may lead to faster sample throughput and increased sensitivity for the detection of individual proteins. Copyright 2000 John Wiley & Sons, Ltd.

Clinical proteomic analysis of scrub typhus infection.

PubMed

Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

2018-01-01

Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

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

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

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

Analysis of the early heterocyst Cys-proteome in the multicellular cyanobacterium Nostoc punctiforme reveals novel insights into the division of labor within diazotrophic filaments.

PubMed

Sandh, Gustaf; Ramström, Margareta; Stensjö, Karin

2014-12-04

In the filamentous cyanobacterium Nostoc punctiforme ATCC 29133, removal of combined nitrogen induces the differentiation of heterocysts, a cell-type specialized in N2 fixation. The differentiation involves genomic, structural and metabolic adaptations. In cyanobacteria, changes in the availability of carbon and nitrogen have also been linked to redox regulated posttranslational modifications of protein bound thiol groups. We have here employed a thiol targeting strategy to relatively quantify the putative redox proteome in heterocysts as compared to N2-fixing filaments, 24 hours after combined nitrogen depletion. The aim of the study was to expand the coverage of the cell-type specific proteome and metabolic landscape of heterocysts. Here we report the first cell-type specific proteome of newly formed heterocysts, compared to N2-fixing filaments, using the cysteine-specific selective ICAT methodology. The data set defined a good quantitative accuracy of the ICAT reagent in complex protein samples. The relative abundance levels of 511 proteins were determined and 74% showed a cell-type specific differential abundance. The majority of the identified proteins have not previously been quantified at the cell-type specific level. We have in addition analyzed the cell-type specific differential abundance of a large section of proteins quantified in both newly formed and steady-state diazotrophic cultures in N. punctiforme. The results describe a wide distribution of members of the putative redox regulated Cys-proteome in the central metabolism of both vegetative cells and heterocysts of N. punctiforme. The data set broadens our understanding of heterocysts and describes novel proteins involved in heterocyst physiology, including signaling and regulatory proteins as well as a large number of proteins with unknown function. Significant differences in cell-type specific abundance levels were present in the cell-type specific proteomes of newly formed diazotrophic filaments as compared to steady-state cultures. Therefore we conclude that by using our approach we are able to analyze a synchronized fraction of newly formed heterocysts, which enabled a better detection of proteins involved in the heterocyst specific physiology.

Characterisation of the Manduca sexta sperm proteome: Genetic novelty underlying sperm composition in Lepidoptera.

PubMed

Whittington, Emma; Zhao, Qian; Borziak, Kirill; Walters, James R; Dorus, Steve

2015-07-01

The application of mass spectrometry based proteomics to sperm biology has greatly accelerated progress in understanding the molecular composition and function of spermatozoa. To date, these approaches have been largely restricted to model organisms, all of which produce a single sperm morph capable of oocyte fertilisation. Here we apply high-throughput mass spectrometry proteomic analysis to characterise sperm composition in Manduca sexta, the tobacco hornworm moth, which produce heteromorphic sperm, including one fertilisation competent (eupyrene) and one incompetent (apyrene) sperm type. This resulted in the high confidence identification of 896 proteins from a co-mixed sample of both sperm types, of which 167 are encoded by genes with strict one-to-one orthology in Drosophila melanogaster. Importantly, over half (55.1%) of these orthologous proteins have previously been identified in the D. melanogaster sperm proteome and exhibit significant conservation in quantitative protein abundance in sperm between the two species. Despite the complex nature of gene expression across spermatogenic stages, a significant correlation was also observed between sperm protein abundance and testis gene expression. Lepidopteran-specific sperm proteins (e.g., proteins with no homology to proteins in non-Lepidopteran taxa) were present in significantly greater abundance on average than those with homology outside the Lepidoptera. Given the disproportionate production of apyrene sperm (96% of all mature sperm in Manduca) relative to eupyrene sperm, these evolutionarily novel and highly abundant proteins are candidates for possessing apyrene-specific functions. Lastly, comparative genomic analyses of testis-expressed, ovary-expressed and sperm genes identified a concentration of novel sperm proteins shared amongst Lepidoptera of potential relevance to the evolutionary origin of heteromorphic spermatogenesis. As the first published Lepidopteran sperm proteome, this whole-cell proteomic characterisation will facilitate future evolutionary genetic and developmental studies of heteromorphic sperm production and parasperm function. Furthermore, the analyses presented here provide useful annotation information regarding sex-biased gene expression, novel Lepidopteran genes and gene function in the male gamete to complement the newly sequenced and annotated Manduca genome. Copyright © 2015 Elsevier Ltd. All rights reserved.

Proteomics data repositories

PubMed Central

Riffle, Michael; Eng, Jimmy K.

2010-01-01

The field of proteomics, particularly the application of mass spectrometry analysis to protein samples, is well-established and growing rapidly. Proteomics studies generate large volumes of raw experimental data and inferred biological results. To facilitate the dissemination of these data, centralized data repositories have been developed that make the data and results accessible to proteomics researchers and biologists alike. This review of proteomics data repositories focuses exclusively on freely-available, centralized data resources that disseminate or store experimental mass spectrometry data and results. The resources chosen reflect a current “snapshot” of the state of resources available with an emphasis placed on resources that may be of particular interest to yeast researchers. Resources are described in terms of their intended purpose and the features and functionality provided to users. PMID:19795424

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; Bae, Jingi; Kim, Hokeun; Oh, Se Yeon; Park, Young Soo; Lee, Jae-Hyuk; Lee, Sang-Won

2015-08-21

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

Physiological and Comparative Proteomic Analysis Reveals Different Drought Responses in Roots and Leaves of Drought-Tolerant Wild Wheat (Triticum boeoticum)

PubMed Central

Liu, Hui; Sultan, Muhammad Abdul Rab Faisal; Liu, Xiang li; Zhang, Jin; Yu, Fei; Zhao, Hui xian

2015-01-01

To determine the proteomic-level responses of drought tolerant wild wheat (Triticum boeoticum), physiological and comparative proteomic analyses were conducted using the roots and the leaves of control and short term drought-stressed plants. Drought stress was imposed by transferring hydroponically grown seedlings at the 3-leaf stage into 1/2 Hoagland solution containing 20% PEG-6000 for 48 h. Root and leaf samples were separately collected at 0 (control), 24, and 48 h of drought treatment for analysis. Physiological analysis indicated that abscisic acid (ABA) level was greatly increased in the drought-treated plants, but the increase was greater and more rapid in the leaves than in the roots. The net photosynthetic rate of the wild wheat leaves was significantly decreased under short-term drought stress. The deleterious effects of drought on the studied traits mainly targeted photosynthesis. Comparative proteomic analysis identified 98 and 85 differently changed protein spots (DEPs) (corresponding to 87 and 80 unique proteins, respectively) in the leaves and the roots, respectively, with only 6 mutual unique proteins in the both organs. An impressive 86% of the DEPs were implicated in detoxification and defense, carbon metabolism, amino acid and nitrogen metabolism, proteins metabolism, chaperones, transcription and translation, photosynthesis, nucleotide metabolism, and signal transduction. Further analysis revealed some mutual and tissue-specific responses to short-term drought in the leaves and the roots. The differences of drought-response between the roots and the leaves mainly included that signal sensing and transduction-associated proteins were greatly up-regulated in the roots. Photosynthesis and carbon fixation ability were decreased in the leaves. Glycolysis was down-regulated but PPP pathway enhanced in the roots, resulting in occurrence of complex changes in energy metabolism and establishment of a new homeostasis. Protein metabolism was down-regulated in the roots, but enhanced in the leaves. These results will contribute to the existing knowledge on the complexity of root and leaf protein changes that occur in response to drought, and also provide a framework for further functional studies on the identified proteins. PMID:25859656

Peptidomics of Three Bothrops Snake Venoms: Insights Into the Molecular Diversification of Proteomes and Peptidomes*

PubMed Central

Tashima, Alexandre K.; Zelanis, André; Kitano, Eduardo S.; Ianzer, Danielle; Melo, Robson L.; Rioli, Vanessa; Sant'anna, Sávio S.; Schenberg, Ana C. G.; Camargo, Antônio C. M.; Serrano, Solange M. T.

2012-01-01

Snake venom proteomes/peptidomes are highly complex and maintenance of their integrity within the gland lumen is crucial for the expression of toxin activities. There has been considerable progress in the field of venom proteomics, however, peptidomics does not progress as fast, because of the lack of comprehensive venom sequence databases for analysis of MS data. Therefore, in many cases venom peptides have to be sequenced manually by MS/MS analysis or Edman degradation. This is critical for rare snake species, as is the case of Bothrops cotiara (BC) and B. fonsecai (BF), which are regarded as near threatened with extinction. In this study we conducted a comprehensive analysis of the venom peptidomes of BC, BF, and B. jararaca (BJ) using a combination of solid-phase extraction and reversed-phase HPLC to fractionate the peptides, followed by nano-liquid chromatography-tandem MS (LC-MS/MS) or direct infusion electrospray ionization-(ESI)-MS/MS or MALDI-MS/MS analyses. We detected marked differences in the venom peptidomes and identified peptides ranging from 7 to 39 residues in length by de novo sequencing. Forty-four unique sequences were manually identified, out of which 30 are new peptides, including 17 bradykinin-potentiating peptides, three poly-histidine-poly-glycine peptides and interestingly, 10 l-amino acid oxidase fragments. Some of the new bradykinin-potentiating peptides display significant bradykinin potentiating activity. Automated database search revealed fragments from several toxins in the peptidomes, mainly from l-amino acid oxidase, and allowed the determination of the peptide bond specificity of proteinases and amino acid occurrences for the P4-P4′ sites. We also demonstrate that the venom lyophilization/resolubilization process greatly increases the complexity of the peptidome because of the imbalance caused to the venom proteome and the consequent activity of proteinases on venom components. The use of proteinase inhibitors clearly showed different outcomes in the peptidome characterization and suggested that degradomic-peptidomic analysis of snake venoms is highly sensitive to the conditions of sampling procedures. PMID:22869554

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

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

2014-01-01

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

Science, marketing and wishful thinking in quantitative proteomics.

PubMed

Hackett, Murray

2008-11-01

In a recent editorial (J. Proteome Res. 2007, 6, 1633) and elsewhere questions have been raised regarding the lack of attention paid to good analytical practice with respect to the reporting of quantitative results in proteomics. Using those comments as a starting point, several issues are discussed that relate to the challenges involved in achieving adequate sampling with MS-based methods in order to generate valid data for large-scale studies. The discussion touches on the relationships that connect sampling depth and the power to detect protein abundance change, conflict of interest, and strategies to overcome bureaucratic obstacles that impede the use of peer-to-peer technologies for transfer and storage of large data files generated in such experiments.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Gielisch, Ina; Meierhofer, David

2015-01-02

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

Proteomic Profiling of Paraffin-Embedded Samples Identifies Metaplasia-Specific and Early-Stage Gastric Cancer Biomarkers

PubMed Central

Sousa, Josane F.; Ham, Amy-Joan L.; Whitwell, Corbin; Nam, Ki Taek; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Zhang, Bing; Li, Ming; LaFleur, Bonnie; Liebler, Daniel C.; Goldenring, James R.

2013-01-01

Early diagnosis and curative resection are the predominant factors associated with increased survival in patients with gastric cancer. However, most gastric cancer cases are still diagnosed at later stages. Since most pathologic specimens are archived as FFPE samples, the ability to use them to generate expression profiles can greatly improve cancer biomarker discovery. We sought to uncover new biomarkers for stomach preneoplastic metaplasias and neoplastic lesions by generating proteome profiles using FFPE samples. We combined peptide isoelectric focusing and liquid chromatography–tandem mass spectrometry analysis to generate proteomic profiles from FFPE samples of intestinal-type gastric cancer, metaplasia, and normal mucosa. The expression patterns of selected proteins were analyzed by immunostaining first in single tissue sections from normal stomach, metaplasia, and gastric cancer and later in larger tissue array cohorts. We detected 60 proteins up-regulated and 87 proteins down-regulated during the progression from normal mucosa to metaplasia to gastric cancer. Two of the up-regulated proteins, LTF and DMBT1, were validated as specific markers for spasmolytic polypeptide–expressing metaplasia and intestinal metaplasia, respectively. In cancers, significantly lower levels of DMBT1 or LTF correlated with more advanced disease and worse prognosis. Thus, proteomic profiling using FFPE samples has led to the identification of two novel markers for stomach metaplasias and gastric cancer prognosis. PMID:22944598

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

PubMed Central

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

2016-01-01

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

Proteomics and bioinformatics analysis of altered protein expression in the placental villous tissue from early recurrent miscarriage patients.

PubMed

Pan, Hai-Tao; Ding, Hai-Gang; Fang, Min; Yu, Bin; Cheng, Yi; Tan, Ya-Jing; Fu, Qi-Qin; Lu, Bo; Cai, Hong-Guang; Jin, Xin; Xia, Xian-Qing; Zhang, Tao

2018-01-01

Recurrent miscarriage (RM) affects 5% of women, it has an adverse emotional impact on women. Because of the complexities of early development, the mechanism of recurrent miscarriage is still unclear. We hypothesized that abnormal placenta leads to early recurrent miscarriage (ERM). The aim of this study was to identify ERM associated factors in human placenta villous tissue using proteomics. Investigation of these differences in protein expression in parallel profiling is essential to understand the comprehensive pathophysiological mechanism underlying recurrent miscarriage (RM). To gain more insight into mechanisms of recurrent miscarriage (RM), a comparative proteome profile of the human placenta villous tissue in normal and RM pregnancies was analyzed using iTRAQ technology and bioinformatics analysis used by Ingenuity Pathway Analysis (IPA) software. In this study, we employed an iTRAQ based proteomics analysis of four placental villous tissues from patients with early recurrent miscarriage (ERM) and four from normal pregnant women. Finally, we identified 2805 proteins and 79,998 peptides between patients with RM and normal matched group. Further analysis identified 314 differentially expressed proteins in placental villous tissue (≥1.3-fold, Student's t-test, p < 0.05); 209 proteins showed the increased expression while 105 proteins showed decreased expression. These 314 proteins were analyzed by Ingenuity Pathway Analysis (IPA) and were found to play important roles in the growth of embryo. Furthermore, network analysis show that Angiotensinogen (AGT), MAPK14 and Prothrombin (F2) are core factors in early embryonic development. We used another 8 independent samples (4 cases and 4 controls) to cross validation of the proteomic data. This study has identified several proteins that are associated with early development, these results may supply new insight into mechanisms behind recurrent miscarriage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria

PubMed Central

Hui, Sheng; Silverman, Josh M; Chen, Stephen S; Erickson, David W; Basan, Markus; Wang, Jilong; Hwa, Terence; Williamson, James R

2015-01-01

A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. PMID:25678603

Marine proteomics: a critical assessment of an emerging technology.

PubMed

Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M

2012-10-26

The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

Deep sequencing and proteomic analysis of the microRNA-induced silencing complex in human red blood cells.

PubMed

Azzouzi, Imane; Moest, Hansjoerg; Wollscheid, Bernd; Schmugge, Markus; Eekels, Julia J M; Speer, Oliver

2015-05-01

During maturation, erythropoietic cells extrude their nuclei but retain their ability to respond to oxidant stress by tightly regulating protein translation. Several studies have reported microRNA-mediated regulation of translation during terminal stages of erythropoiesis, even after enucleation. In the present study, we performed a detailed examination of the endogenous microRNA machinery in human red blood cells using a combination of deep sequencing analysis of microRNAs and proteomic analysis of the microRNA-induced silencing complex. Among the 197 different microRNAs detected, miR-451a was the most abundant, representing more than 60% of all read sequences. In addition, miR-451a and its known target, 14-3-3ζ mRNA, were bound to the microRNA-induced silencing complex, implying their direct interaction in red blood cells. The proteomic characterization of endogenous Argonaute 2-associated microRNA-induced silencing complex revealed 26 cofactor candidates. Among these cofactors, we identified several RNA-binding proteins, as well as motor proteins and vesicular trafficking proteins. Our results demonstrate that red blood cells contain complex microRNA machinery, which might enable immature red blood cells to control protein translation independent of de novo nuclei information. Copyright © 2015 ISEH - International Society for Experimental Hematology. Published by Elsevier Inc. All rights reserved.

Applications of reversible covalent chemistry in analytical sample preparation.

PubMed

Siegel, David

2012-12-07

Reversible covalent chemistry (RCC) adds another dimension to commonly used sample preparation techniques like solid-phase extraction (SPE), solid-phase microextraction (SPME), molecular imprinted polymers (MIPs) or immuno-affinity cleanup (IAC): chemical selectivity. By selecting analytes according to their covalent reactivity, sample complexity can be reduced significantly, resulting in enhanced analytical performance for low-abundance target analytes. This review gives a comprehensive overview of the applications of RCC in analytical sample preparation. The major reactions covered include reversible boronic ester formation, thiol-disulfide exchange and reversible hydrazone formation, targeting analyte groups like diols (sugars, glycoproteins and glycopeptides, catechols), thiols (cysteinyl-proteins and cysteinyl-peptides) and carbonyls (carbonylated proteins, mycotoxins). Their applications range from low abundance proteomics to reversible protein/peptide labelling to antibody chromatography to quantitative and qualitative food analysis. In discussing the potential of RCC, a special focus is on the conditions and restrictions of the utilized reaction chemistry.

The quest of the human proteome and the missing proteins: digging deeper.

PubMed

Reddy, Panga Jaipal; Ray, Sandipan; Srivastava, Sanjeeva

2015-05-01

Given the diverse range of transcriptional and post-transcriptional mechanisms of gene regulation, the estimates of the human proteome is likely subject to scientific surprises as the field of proteomics has gained momentum worldwide. In this regard, the establishment of the "Human Proteome Draft" using high-resolution mass spectrometry (MS), tissue microarrays, and immunohistochemistry by three independent research groups (laboratories of Pandey, Kuster, and Uhlen) accelerated the pace of proteomics research. The Chromosome Centric Human Proteome Project (C-HPP) has taken initiative towards the completion of the Human Proteome Project (HPP) so as to understand the proteomics correlates of common complex human diseases and biological diversity, not to mention person-to-person and population differences in response to drugs, nutrition, vaccines, and other health interventions and host-environment interactions. Although high-resolution MS-based and antibody microarray approaches have shown enormous promises, we are still unable to map the whole human proteome due to the presence of numerous "missing proteins." In December 2014, at the Indian Institute of Technology Bombay, Mumbai the 6(th) Annual Meeting of the Proteomics Society, India (PSI) and the International Proteomics Conference was held. As part of this interdisciplinary summit, a panel discussion session on "The Quest of the Human Proteome and Missing Proteins" was organized. Eminent scientists in the field of proteomics and systems biology, including Akhilesh Pandey, Gilbert S. Omenn, Mark S. Baker, and Robert L. Mortiz, shed light on different aspects of the human proteome drafts and missing proteins. Importantly, the possible reasons for the "missing proteins" in shotgun MS workflow were identified and debated by experts as low tissue expression, lack of enzymatic digestion site, or protein lost during extraction, among other contributing factors. To capture the missing proteins, the experts' collective view was to study the wider tissue range with multiple digesting enzymes and follow targeted proteomics workflow in particular. On the innovation trajectory from the proteomics laboratory to novel proteomics diagnostics and therapeutics in society, we will also need new conceptual frames for translation science and innovation strategy in proteomics. These will embody both technical as well as rigorous social science and humanities considerations to understand the correlates of the proteome from cell to society.

Needles in the blue sea: sub-species specificity in targeted protein biomarker analyses within the vast oceanic microbial metaproteome.

PubMed

Saito, Mak A; Dorsk, Alexander; Post, Anton F; McIlvin, Matthew R; Rappé, Michael S; DiTullio, Giacomo R; Moran, Dawn M

2015-10-01

Proteomics has great potential for studies of marine microbial biogeochemistry, yet high microbial diversity in many locales presents us with unique challenges. We addressed this challenge with a targeted metaproteomics workflow for NtcA and P-II, two nitrogen regulatory proteins, and demonstrated its application for cyanobacterial taxa within microbial samples from the Central Pacific Ocean. Using METATRYP, an open-source Python toolkit, we examined the number of shared (redundant) tryptic peptides in representative marine microbes, with the number of tryptic peptides shared between different species typically being 1% or less. The related cyanobacteria Prochlorococcus and Synechococcus shared an average of 4.8 ± 1.9% of their tryptic peptides, while shared intraspecies peptides were higher, 13 ± 15% shared peptides between 12 Prochlorococcus genomes. An NtcA peptide was found to target multiple cyanobacteria species, whereas a P-II peptide showed specificity to the high-light Prochlorococcus ecotype. Distributions of NtcA and P-II in the Central Pacific Ocean were similar except at the Equator likely due to differential nitrogen stress responses between Prochlorococcus and Synechococcus. The number of unique tryptic peptides coded for within three combined oceanic microbial metagenomes was estimated to be ∼4 × 10(7) , 1000-fold larger than an individual microbial proteome and 27-fold larger than the human proteome, yet still 20 orders of magnitude lower than the peptide diversity possible in all protein space, implying that peptide mapping algorithms should be able to withstand the added level of complexity in metaproteomic samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lysine acetylation stoichiometry and proteomics analyses reveal pathways regulated by sirtuin 1 in human cells.

PubMed

Gil, Jeovanis; Ramírez-Torres, Alberto; Chiappe, Diego; Luna-Peñaloza, Juan; Fernandez-Reyes, Francis C; Arcos-Encarnación, Bolivar; Contreras, Sandra; Encarnación-Guevara, Sergio

2017-11-03

Lysine acetylation is a widespread posttranslational modification affecting many biological pathways. Recent studies indicate that acetylated lysine residues mainly exhibit low acetylation occupancy, but challenges in sample preparation and analysis make it difficult to confidently assign these numbers, limiting understanding of their biological significance. Here, we tested three common sample preparation methods to determine their suitability for assessing acetylation stoichiometry in three human cell lines, identifying the acetylation occupancy in more than 1,300 proteins from each cell line. The stoichiometric analysis in combination with quantitative proteomics also enabled us to explore their functional roles. We found that higher abundance of the deacetylase sirtuin 1 (SIRT1) correlated with lower acetylation occupancy and lower levels of ribosomal proteins, including those involved in ribosome biogenesis and rRNA processing. Treatment with the SIRT1 inhibitor EX-527 confirmed SIRT1's role in the regulation of pre-rRNA synthesis and processing. Specifically, proteins involved in pre-rRNA transcription, including subunits of the polymerase I and SL1 complexes and the RNA polymerase I-specific transcription initiation factor RRN3, were up-regulated after SIRT1 inhibition. Moreover, many protein effectors and regulators of pre-rRNA processing needed for rRNA maturation were also up-regulated after EX-527 treatment with the outcome that pre-rRNA and 28S rRNA levels also increased. More generally, we found that SIRT1 inhibition down-regulates metabolic pathways, including glycolysis and pyruvate metabolism. Together, these results provide the largest data set thus far of lysine acetylation stoichiometry (available via ProteomeXchange with identifier PXD005903) and set the stage for further biological investigations of this central posttranslational modification. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Integrating Mass Spectrometry of Intact Protein Complexes into Structural Proteomics

PubMed Central

Hyung, Suk-Joon; Ruotolo, Brandon T.

2013-01-01

Summary Mass spectrometry analysis of intact protein complexes has emerged as an established technology for assessing the composition and connectivity within dynamic, heterogeneous multiprotein complexes at low concentrations and in the context of mixtures. As this technology continues to move forward, one of the main challenges is to integrate the information content of such intact protein complex measurements with other mass spectrometry approaches in structural biology. Methods such as H/D exchange, oxidative foot-printing, chemical cross-linking, affinity purification, and ion mobility separation add complementary information that allows access to every level of protein structure and organization. Here, we survey the structural information that can be retrieved by such experiments, demonstrate the applicability of integrative mass spectrometry approaches in structural proteomics, and look to the future to explore upcoming innovations in this rapidly-advancing area. PMID:22611037

Mapping Proteoforms and Protein Complexes From King Cobra Venom Using Both Denaturing and Native Top-down Proteomics.

PubMed

Melani, Rafael D; Skinner, Owen S; Fornelli, Luca; Domont, Gilberto B; Compton, Philip D; Kelleher, Neil L

2016-07-01

Characterizing whole proteins by top-down proteomics avoids a step of inference encountered in the dominant bottom-up methodology when peptides are assembled computationally into proteins for identification. The direct interrogation of whole proteins and protein complexes from the venom of Ophiophagus hannah (king cobra) provides a sharply clarified view of toxin sequence variation, transit peptide cleavage sites and post-translational modifications (PTMs) likely critical for venom lethality. A tube-gel format for electrophoresis (called GELFrEE) and solution isoelectric focusing were used for protein fractionation prior to LC-MS/MS analysis resulting in 131 protein identifications (18 more than bottom-up) and a total of 184 proteoforms characterized from 14 protein toxin families. Operating both GELFrEE and mass spectrometry to preserve non-covalent interactions generated detailed information about two of the largest venom glycoprotein complexes: the homodimeric l-amino acid oxidase (∼130 kDa) and the multichain toxin cobra venom factor (∼147 kDa). The l-amino acid oxidase complex exhibited two clusters of multiproteoform complexes corresponding to the presence of 5 or 6 N-glycans moieties, each consistent with a distribution of N-acetyl hexosamines. Employing top-down proteomics in both native and denaturing modes provides unprecedented characterization of venom proteoforms and their complexes. A precise molecular inventory of venom proteins will propel the study of snake toxin variation and the targeted development of new antivenoms or other biotherapeutics. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteomics for understanding miRNA biology.

PubMed

Huang, Tai-Chung; Pinto, Sneha M; Pandey, Akhilesh

2013-02-01

MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics and syndrome of Chinese medicine

PubMed Central

Lu, Chuan-Li; Qv, Xiao-Ying; Jiang, Jian-Guo

2010-01-01

Abstract Syndrome of Chinese medicine is an understanding of the regularity of disease occurrence and development and its performance of symptoms. Syndrome is the key to recognize diseases and the foundation to treat them. However, because of the complexity of the concept and the limitation of present investigations, the research of syndrome is hard to go further. Proteomics has been received extensive attention in the area of medical diagnosis and drug development. In the holistic and systemic context, proteomics have a convergence with traditional Chinese medicine (TCM) syndrome, which could overcome the one-sidedness and singleness of TCM and avoid the complication and tedious processes. Chinese medicine has a wealth of experience and proteomics has a substantial research potential, the integration of the two aspects will bring a great enhancement of our knowledge of disease. PMID:20874721

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

PubMed

Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

2016-01-01

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

Mass spectrometric identification of proteins in complex post-genomic projects. Soluble proteins of the metabolically versatile, denitrifying 'Aromatoleum' sp. strain EbN1.

PubMed

Hufnagel, Peter; Rabus, Ralf

2006-01-01

The rapidly developing proteomics technologies help to advance the global understanding of physiological and cellular processes. The lifestyle of a study organism determines the type and complexity of a given proteomic project. The complexity of this study is characterized by a broad collection of pathway-specific subproteomes, reflecting the metabolic versatility as well as the regulatory potential of the aromatic-degrading, denitrifying bacterium 'Aromatoleum' sp. strain EbN1. Differences in protein profiles were determined using a gel-based approach. Protein identification was based on a progressive application of MALDI-TOF-MS, MALDI-TOF-MS/MS and LC-ESI-MS/MS. This progression was result-driven and automated by software control. The identification rate was increased by the assembly of a project-specific list of background signals that was used for internal calibration of the MS spectra, and by the combination of two search engines using a dedicated MetaScoring algorithm. In total, intelligent bioinformatics could increase the identification yield from 53 to 70% of the analyzed 5,050 gel spots; a total of 556 different proteins were identified. MS identification was highly reproducible: most proteins were identified more than twice from parallel 2DE gels with an average sequence coverage of >50% and rather restrictive score thresholds (Mascot >or=95, ProFound >or=2.2, MetaScore >or=97). The MS technologies and bioinformatics tools that were implemented and integrated to handle this complex proteomic project are presented. In addition, we describe the basic principles and current developments of the applied technologies and provide an overview over the current state of microbial proteome research. Copyright (c) 2006 S. Karger AG, Basel.

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

iTRAQ Quantitative Proteomic Analysis of Vitreous from Patients with Retinal Detachment.

PubMed

Santos, Fátima Milhano; Gaspar, Leonor Mesquita; Ciordia, Sergio; Rocha, Ana Sílvia; Castro E Sousa, João Paulo; Paradela, Alberto; Passarinha, Luís António; Tomaz, Cândida Teixeira

2018-04-11

Rhegmatogenous retinal detachment (RRD) is a potentially blinding condition characterized by a physical separation between neurosensory retina and retinal pigment epithelium. Quantitative proteomics can help to understand the changes that occur at the cellular level during RRD, providing additional information about the molecular mechanisms underlying its pathogenesis. In the present study, iTRAQ labeling was combined with two-dimensional LC-ESI-MS/MS to find expression changes in the proteome of vitreous from patients with RRD when compared to control samples. A total of 150 proteins were found differentially expressed in the vitreous of patients with RRD, including 96 overexpressed and 54 underexpressed. Several overexpressed proteins, several such as glycolytic enzymes (fructose-bisphosphate aldolase A, gamma-enolase, and phosphoglycerate kinase 1), glucose transporters (GLUT-1), growth factors (metalloproteinase inhibitor 1), and serine protease inhibitors (plasminogen activator inhibitor 1) are regulated by HIF-1, which suggests that HIF-1 signaling pathway can be triggered in response to RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Nevertheless, the differentially expressed proteins found in this study suggest that different mechanisms are activated after RRD to promote the survival of retinal cells through complex cellular responses.

iTRAQ Quantitative Proteomic Analysis of Vitreous from Patients with Retinal Detachment

PubMed Central

Gaspar, Leonor Mesquita; Ciordia, Sergio; Rocha, Ana Sílvia; Castro e Sousa, João Paulo; Paradela, Alberto

2018-01-01

Rhegmatogenous retinal detachment (RRD) is a potentially blinding condition characterized by a physical separation between neurosensory retina and retinal pigment epithelium. Quantitative proteomics can help to understand the changes that occur at the cellular level during RRD, providing additional information about the molecular mechanisms underlying its pathogenesis. In the present study, iTRAQ labeling was combined with two-dimensional LC-ESI-MS/MS to find expression changes in the proteome of vitreous from patients with RRD when compared to control samples. A total of 150 proteins were found differentially expressed in the vitreous of patients with RRD, including 96 overexpressed and 54 underexpressed. Several overexpressed proteins, several such as glycolytic enzymes (fructose-bisphosphate aldolase A, gamma-enolase, and phosphoglycerate kinase 1), glucose transporters (GLUT-1), growth factors (metalloproteinase inhibitor 1), and serine protease inhibitors (plasminogen activator inhibitor 1) are regulated by HIF-1, which suggests that HIF-1 signaling pathway can be triggered in response to RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Nevertheless, the differentially expressed proteins found in this study suggest that different mechanisms are activated after RRD to promote the survival of retinal cells through complex cellular responses. PMID:29641463

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

PubMed

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

2018-02-01

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

Quantitative proteomic analysis reveals evolutionary divergence and species-specific peptides in the Alexandrium tamarense complex (Dinophyceae).

PubMed

Li, Cheng; Zhang, Yong; Xie, Zhang-Xian; He, Zhi-Ping; Lin, Lin; Wang, Da-Zhi

2013-06-28

The Alexandrium tamarense/catenella/fundyense complex is the major causative agent responsible for harmful algal blooms and paralytic shellfish poisoning around the world. However, taxonomy of the A. tamarense complex is contentious and the evolutionary relationships within the complex are unclear. This study compared protein profiles of the A. tamarense complex collected from different geographic regions using the two dimensional fluorescence difference gel electrophoresis (2-D DIGE) approach, and identified species-specific peptides using MALDI-TOF/TOF mass spectrometry. The results showed that three Alexandrium morphotypes presented significantly different protein expression patterns with about 30-40% shared proteins. However, ecotypes from different geographic regions within a species exhibited the same expression patterns, although a few proteins were altered in abundance. Several proteins, i.e. ribulose-1,5-bisphosphate carboxylase oxygenase form II, plastid protein NAP50, methionine S-adenosyltransferase, and peridinin-chlorophyll a-binding protein, were identified and presented different shift patterns in isoelectric point and/or molecular weight in the 2-D DIGE gels, indicating that amino acid mutation and/or posttranslational modification of these proteins had occurred. The species-specific peptide mass fingerprint and amino acid sequence of ribulose-1,5-bisphosphate carboxylase oxygenase were characterized in the A. tamarense complex, and amino acid substitution occurred among them. This study indicated that evolutionary divergence had occurred at the proteomic level in the A. tamarense complex, and that the species-specific peptides could be used as potential biomarkers to distinguish the three morphotypes. Scientific question: The Alexandrium tamarense/catenella/fundyense complex is the major causative agent responsible for harmful algal blooms and paralytic shellfish poisoning around the world. However, taxonomy of the A. tamarense complex is contentious and the evolutionary relationships within the complex are unclear, which has seriously impeded our understanding of Alexandrium-causing HABs and, consequently, the monitoring, mitigation and prevention. Technical significance: This study, for the first time, compared the global protein expression patterns of eight ecotypes from the A. tamarense complex and identified species-specific peptides using a quantitative proteomic approach combining 2-D DIGE and MALDI-TOF/TOF MS. This study demonstrated that the evolutionary divergence had occurred in the A. tamarense complex at the proteomic level, and the complex should be classified into three species, i.e. A. tamarense, A. catenella, and A. fundyense. Moreover, the species-specific peptide mass fingerprints could be used as potential biomarkers to distinguish the three morphotypes. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion*

PubMed Central

Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas

2016-01-01

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394

A unique proteomic profile on surface IgM ligation in unmutated chronic lymphocytic leukemia

PubMed Central

Perrot, Aurore; Pionneau, Cédric; Nadaud, Sophie; Davi, Frédéric; Leblond, Véronique; Jacob, Frédéric; Merle-Béral, Hélène; Herbrecht, Raoul; Béné, Marie-Christine; Gribben, John G.; Vallat, Laurent

2011-01-01

Chronic lymphocytic leukemia (CLL) is characterized by a highly variable clinical course with 2 extreme subsets: indolent, ZAP70− and mutated immunoglobulin heavy chain gene (M-CLL); and aggressive, ZAP70+ and unmutated immunoglobulin heavy chain (UM-CLL). Given the long-term suspicion of antigenic stimulation as a primum movens in the disease, the role of the B-cell receptor has been extensively studied in various experimental settings; albeit scarcely in a comparative dynamic proteomic approach. Here we use a quantitative 2-dimensional fluorescence difference gel electrophoresis technology to compare 48 proteomic profiles of the 2 CLL subsets before and after anti-IgM ligation. Differentially expressed proteins were subsequently identified by mass spectrometry. We show that unstimulated M- and UM-CLL cells display distinct proteomic profiles. Furthermore, anti-IgM stimulation induces a specific proteomic response, more pronounced in the more aggressive CLL. Statistical analyses demonstrate several significant protein variations according to stimulation conditions. Finally, we identify an intermediate form of M-CLL cells, with an indolent profile (ZAP70−) but sharing aggressive proteomic profiles alike UM-CLL cells. Collectively, this first quantitative and dynamic proteome analysis of CLL further dissects the complex molecular pathway after B-cell receptor stimulation and depicts distinct proteomic profiles, which could lead to novel molecular stratification of the disease. PMID:21602524

Mining Missing Membrane Proteins by High-pH Reverse Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry

PubMed Central

Kitata, Reta Birhanu; Dimayacyac-Esleta, Baby Rorielyn T.; Choong, Wai-Kok; Tsai, Chia-Feng; Lin, Tai-Du; Tsou, Chih-Chiang; Weng, Shao-Hsing; Chen, Yi-Ju; Yang, Pan-Chyr; Arco, Susan D.; Nesvizhskii, Alexey I.; Sung, Ting-Yi; Chen, Yu-Ju

2016-01-01

Despite significant efforts in the past decade towards complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still “missing proteins”. Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using non-small cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip pre-fractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue were incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring (MRM) using synthetic peptides, we provided additional evidences for 8 missing proteins including 7 with transmembrane helix domains (TMH). This study demonstrates that mining missing proteins focused on cancer membrane sub-proteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224. PMID:26202522

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

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.

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.

Chemical Proteomic Approaches Targeting Cancer Stem Cells: A Review of Current Literature.

PubMed

Jung, Hye Jin

2017-01-01

Cancer stem cells (CSCs) have been proposed as central drivers of tumor initiation, progression, recurrence, and therapeutic resistance. Therefore, identifying stem-like cells within cancers and understanding their properties is crucial for the development of effective anticancer therapies. Recently, chemical proteomics has become a powerful tool to efficiently determine protein networks responsible for CSC pathophysiology and comprehensively elucidate molecular mechanisms of drug action against CSCs. This review provides an overview of major methodologies utilized in chemical proteomic approaches. In addition, recent successful chemical proteomic applications targeting CSCs are highlighted. Future direction of potential CSC research by integrating chemical genomic and proteomic data obtained from a single biological sample of CSCs are also suggested in this review. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Head and neck cancer: proteomic advances and biomarker achievements.

PubMed

Rezende, Taia Maria Berto; de Souza Freire, Mirna; Franco, Octávio Luiz

2010-11-01

Tumors of the head and neck comprise an important neoplasia group, the incidence of which is increasing in many parts of the world. Recent advances in diagnostic and therapeutic techniques for these lesions have yielded novel molecular targets, uncovered signal pathway dominance, and advanced early cancer detection. Proteomics is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the analysis of different types of samples. The proteomic profiles of different types of cancer have been studied, and this has provided remarkable advances in cancer understanding. This review covers recent advances for head and neck cancer; it encompasses the risk factors, pathogenesis, proteomic tools that can help in understanding cancer, and new proteomic findings in this type of cancer. Copyright © 2010 American Cancer Society.

Integrated redox proteomics and metabolomics of mitochondria to identify mechanisms of cd toxicity.

PubMed

Go, Young-Mi; Roede, James R; Orr, Michael; Liang, Yongliang; Jones, Dean P

2014-05-01

Cadmium (Cd) exposure contributes to human diseases affecting liver, kidney, lung, and other organ systems, but mechanisms underlying the pleotropic nature of these toxicities are poorly understood. Cd accumulates in humans from dietary, environmental (including cigarette smoke), and occupational sources, and has a twenty-year biologic half-life. Our previous mouse and cell studies showed that environmental low-dose Cd exposure altered protein redox states resulting in stimulation of inflammatory signaling and disruption of the actin cytoskeleton system, suggesting that Cd could impact multiple mechanisms of disease. In the current study, we investigated the effects of acute Cd exposure on the redox proteome and metabolome of mouse liver mitochondria to gain insight into associated toxicological mechanisms and functions. We analyzed redox states of liver mitochondrial proteins by redox proteomics using isotope coded affinity tag (ICAT) combined mass spectrometry. Redox ICAT identified 2687 cysteine-containing peptides (peptidyl Cys) of which 1667 peptidyl Cys (657 proteins) were detected in both control and Cd-exposed samples. Of these, 46% (1247 peptidyl Cys, 547 proteins) were oxidized by Cd more than 1.5-fold relative to controls. Bioinformatics analysis using MetaCore software showed that Cd affected 86 pathways, including 24 Cys in proteins functioning in branched chain amino acid (BCAA) and 14 Cys in proteins functioning in fatty acid (acylcarnitine/carnitine) metabolism. Consistently, high-resolution metabolomics data showed that Cd treatment altered levels of BCAA and carnitine metabolites. Together, these results show that mitochondrial protein redox and metabolites are targets in Cd-induced hepatotoxicity. The results further indicate that redox proteomics and metabolomics can be used in an integrated systems approach to investigate complex disease mechanisms.

Combinatorial depletion analysis to assemble the network architecture of the SAGA and ADA chromatin remodeling complexes.

PubMed

Lee, Kenneth K; Sardiu, Mihaela E; Swanson, Selene K; Gilmore, Joshua M; Torok, Michael; Grant, Patrick A; Florens, Laurence; Workman, Jerry L; Washburn, Michael P

2011-07-05

Despite the availability of several large-scale proteomics studies aiming to identify protein interactions on a global scale, little is known about how proteins interact and are organized within macromolecular complexes. Here, we describe a technique that consists of a combination of biochemistry approaches, quantitative proteomics and computational methods using wild-type and deletion strains to investigate the organization of proteins within macromolecular protein complexes. We applied this technique to determine the organization of two well-studied complexes, Spt-Ada-Gcn5 histone acetyltransferase (SAGA) and ADA, for which no comprehensive high-resolution structures exist. This approach revealed that SAGA/ADA is composed of five distinct functional modules, which can persist separately. Furthermore, we identified a novel subunit of the ADA complex, termed Ahc2, and characterized Sgf29 as an ADA family protein present in all Gcn5 histone acetyltransferase complexes. Finally, we propose a model for the architecture of the SAGA and ADA complexes, which predicts novel functional associations within the SAGA complex and provides mechanistic insights into phenotypical observations in SAGA mutants.

Combinatorial depletion analysis to assemble the network architecture of the SAGA and ADA chromatin remodeling complexes

PubMed Central

Lee, Kenneth K; Sardiu, Mihaela E; Swanson, Selene K; Gilmore, Joshua M; Torok, Michael; Grant, Patrick A; Florens, Laurence; Workman, Jerry L; Washburn, Michael P

2011-01-01

Despite the availability of several large-scale proteomics studies aiming to identify protein interactions on a global scale, little is known about how proteins interact and are organized within macromolecular complexes. Here, we describe a technique that consists of a combination of biochemistry approaches, quantitative proteomics and computational methods using wild-type and deletion strains to investigate the organization of proteins within macromolecular protein complexes. We applied this technique to determine the organization of two well-studied complexes, Spt–Ada–Gcn5 histone acetyltransferase (SAGA) and ADA, for which no comprehensive high-resolution structures exist. This approach revealed that SAGA/ADA is composed of five distinct functional modules, which can persist separately. Furthermore, we identified a novel subunit of the ADA complex, termed Ahc2, and characterized Sgf29 as an ADA family protein present in all Gcn5 histone acetyltransferase complexes. Finally, we propose a model for the architecture of the SAGA and ADA complexes, which predicts novel functional associations within the SAGA complex and provides mechanistic insights into phenotypical observations in SAGA mutants. PMID:21734642

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

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.

Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

PubMed

Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

2004-01-01

The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

Molecular Profiles for Lung Cancer Pathogenesis and Detection in US Veterans

DTIC Science & Technology

2012-10-01

will be further strengthened via Multiple Reaction Monitoring ( MRM ) performed on the remaining samples by the Vanderbilt group. MRM using mass...proteomics detects all protein changes in the sample in an unfocused fashion, MRM is targeted and highly selective, allowing us to specifically look for...proteins of interest. To this end, we have generated a list of candidate proteins for MRM utilizing shotgun proteomic, mRNA array, and miRNA array

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics

PubMed Central

Bell, Alexander W.; Deutsch, Eric W.; Au, Catherine E.; Kearney, Robert E.; Beavis, Ron; Sechi, Salvatore; Nilsson, Tommy; Bergeron, John J.M.

2009-01-01

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics. PMID:19448641

Proteome Profiles of Outer Membrane Vesicles and Extracellular Matrix of Pseudomonas aeruginosa Biofilms.

PubMed

Couto, Narciso; Schooling, Sarah R; Dutcher, John R; Barber, Jill

2015-10-02

In the present work, two different proteomic platforms, gel-based and gel-free, were used to map the matrix and outer membrane vesicle exoproteomes of Pseudomonas aeruginosa PAO1 biofilms. These two proteomic strategies allowed us a confident identification of 207 and 327 proteins from enriched outer membrane vesicles and whole matrix isolated from biofilms. Because of the physicochemical characteristics of these subproteomes, the two strategies showed complementarity, and thus, the most comprehensive analysis of P. aeruginosa exoproteome to date was achieved. Under our conditions, outer membrane vesicles contribute approximately 20% of the whole matrix proteome, demonstrating that membrane vesicles are an important component of the matrix. The proteomic profiles were analyzed in terms of their biological context, namely, a biofilm. Accordingly relevant metabolic processes involved in cellular adaptation to the biofilm lifestyle as well as those related to P. aeruginosa virulence capabilities were a key feature of the analyses. The diversity of the matrix proteome corroborates the idea of high heterogeneity within the biofilm; cells can display different levels of metabolism and can adapt to local microenvironments making this proteomic analysis challenging. In addition to analyzing our own primary data, we extend the analysis to published data by other groups in order to deepen our understanding of the complexity inherent within biofilm populations.

Proteomics boosts translational and clinical microbiology.

PubMed

Del Chierico, F; Petrucca, A; Vernocchi, P; Bracaglia, G; Fiscarelli, E; Bernaschi, P; Muraca, M; Urbani, A; Putignani, L

2014-01-31

The application of proteomics to translational and clinical microbiology is one of the most advanced frontiers in the management and control of infectious diseases and in the understanding of complex microbial systems within human fluids and districts. This new approach aims at providing, by dedicated bioinformatic pipelines, a thorough description of pathogen proteomes and their interactions within the context of human host ecosystems, revolutionizing the vision of infectious diseases in biomedicine and approaching new viewpoints in both diagnostic and clinical management of the patient. Indeed, in the last few years, many laboratories have matured a series of advanced proteomic applications, aiming at providing individual proteome charts of pathogens, with respect to their morph and/or cell life stages, antimicrobial or antimycotic resistance profiling, epidemiological dispersion. Herein, we aim at reviewing the current state-of-the-art on proteomic protocols designed and set-up for translational and diagnostic microbiological purposes, from axenic pathogens' characterization to microbiota ecosystems' full description. The final goal is to describe applications of the most common MALDI-TOF MS platforms to advanced diagnostic issues related to emerging infections, increasing of fastidious bacteria, and generation of patient-tailored phylotypes. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. © 2013. Published by Elsevier B.V. All rights reserved.

Selected reaction monitoring mass spectrometry: a methodology overview.

PubMed

Ebhardt, H Alexander

2014-01-01

Moving past the discovery phase of proteomics, the term targeted proteomics combines multiple approaches investigating a certain set of proteins in more detail. One such targeted proteomics approach is the combination of liquid chromatography and selected or multiple reaction monitoring mass spectrometry (SRM, MRM). SRM-MS requires prior knowledge of the fragmentation pattern of peptides, as the presence of the analyte in a sample is determined by measuring the m/z values of predefined precursor and fragment ions. Using scheduled SRM-MS, many analytes can robustly be monitored allowing for high-throughput sample analysis of the same set of proteins over many conditions. In this chapter, fundaments of SRM-MS are explained as well as an optimized SRM pipeline from assay generation to data analyzed.

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

PubMed

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

2012-12-01

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

Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life

DOE PAGES

Xiong, Weili; Brown, Christopher T.; Morowitz, Michael J.; ...

2017-07-10

Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. But, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota). We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants’ gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for eachmore » of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We also identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. By applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production. Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.« less

Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life

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

Xiong, Weili; Brown, Christopher T.; Morowitz, Michael J.

Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. But, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota). We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants’ gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for eachmore » of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We also identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. By applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production. Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.« less

Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life.

PubMed

Xiong, Weili; Brown, Christopher T; Morowitz, Michael J; Banfield, Jillian F; Hettich, Robert L

2017-07-10

Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. However, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota). We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants' gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for each of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. Applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production. Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.

Slow histidine H/D exchange protocol for thermodynamic analysis of protein folding and stability using mass spectrometry.

PubMed

Tran, Duc T; Banerjee, Sambuddha; Alayash, Abdu I; Crumbliss, Alvin L; Fitzgerald, Michael C

2012-02-07

Described here is a mass spectrometry-based protocol to study the thermodynamic stability of proteins and protein-ligand complexes using the chemical denaturant dependence of the slow H/D exchange reaction of the imidazole C(2) proton in histidine side chains. The protocol is developed using several model protein systems including: ribonuclease (Rnase) A, myoglobin, bovine carbonic anhydrase (BCA) II, hemoglobin (Hb), and the hemoglobin-haptoglobin (Hb-Hp) protein complex. Folding free energies consistent with those previously determined by other more conventional techniques were obtained for the two-state folding proteins, Rnase A and myoglobin. The protocol successfully detected a previously observed partially unfolded intermediate stabilized in the BCA II folding/unfolding reaction, and it could be used to generate a K(d) value of 0.24 nM for the Hb-Hp complex. The compatibility of the protocol with conventional mass spectrometry-based proteomic sample preparation and analysis methods was also demonstrated in an experiment in which the protocol was used to detect the binding of zinc to superoxide dismutase in the yeast cell lysate sample. The yeast cell sample analyses also helped define the scope of the technique, which requires the presence of globally protected histidine residues in a protein's three-dimensional structure for successful application. © 2011 American Chemical Society

Development of a 45kpsi ultrahigh pressure liquid chromatography instrument for gradient separations of peptides using long microcapillary columns and sub-2μm particles.

PubMed

Grinias, Kaitlin M; Godinho, Justin M; Franklin, Edward G; Stobaugh, Jordan T; Jorgenson, James W

2016-10-21

Commercial chromatographic instrumentation for bottom-up proteomics is often inadequate to resolve the number of peptides in many samples. This has inspired a number of complex approaches to increase peak capacity, including various multidimensional approaches, and reliance on advancements in mass spectrometry. One-dimensional reversed phase separations are limited by the pressure capabilities of commercial instruments and prevent the realization of greater separation power in terms of speed and resolution inherent to smaller sorbents and ultrahigh pressure liquid chromatography. Many applications with complex samples could benefit from the increased separation performance of long capillary columns packed with sub-2μm sorbents. Here, we introduce a system that operates at a constant pressure and is capable of separations at pressures up to 45kpsi. The system consists of a commercially available capillary liquid chromatography instrument, for sample management and gradient creation, and is modified with a storage loop and isolated pneumatic amplifier pump for elevated separation pressure. The system's performance is assessed with a complex peptide mixture and a range of microcapillary columns packed with sub-2μm C18 particles. Copyright © 2016 Elsevier B.V. All rights reserved.

Virtual Labs in proteomics: new E-learning tools.

PubMed

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

2012-05-17

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

Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML database--Xindice.

PubMed

Li, Feng; Li, Maoyu; Xiao, Zhiqiang; Zhang, Pengfei; Li, Jianling; Chen, Zhuchu

2006-01-11

Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database. The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database. Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at http://www.xyproteomics.org/.

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

PubMed

Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

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.

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.

A Rapid and Reliable Method for Total Protein Extraction from Succulent Plants for Proteomic Analysis.

PubMed

Lledías, Fernando; Hernández, Felipe; Rivas, Viridiana; García-Mendoza, Abisaí; Cassab, Gladys I; Nieto-Sotelo, Jorge

2017-08-01

Crassulacean acid metabolism plants have some morphological features, such as succulent and reduced leaves, thick cuticles, and sunken stomata that help them prevent excessive water loss and irradiation. As molecular constituents of these morphological adaptations to xeric environments, succulent plants produce a set of specific compounds such as complex polysaccharides, pigments, waxes, and terpenoids, to name a few, in addition to uncharacterized proteases. Since all these compounds interfere with the analysis of proteins by electrophoretic techniques, preparation of high quality samples from these sources represents a real challenge. The absence of adequate protocols for protein extraction has restrained the study of this class of plants at the molecular level. Here, we present a rapid and reliable protocol that could be accomplished in 1 h and applied to a broad range of plants with reproducible results. We were able to obtain well-resolved SDS/PAGE protein patterns in extracts from different members of the subfamilies Agavoideae (Agave, Yucca, Manfreda, and Furcraea), Nolinoideae (Dasylirion and Beucarnea), and the Cactaceae family. This method is based on the differential solubility of contaminants and proteins in the presence of acetone and pH-altered solutions. We speculate about the role of saponins and high molecular weight carbohydrates to produce electrophoretic-compatible samples. A modification of the basic protocol allowed the analysis of samples by bidimensional electrophoresis (2DE) for proteomic analysis. Furostanol glycoside 26-O-β-glucosidase (an enzyme involved in steroid saponin synthesis) was successfully identified by mass spectrometry analysis and de novo sequencing of a 2DE spot from an Agave attenuata sample.

Platelet proteomics: from discovery to diagnosis.

PubMed

Looße, Christina; Swieringa, Frauke; Heemskerk, Johan W M; Sickmann, Albert; Lorenz, Christin

2018-05-22

Platelets are the smallest cells within the circulating blood with key roles in physiological haemostasis and pathological thrombosis regulated by the onset of activating/inhibiting processes via receptor responses and signalling cascades. Areas covered: Proteomics as well as genomic approaches have been fundamental in identifying and quantifying potential targets for future diagnostic strategies in the prevention of bleeding and thrombosis, and uncovering the complexity of platelet functions in health and disease. In this article, we provide a critical overview on current functional tests used in diagnostics and the future perspectives for platelet proteomics in clinical applications. Expert commentary: Proteomics represents a valuable tool for the identification of patients with diverse platelet associated defects. In-depth validation of identified biomarkers, e.g. receptors, signalling proteins, post-translational modifications, in large cohorts is decisive for translation into routine clinical diagnostics.

A-to-I RNA Editing Contributes to Proteomic Diversity in Cancer.

PubMed

Peng, Xinxin; Xu, Xiaoyan; Wang, Yumeng; Hawke, David H; Yu, Shuangxing; Han, Leng; Zhou, Zhicheng; Mojumdar, Kamalika; Jeong, Kang Jin; Labrie, Marilyne; Tsang, Yiu Huen; Zhang, Minying; Lu, Yiling; Hwu, Patrick; Scott, Kenneth L; Liang, Han; Mills, Gordon B

2018-05-14

Adenosine (A) to inosine (I) RNA editing introduces many nucleotide changes in cancer transcriptomes. However, due to the complexity of post-transcriptional regulation, the contribution of RNA editing to proteomic diversity in human cancers remains unclear. Here, we performed an integrated analysis of TCGA genomic data and CPTAC proteomic data. Despite limited site diversity, we demonstrate that A-to-I RNA editing contributes to proteomic diversity in breast cancer through changes in amino acid sequences. We validate the presence of editing events at both RNA and protein levels. The edited COPA protein increases proliferation, migration, and invasion of cancer cells in vitro. Our study suggests an important contribution of A-to-I RNA editing to protein diversity in cancer and highlights its translational potential. Copyright © 2018 Elsevier Inc. All rights reserved.

Quantitative targeted proteomics for understanding the blood-brain barrier: towards pharmacoproteomics.

PubMed

Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya

2014-06-01

The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.

Hospitalized Premature Infants Are Colonized by Related Bacterial Strains with Distinct Proteomic Profiles

PubMed Central

Xiong, Weili; Olm, Matthew R.; Thomas, Brian C.; Baker, Robyn; Firek, Brian; Morowitz, Michael J.; Hettich, Robert L.

2018-01-01

ABSTRACT During the first weeks of life, microbial colonization of the gut impacts human immune system maturation and other developmental processes. In premature infants, aberrant colonization has been implicated in the onset of necrotizing enterocolitis (NEC), a life-threatening intestinal disease. To study the premature infant gut colonization process, genome-resolved metagenomics was conducted on 343 fecal samples collected during the first 3 months of life from 35 premature infants housed in a neonatal intensive care unit, 14 of whom developed NEC, and metaproteomic measurements were made on 87 samples. Microbial community composition and proteomic profiles remained relatively stable on the time scale of a week, but the proteome was more variable. Although genetically similar organisms colonized many infants, most infants were colonized by distinct strains with metabolic profiles that could be distinguished using metaproteomics. Microbiome composition correlated with infant, antibiotics administration, and NEC diagnosis. Communities were found to cluster into seven primary types, and community type switched within infants, sometimes multiple times. Interestingly, some communities sampled from the same infant at subsequent time points clustered with those of other infants. In some cases, switches preceded onset of NEC; however, no species or community type could account for NEC across the majority of infants. In addition to a correlation of protein abundances with organism replication rates, we found that organism proteomes correlated with overall community composition. Thus, this genome-resolved proteomics study demonstrated that the contributions of individual organisms to microbiome development depend on microbial community context. PMID:29636439

Multidimensional electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) for quantitative analysis of the proteome and phosphoproteome in clinical and biomedical research.

PubMed

Loroch, Stefan; Schommartz, Tim; Brune, Wolfram; Zahedi, René Peiman; Sickmann, Albert

2015-05-01

Quantitative proteomics and phosphoproteomics have become key disciplines in understanding cellular processes. Fundamental research can be done using cell culture providing researchers with virtually infinite sample amounts. In contrast, clinical, pre-clinical and biomedical research is often restricted to minute sample amounts and requires an efficient analysis with only micrograms of protein. To address this issue, we generated a highly sensitive workflow for combined LC-MS-based quantitative proteomics and phosphoproteomics by refining an ERLIC-based 2D phosphoproteomics workflow into an ERLIC-based 3D workflow covering the global proteome as well. The resulting 3D strategy was successfully used for an in-depth quantitative analysis of both, the proteome and the phosphoproteome of murine cytomegalovirus-infected mouse fibroblasts, a model system for host cell manipulation by a virus. In a 2-plex SILAC experiment with 150 μg of a tryptic digest per condition, the 3D strategy enabled the quantification of ~75% more proteins and even ~134% more peptides compared to the 2D strategy. Additionally, we could quantify ~50% more phosphoproteins by non-phosphorylated peptides, concurrently yielding insights into changes on the levels of protein expression and phosphorylation. Beside its sensitivity, our novel three-dimensional ERLIC-strategy has the potential for semi-automated sample processing rendering it a suitable future perspective for clinical, pre-clinical and biomedical research. Copyright © 2015. Published by Elsevier B.V.

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

PubMed

Kamada, Haruhiko

2012-01-01

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

Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

PubMed

Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

2017-01-01

No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as proteomics. The proposed nested governance structure is comprised of (a) scientists, (b) ethicists, and (c) scholars in the nascent field of "ethics-of-ethics", and aims to cultivate a robust social proteome for personalized medicine. Ostrom often noted that such nested governance designs offer assurance that political power embedded in innovation processes is distributed evenly and is not concentrated disproportionately in a single overbearing stakeholder or person. We agree with this assessment and conclude by underscoring the synergistic value of social and biological proteomes to realize the full potentials of proteomics science for personalized medicine in psychiatry in the present era of Big Data.

Global Reprogramming of Host SUMOylation during Influenza Virus Infection

PubMed Central

Domingues, Patricia; Golebiowski, Filip; Tatham, Michael H.; Lopes, Antonio M.; Taggart, Aislynn; Hay, Ronald T.; Hale, Benjamin G.

2015-01-01

Summary Dynamic nuclear SUMO modifications play essential roles in orchestrating cellular responses to proteotoxic stress, DNA damage, and DNA virus infection. Here, we describe a non-canonical host SUMOylation response to the nuclear-replicating RNA pathogen, influenza virus, and identify viral RNA polymerase activity as a major contributor to SUMO proteome remodeling. Using quantitative proteomics to compare stress-induced SUMOylation responses, we reveal that influenza virus infection triggers unique re-targeting of SUMO to 63 host proteins involved in transcription, mRNA processing, RNA quality control, and DNA damage repair. This is paralleled by widespread host deSUMOylation. Depletion screening identified ten virus-induced SUMO targets as potential antiviral factors, including C18orf25 and the SMC5/6 and PAF1 complexes. Mechanistic studies further uncovered a role for SUMOylation of the PAF1 complex component, parafibromin (CDC73), in potentiating antiviral gene expression. Our global characterization of influenza virus-triggered SUMO redistribution provides a proteomic resource to understand host nuclear SUMOylation responses to infection. PMID:26549460

Vintage venoms: proteomic and pharmacological stability of snake venoms stored for up to eight decades.

PubMed

Jesupret, Clémence; Baumann, Kate; Jackson, Timothy N W; Ali, Syed Abid; Yang, Daryl C; Greisman, Laura; Kern, Larissa; Steuten, Jessica; Jouiaei, Mahdokht; Casewell, Nicholas R; Undheim, Eivind A B; Koludarov, Ivan; Debono, Jordan; Low, Dolyce H W; Rossi, Sarah; Panagides, Nadya; Winter, Kelly; Ignjatovic, Vera; Summerhayes, Robyn; Jones, Alun; Nouwens, Amanda; Dunstan, Nathan; Hodgson, Wayne C; Winkel, Kenneth D; Monagle, Paul; Fry, Bryan Grieg

2014-06-13

For over a century, venom samples from wild snakes have been collected and stored around the world. However, the quality of storage conditions for "vintage" venoms has rarely been assessed. The goal of this study was to determine whether such historical venom samples are still biochemically and pharmacologically viable for research purposes, or if new sample efforts are needed. In total, 52 samples spanning 5 genera and 13 species with regional variants of some species (e.g., 14 different populations of Notechis scutatus) were analysed by a combined proteomic and pharmacological approach to determine protein structural stability and bioactivity. When venoms were not exposed to air during storage, the proteomic results were virtually indistinguishable from that of fresh venom and bioactivity was equivalent or only slightly reduced. By contrast, a sample of Acanthophis antarcticus venom that was exposed to air (due to a loss of integrity of the rubber stopper) suffered significant degradation as evidenced by the proteomics profile. Interestingly, the neurotoxicity of this sample was nearly the same as fresh venom, indicating that degradation may have occurred in the free N- or C-terminus chains of the proteins, rather than at the tips of loops where the functional residues are located. These results suggest that these and other vintage venom collections may be of continuing value in toxin research. This is particularly important as many snake species worldwide are declining due to habitat destruction or modification. For some venoms (such as N. scutatus from Babel Island, Flinders Island, King Island and St. Francis Island) these were the first analyses ever conducted and these vintage samples may represent the only venom ever collected from these unique island forms of tiger snakes. Such vintage venoms may therefore represent the last remaining stocks of some local populations and thus are precious resources. These venoms also have significant historical value as the Oxyuranus venoms analysed include samples from the first coastal taipan (Oxyuranus scutellatus) collected for antivenom production (the snake that killed the collector Kevin Budden), as well as samples from the first Oxyuranus microlepidotus specimen collected after the species' rediscovery in 1976. These results demonstrate that with proper storage techniques, venom samples can retain structural and pharmacological stability. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Detachable strong cation exchange monolith, integrated with capillary zone electrophoresis and coupled with pH gradient elution, produces improved sensitivity and numbers of peptide identifications during bottom-up analysis of complex proteomes.

PubMed

Zhang, Zhenbin; Yan, Xiaojing; Sun, Liangliang; Zhu, Guijie; Dovichi, Norman J

2015-04-21

A detachable sulfonate-silica hybrid strong cation-exchange monolith was synthesized in a fused silica capillary, and used for solid phase extraction with online pH gradient elution during capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) proteomic analysis. Tryptic digests were prepared in 50 mM formic acid and loaded onto the strong cation-exchange monolith. Fractions were eluted using a series of buffers with lower concentration but higher pH values than the 50 mM formic acid background electrolyte. This combination of elution and background electrolytes results in both sample stacking and formation of a dynamic pH junction and allows use of relatively large elution buffer volumes while maintaining reasonable peak efficiency and resolution. A series of five pH bumps were applied to elute E. coli tryptic peptides from the monolith, followed by analysis using CZE coupled to an LTQ-Orbitrap Velos mass spectrometer; 799 protein groups and 3381 peptides were identified from 50 ng of the digest in a 2.5 h analysis, which approaches the identification rate for this organism that was obtained with an Orbitrap Fusion. We attribute the improved numbers of peptide and protein identifications to the efficient fractionation by the online pH gradient elution, which decreased the complexity of the sample in each elution step and improved the signal intensity of low abundance peptides. We also performed a comparative analysis using a nanoACQUITY UltraPerformance LCH system. Similar numbers of protein and peptide identifications were produced by the two methods. Protein identifications showed significant overlap between the two methods, whereas peptide identifications were complementary.

Mitochondrial Proteome Studies in Seeds during Germination

PubMed Central

Czarna, Malgorzata; Kolodziejczak, Marta; Janska, Hanna

2016-01-01

Seed germination is considered to be one of the most critical phases in the plant life cycle, establishing the next generation of a plant species. It is an energy-demanding process that requires functioning mitochondria. One of the earliest events of seed germination is progressive development of structurally simple and metabolically quiescent promitochondria into fully active and cristae-containing mitochondria, known as mitochondrial biogenesis. This is a complex and tightly regulated process, which is accompanied by sequential and dynamic gene expression, protein synthesis, and post-translational modifications. The aim of this review is to give a comprehensive summary of seed mitochondrial proteome studies during germination of various plant model organisms. We describe different gel-based and gel-free proteomic approaches used to characterize mitochondrial proteomes of germinating seeds as well as challenges and limitations of these proteomic studies. Furthermore, the dynamic changes in the abundance of the mitochondrial proteomes of germinating seeds are illustrated, highlighting numerous mitochondrial proteins involved in respiration, tricarboxycylic acid (TCA) cycle, metabolism, import, and stress response as potentially important for seed germination. We then review seed mitochondrial protein carbonylation, phosphorylation, and S-nitrosylation as well as discuss the possible link between these post-translational modifications (PTMs) and the regulation of seed germination. PMID:28248229

Comparative Network-Based Recovery Analysis and Proteomic Profiling of Neurological Changes in Valproic Acid-Treated Mice

PubMed Central

2013-01-01

Despite its prominence for characterization of complex mixtures, LC–MS/MS frequently fails to identify many proteins. Network-based analysis methods, based on protein–protein interaction networks (PPINs), biological pathways, and protein complexes, are useful for recovering non-detected proteins, thereby enhancing analytical resolution. However, network-based analysis methods do come in varied flavors for which the respective efficacies are largely unknown. We compare the recovery performance and functional insights from three distinct instances of PPIN-based approaches, viz., Proteomics Expansion Pipeline (PEP), Functional Class Scoring (FCS), and Maxlink, in a test scenario of valproic acid (VPA)-treated mice. We find that the most comprehensive functional insights, as well as best non-detected protein recovery performance, are derived from FCS utilizing real biological complexes. This outstrips other network-based methods such as Maxlink or Proteomics Expansion Pipeline (PEP). From FCS, we identified known biological complexes involved in epigenetic modifications, neuronal system development, and cytoskeletal rearrangements. This is congruent with the observed phenotype where adult mice showed an increase in dendritic branching to allow the rewiring of visual cortical circuitry and an improvement in their visual acuity when tested behaviorally. In addition, PEP also identified a novel complex, comprising YWHAB, NR1, NR2B, ACTB, and TJP1, which is functionally related to the observed phenotype. Although our results suggest different network analysis methods can produce different results, on the whole, the findings are mutually supportive. More critically, the non-overlapping information each provides can provide greater holistic understanding of complex phenotypes. PMID:23557376

Cold and Heat Stress Diversely Alter Both Cauliflower Respiration and Distinct Mitochondrial Proteins Including OXPHOS Components and Matrix Enzymes

PubMed Central

Rurek, Michał; Czołpińska, Magdalena; Pawłowski, Tomasz Andrzej; Krzesiński, Włodzimierz; Spiżewski, Tomasz

2018-01-01

Complex proteomic and physiological approaches for studying cold and heat stress responses in plant mitochondria are still limited. Variations in the mitochondrial proteome of cauliflower (Brassica oleracea var. botrytis) curds after cold and heat and after stress recovery were assayed by two-dimensional polyacrylamide gel electrophoresis (2D PAGE) in relation to mRNA abundance and respiratory parameters. Quantitative analysis of the mitochondrial proteome revealed numerous stress-affected protein spots. In cold, major downregulations in the level of photorespiratory enzymes, porine isoforms, oxidative phosphorylation (OXPHOS) and some low-abundant proteins were observed. In contrast, carbohydrate metabolism enzymes, heat-shock proteins, translation, protein import, and OXPHOS components were involved in heat response and recovery. Several transcriptomic and metabolic regulation mechanisms are also suggested. Cauliflower plants appeared less susceptible to heat; closed stomata in heat stress resulted in moderate photosynthetic, but only minor respiratory impairments, however, photosystem II performance was unaffected. Decreased photorespiration corresponded with proteomic alterations in cold. Our results show that cold and heat stress not only operate in diverse modes (exemplified by cold-specific accumulation of some heat shock proteins), but exert some associations at molecular and physiological levels. This implies a more complex model of action of investigated stresses on plant mitochondria. PMID:29547512

A Proteome Translocation Response to Complex Desert Stress Environments in Perennial Phragmites Sympatric Ecotypes with Contrasting Water Availability.

PubMed

Li, Li; Chen, Xiaodan; Shi, Lu; Wang, Chuanjing; Fu, Bing; Qiu, Tianhang; Cui, Suxia

2017-01-01

After a long-term adaptation to desert environment, the perennial aquatic plant Phragmites communis has evolved a desert-dune ecotype. The desert-dune ecotype (DR) of Phragmites communis showed significant differences in water activity and protein distribution compared to its sympatric swamp ecotype (SR). Many proteins that were located in the soluble fraction of SR translocated to the insoluble fraction of DR, suggesting that membrane-associated proteins were greatly reinforced in DR. The unknown phenomenon in plant stress physiology was defined as a proteome translocation response. Quantitative 2D-DIGE technology highlighted these 'bound' proteins in DR. Fifty-eight kinds of proteins were identified as candidates of the translocated proteome in Phragmites . The majority were chloroplast proteins. Unexpectedly, Rubisco was the most abundant protein sequestered by DR. Rubisco activase, various chaperons and 2-cysteine peroxiredoxin were major components in the translocation response. Conformational change was assumed to be the main reason for the Rubisco translocation due to no primary sequence difference between DR and SR. The addition of reductant in extraction process partially reversed the translocation response, implying that intracellular redox status plays a role in the translocation response of the proteome. The finding emphasizes the realistic significance of the membrane-association of biomolecule for plant long-term adaptation to complex stress conditions.

Metaproteomics Identifies the Protein Machinery Involved in Metal and Radionuclide Reduction in Subsurface Microbiomes and Elucidates Mechanisms and U(VI) Reduction Immobilization

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

Pfiffner, Susan M.; Löffler, Frank; Ritalahti, Kirsti

The overall goal for this funded project was to develop and exploit environmental metaproteomics tools to identify biomarkers for monitoring microbial activity affecting U speciation at U-contaminated sites, correlate metaproteomics profiles with geochemical parameters and U(VI) reduction activity (or lack thereof), elucidate mechanisms contributing to U(VI) reduction, and provide remediation project managers with additional information to make science-based site management decisions for achieving cleanup goals more efficiently. Although significant progress has been made in elucidating the microbiology contribution to metal and radionuclide reduction, the cellular components, pathway(s), and mechanisms involved in U trans-formation remain poorly understood. Recent advances in (meta)proteomicsmore » technology enable detailed studies of complex samples, including environmental samples, which differ between sites and even show considerable variability within the same site (e.g., the Oak Ridge IFRC site). Additionally, site-specific geochemical conditions affect microbial activity and function, suggesting generalized assessment and interpretations may not suffice. This research effort integrated current understanding of the microbiology and biochemistry of U(VI) reduction and capitalize on advances in proteomics technology made over the past few years. Field-related analyses used Oak Ridge IFRC field ground water samples from locations where slow-release substrate biostimulation has been implemented to accelerate in situ U(VI) reduction rates. Our overarching hypothesis was that the metabolic signature in environmental samples, as deciphered by the metaproteome measurements, would show a relationship with U(VI) reduction activity. Since metaproteomic and metagenomic characterizations were computationally challenging and time-consuming, we used a tiered approach that combines database mining, controlled laboratory studies, U(VI) reduction activity measurements, phylogenetic analyses, and gene expression studies to support the metaproteomics characterizations. Growth experiments of target microorganisms (Anaeromyxobacter, Shewanella, Geobacter) revealed tremendous respiratory versatility, as evidenced by the ability to utilize a range of electron donors (e.g. acetate, hydrogen, pyruvate, lactate, succinate, formate) and electron acceptors (e.g. nitrate, fumarate, halogenated phenols, ferric iron, nitrous oxide, etc.). In particular, the dissimilatory metabolic reduction of metals, including radionuclides, by target microorganisms spurred interest for in situ bioremediation of contaminated soils and sediments. Distinct c-type cytochrome expression patterns were observed in target microorganisms grown with the different electron acceptors. For each target microorganism, the core proteome covered almost all metabolic pathways represented by their corresponding pan-proteomes. Unique proteins were detected for each target microorganism, and their expression and possible functionalities were linked to specific growth conditions through proteomics measurements. Optimization of the proteomic tools included in-depth comprehensive metagenomic and metaproteomic analyses on a limited number of samples. The optimized metaproteomic analyses were then applied to Oak Ridge IFRC field samples from the slow-release substrate biostimulation. Metaproteomic analysis and pathway mapping results demonstrated the distinct effects of metal and non-metal growth conditions on the proteome expression. With these metaproteomic tools, we identified which previously hypothetical metabolic pathways were active during the analyzed time points of the slow release substrate biostimulation. Thus, we demonstrated the utility of these tools for site assessment, efficient implementation of bioremediation and long-term monitoring. This research of detailed protein analysis linked with metal reduction activity did (1) show that c-type cytochrome isoforms, previously associated with radionuclide reduction activity, are suitable biomarkers, (2) identify new biomarker targets for site assessment and bioremediation monitoring, and (3) provide new information about specific proteins and mechanisms involved in U(VI) reduction and immobilization. This expanded metagenomic and metaproteomic toolbox contributed to implementing science-driven site management with broad benefits to the DOE mission.« less

Potential spoilage yeasts in winery environments: Characterization and proteomic analysis of Trigonopsis cantarellii.

PubMed

Portugal, Cauré; Pinto, Luís; Ribeiro, Miguel; Tenorio, Carmen; Igrejas, Gilberto; Ruiz-Larrea, Fernanda

2015-10-01

Wine microbiota is complex and includes a wide diversity of yeast species. Few of them are able to survive under the restrictive conditions of dry red wines. In our study we detected and identified seven yeast species of the order Saccharomycetales that can be considered potential spoilers of wines due to physiological traits such as acidogenic metabolism and off-odor generation: Arthroascus schoenii, Candida ishiwadae, Meyerozyma guilliermondii, Pichia holstii, Pichia manshurica, Trigonopsis cantarellii, and Trigonopsis variabilis. Based on the prevalence of T. cantarellii isolates in the wine samples of our study, we further characterized this species, determined molecular and phenotypic features, and performed a proteomic analysis to identify differentially expressed proteins at mid-exponential growth phase in the presence of ethanol in the culture broth. This yeast species is shown to be able to grow in the presence of ethanol by expressing heat shock proteins (Hsp70, Hsp71) and a DNA damage-related protein (Rad24), and to be able to confer spoilage characteristics on wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Protein 3-Nitrotyrosine in Complex Biological Samples: Quantification by High-Pressure Liquid Chromatography/Electrochemical Detection and Emergence of Proteomic Approaches for Unbiased Identification of Modification Sites

PubMed Central

Nuriel, Tal; Deeb, Ruba S.; Hajjar, David P.; Gross, Steven S.

2008-01-01

Nitration of tyrosine residues by nitric oxide (NO)-derived species results in the accumulation of 3-nitrotyrosine in proteins, a hallmark of nitrosative stress in cells and tissues. Tyrosine nitration is recognized as one of the multiple signaling modalities used by NO-derived species for the regulation of protein structure and function in health and disease. Various methods have been described for the quantification of protein 3-nitrotyrosine residues, and several strategies have been presented toward the goal of proteome-wide identification of protein tyrosine modification sites. This chapter details a useful protocol for the quantification of 3-nitrotyrosine in cells and tissues using high-pressure liquid chromatography with electrochemical detection. Additionally, this chapter describes a novel biotin-tagging strategy for specific enrichment of 3-nitrotyrosine-containing peptides. Application of this strategy, in conjunction with high-throughput MS/MS-based peptide sequencing, is anticipated to fuel efforts in developing comprehensive inventories of nitrosative stress-induced protein-tyrosine modification sites in cells and tissues. PMID:18554526

A large scale Plasmodium vivax- Saimiri boliviensis trophozoite-schizont transition proteome

PubMed Central

Lapp, Stacey A.; Barnwell, John W.; Galinski, Mary R.

2017-01-01

Plasmodium vivax is a complex protozoan parasite with over 6,500 genes and stage-specific differential expression. Much of the unique biology of this pathogen remains unknown, including how it modifies and restructures the host reticulocyte. Using a recently published P. vivax reference genome, we report the proteome from two biological replicates of infected Saimiri boliviensis host reticulocytes undergoing transition from the late trophozoite to early schizont stages. Using five database search engines, we identified a total of 2000 P. vivax and 3487 S. boliviensis proteins, making this the most comprehensive P. vivax proteome to date. PlasmoDB GO-term enrichment analysis of proteins identified at least twice by a search engine highlighted core metabolic processes and molecular functions such as glycolysis, translation and protein folding, cell components such as ribosomes, proteasomes and the Golgi apparatus, and a number of vesicle and trafficking related clusters. Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 enriched functional annotation clusters of S. boliviensis proteins highlighted vesicle and trafficking-related clusters, elements of the cytoskeleton, oxidative processes and response to oxidative stress, macromolecular complexes such as the proteasome and ribosome, metabolism, translation, and cell death. Host and parasite proteins potentially involved in cell adhesion were also identified. Over 25% of the P. vivax proteins have no functional annotation; this group includes 45 VIR members of the large PIR family. A number of host and pathogen proteins contained highly oxidized or nitrated residues, extending prior trophozoite-enriched stage observations from S. boliviensis infections, and supporting the possibility of oxidative stress in relation to the disease. This proteome significantly expands the size and complexity of the known P. vivax and Saimiri host iRBC proteomes, and provides in-depth data that will be valuable for ongoing research on this parasite’s biology and pathogenesis. PMID:28829774

A cost-effective method to get insight into the peritoneal dialysate effluent proteome.

PubMed

Araújo, J E; Jorge, S; Teixeira E Costa, F; Ramos, A; Lodeiro, C; Santos, H M; Capelo, J L

2016-08-11

Protein depletion with acetonitrile and protein equalization with dithiothreitol have been assessed with success as proteomics tools for getting insight into the peritoneal dialysate effluent proteome. The methods proposed are cost-effective, fast and easy of handling, and they match the criteria of analytical minimalism: low sample volume and low reagent consumption. Using two-dimensional gel electrophoresis and peptide mass fingerprinting, a total of 72 unique proteins were identified. Acetonitrile depletes de PDE proteome from high-abundance proteins, such as albumin, and enriches the sample in apolipo-like proteins. Dithiothreitol equalizes the PDE proteome by diminishing the levels of albumin and enriching the extract in immunoglobulin-like proteins. The annotation per gene ontology term reveals the same biological paths being affected for patients undergoing peritoneal dialysis, namely that the largest number of proteins lost through peritoneal dialysate are extracellular proteins involved in regulation processes through binding. Renal failure is a growing problem worldwide, and particularly in Europe where the population is getting older. Up-to-date there is a focus of interest in peritoneal dialysis (PD), as it provides a better quality of life and autonomy of the patients than other renal replacement therapies such as haemodialysis. However, PD can only be used during a short period of years, as the peritoneum lost its permeability through time. Therefore to make a breakthrough in PD and consequently contribute to better healthcare system it is urgent to find a group of biomarkers of peritoneum degradation. Here we report on two cost-effective methods for protein depletion in peritoneal dialysate effluent (PDE). The use of ACN and DTT over PDE to deplete high abundant proteins or to equalize the concentration of proteins, respectively, performs well and with similar protein profiles than when the same chemicals are used in human plasma samples. ACN depletes de PDE proteome from large proteins, such as albumin, and enriches the sample in apolipoproteins. DTT equalizes the PDE proteome by diminishing the levels of large proteins such as albumin and enriching the extract in immunoglobulins. Although the number and type of proteins identified are different, the annotation per gene ontology term reveals the same biological paths being affected for patients undergoing peritoneal dialysate. Thus, the largest number of proteins lost through peritoneal dialysate belongs to the group of extracellular proteins involved in regulation processes through binding. As for the searching of biomarkers, DTT seems to be the most promising of the two methods because acts as an equalizer and it allows interrogating more proteins in the same sample.

Wheat proteomics: proteome modulation and abiotic stress acclimation

PubMed Central

Komatsu, Setsuko; Kamal, Abu H. M.; Hossain, Zahed

2014-01-01

Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput “Omics” techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance. PMID:25538718

Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes.

PubMed

Ko, Jina; Bhagwat, Neha; Yee, Stephanie S; Ortiz, Natalia; Sahmoud, Amine; Black, Taylor; Aiello, Nicole M; McKenzie, Lydie; O'Hara, Mark; Redlinger, Colleen; Romeo, Janae; Carpenter, Erica L; Stanger, Ben Z; Issadore, David

2017-11-28

Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of exosomal biomarkers is confounded by substantial heterogeneity between patients and within a tumor itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated exosomes from healthy and diseased murine and clinical cohorts, profiled the RNA cargo inside of these exosomes, and applied a machine learning algorithm to generate predictive panels that could identify samples derived from heterogeneous cancer-bearing individuals. Using this approach, we classified cancer and precancer mice from healthy controls, as well as pancreatic cancer patients from healthy controls, in blinded studies.

Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.

PubMed

Severi, Leda; Losi, Lorena; Fonda, Sergio; Taddia, Laura; Gozzi, Gaia; Marverti, Gaetano; Magni, Fulvio; Chinello, Clizia; Stella, Martina; Sheouli, Jalid; Braicu, Elena I; Genovese, Filippo; Lauriola, Angela; Marraccini, Chiara; Gualandi, Alessandra; D'Arca, Domenico; Ferrari, Stefania; Costi, Maria P

2018-01-01

Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.