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.

Role of the visual experience-dependent nascent proteome in neuronal plasticity

PubMed Central

Liu, Han-Hsuan; McClatchy, Daniel B; Schiapparelli, Lucio; Shen, Wanhua; Yates, John R

2018-01-01

Experience-dependent synaptic plasticity refines brain circuits during development. To identify novel protein synthesis-dependent mechanisms contributing to experience-dependent plasticity, we conducted a quantitative proteomic screen of the nascent proteome in response to visual experience in Xenopus optic tectum using bio-orthogonal metabolic labeling (BONCAT). We identified 83 differentially synthesized candidate plasticity proteins (CPPs). The CPPs form strongly interconnected networks and are annotated to a variety of biological functions, including RNA splicing, protein translation, and chromatin remodeling. Functional analysis of select CPPs revealed the requirement for eukaryotic initiation factor three subunit A (eIF3A), fused in sarcoma (FUS), and ribosomal protein s17 (RPS17) in experience-dependent structural plasticity in tectal neurons and behavioral plasticity in tadpoles. These results demonstrate that the nascent proteome is dynamic in response to visual experience and that de novo synthesis of machinery that regulates RNA splicing and protein translation is required for experience-dependent plasticity. PMID:29412139

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

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.

Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

PubMed

Schaab, Christoph; Geiger, Tamar; Stoehr, Gabriele; Cox, Juergen; Mann, Matthias

2012-03-01

MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database scores. The information contained in MaxQB, including high resolution fragment spectra, is accessible to the community via a user-friendly web interface at http://www.biochem.mpg.de/maxqb.

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

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

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

2009-08-15

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

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

PubMed Central

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

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins. PMID:19181660

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.

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

PubMed

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

2012-05-01

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

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

PubMed Central

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

2012-01-01

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

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

PubMed Central

Röst, Hannes L.; Liu, Yansheng; D’Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C.; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-01-01

Large scale, quantitative proteomic studies have become essential for the analysis of clinical cohorts, large perturbation experiments and systems biology studies. While next-generation mass spectrometric techniques such as SWATH-MS have substantially increased throughput and reproducibility, ensuring consistent quantification of thousands of peptide analytes across multiple LC-MS/MS runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we have developed the TRIC software which utilizes fragment ion data to perform cross-run alignment, consistent peak-picking and quantification for high throughput targeted proteomics. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate peak elution information from all LC-MS/MS runs acquired in a study. When compared to state-of-the-art SWATH-MS data analysis, the algorithm was able to reduce the identification error by more than 3-fold at constant recall, while correcting for highly non-linear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem (iPS) cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups and substantially increased the quantitative completeness and biological information in the data, providing insights into protein dynamics of iPS cells. Overall, this study demonstrates the importance of consistent quantification in highly challenging experimental setups, and proposes an algorithm to automate this task, constituting the last missing piece in a pipeline for automated analysis of massively parallel targeted proteomics datasets. PMID:27479329

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.

Toward improved peptide feature detection in quantitative proteomics using stable isotope labeling.

PubMed

Nilse, Lars; Sigloch, Florian Christoph; Biniossek, Martin L; Schilling, Oliver

2015-08-01

Reliable detection of peptides in LC-MS data is a key algorithmic step in the analysis of quantitative proteomics experiments. While highly abundant peptides can be detected reliably by most modern software tools, there is much less agreement on medium and low-intensity peptides in a sample. The choice of software tools can have a big impact on the quantification of proteins, especially for proteins that appear in lower concentrations. However, in many experiments, it is precisely this region of less abundant but substantially regulated proteins that holds the biggest potential for discoveries. This is particularly true for discovery proteomics in the pharmacological sector with a specific interest in key regulatory proteins. In this viewpoint article, we discuss how the development of novel software algorithms allows us to study this region of the proteome with increased confidence. Reliable results are one of many aspects to be considered when deciding on a bioinformatics software platform. Deployment into existing IT infrastructures, compatibility with other software packages, scalability, automation, flexibility, and support need to be considered and are briefly addressed in this viewpoint article. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

A Comparison of Protein Extraction Methods Suitable for Gel-Based Proteomic Studies of Aphid Proteins

PubMed Central

Cilia, M.; Fish, T.; Yang, X.; Mclaughlin, M.; Thannhauser, T. W.

2009-01-01

Protein extraction methods can vary widely in reproducibility and in representation of the total proteome, yet there are limited data comparing protein isolation methods. The methodical comparison of protein isolation methods is the first critical step for proteomic studies. To address this, we compared three methods for isolation, purification, and solubilization of insect proteins. The aphid Schizaphis graminum, an agricultural pest, was the source of insect tissue. Proteins were extracted using TCA in acetone (TCA-acetone), phenol, or multi-detergents in a chaotrope solution. Extracted proteins were solubilized in a multiple chaotrope solution and examined using 1-D and 2-D electrophoresis and compared directly using 2-D Difference Gel Electrophoresis (2-D DIGE). Mass spectrometry was used to identify proteins from each extraction type. We were unable to ascribe the differences in the proteins extracted to particular physical characteristics, cell location, or biological function. The TCA-acetone extraction yielded the greatest amount of protein from aphid tissues. Each extraction method isolated a unique subset of the aphid proteome. The TCA-acetone method was explored further for its quantitative reliability using 2-D DIGE. Principal component analysis showed that little of the variation in the data was a result of technical issues, thus demonstrating that the TCA-acetone extraction is a reliable method for preparing aphid proteins for a quantitative proteomics experiment. These data suggest that although the TCA-acetone method is a suitable method for quantitative aphid proteomics, a combination of extraction approaches is recommended for increasing proteome coverage when using gel-based separation techniques. PMID:19721822

IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT.

PubMed

Arntzen, Magnus Ø; Koehler, Christian J; Barsnes, Harald; Berven, Frode S; Treumann, Achim; Thiede, Bernd

2011-02-04

Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.

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

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

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

2009-08-15

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

Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition

PubMed Central

Hart-Smith, Gene; Reis, Rodrigo S.; Waterhouse, Peter M.; Wilkins, Marc R.

2017-01-01

Quantitative proteomics strategies – which are playing important roles in the expanding field of plant molecular systems biology – are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) – referred to as TDA/DDA – to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA experiments only (33.0 ± 2.6% versus 8.0 ± 2.7%, respectively; p = 0.011). These results were observed together with uncompromised broad-scale MS/MS data collection in TDA/DDA experiments relative to DDA experiments. Using our observations we provide guidelines for TDA/DDA method design for quantitative plant proteomics studies, and suggest that TDA/DDA is a broadly underutilized proteomics data acquisition strategy. PMID:29021799

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

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

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

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

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

PubMed

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

2016-01-01

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

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

PubMed

Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-10-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

PubMed Central

Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-01-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

The Application of SILAC Mouse in Human Body Fluid Proteomics Analysis Reveals Protein Patterns Associated with IgA Nephropathy.

PubMed

Zhao, Shilin; Li, Rongxia; Cai, Xiaofan; Chen, Wanjia; Li, Qingrun; Xing, Tao; Zhu, Wenjie; Chen, Y Eugene; Zeng, Rong; Deng, Yueyi

2013-01-01

Body fluid proteome is the most informative proteome from a medical viewpoint. But the lack of accurate quantitation method for complicated body fluid limited its application in disease research and biomarker discovery. To address this problem, we introduced a novel strategy, in which SILAC-labeled mouse serum was used as internal standard for human serum and urine proteome analysis. The SILAC-labeled mouse serum was mixed with human serum and urine, and multidimensional separation coupled with tandem mass spectrometry (IEF-LC-MS/MS) analysis was performed. The shared peptides between two species were quantified by their SILAC pairs, and the human-only peptides were quantified by mouse peptides with coelution. The comparison for the results from two replicate experiments indicated the high repeatability of our strategy. Then the urine from Immunoglobulin A nephropathy patients treated and untreated was compared by this quantitation strategy. Fifty-three peptides were found to be significantly changed between two groups, including both known diagnostic markers for IgAN and novel candidates, such as Complement C3, Albumin, VDBP, ApoA,1 and IGFBP7. In conclusion, we have developed a practical and accurate quantitation strategy for comparison of complicated human body fluid proteome. The results from such strategy could provide potential disease-related biomarkers for evaluation of treatment.

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

PubMed

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

2013-03-01

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

PatternLab for proteomics 4.0: A one-stop shop for analyzing shotgun proteomic data

PubMed Central

Carvalho, Paulo C; Lima, Diogo B; Leprevost, Felipe V; Santos, Marlon D M; Fischer, Juliana S G; Aquino, Priscila F; Moresco, James J; Yates, John R; Barbosa, Valmir C

2017-01-01

PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for analyzing shotgun proteomic data. PatternLab contains modules for formatting sequence databases, performing peptide spectrum matching, statistically filtering and organizing shotgun proteomic data, extracting quantitative information from label-free and chemically labeled data, performing statistics for differential proteomics, displaying results in a variety of graphical formats, performing similarity-driven studies with de novo sequencing data, analyzing time-course experiments, and helping with the understanding of the biological significance of data in the light of the Gene Ontology. Here we describe PatternLab for proteomics 4.0, which closely knits together all of these modules in a self-contained environment, covering the principal aspects of proteomic data analysis as a freely available and easily installable software package. All updates to PatternLab, as well as all new features added to it, have been tested over the years on millions of mass spectra. PMID:26658470

Quantitative Molecular Phenotyping of Gill Remodeling in a Cichlid Fish Responding to Salinity Stress*

PubMed Central

Kültz, Dietmar; Li, Johnathon; Gardell, Alison; Sacchi, Romina

2013-01-01

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change. PMID:24065692

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.

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

Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates.

PubMed

Schwämmle, Veit; León, Ileana Rodríguez; Jensen, Ole Nørregaard

2013-09-06

Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant changes on the peptide level, for example, in phospho-proteomics experiments. In order to assess the extent of this problem and the implications for large-scale proteome analysis, we investigated and optimized the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. We applied three tools, including standard t test, moderated t test, also known as limma, and rank products for the detection of significantly changing features in simulated and experimental proteomics data sets with missing values. The rank product method was improved to work with data sets containing missing values. Extensive analysis of simulated and experimental data sets revealed that the performance of the statistical analysis tools depended on simple properties of the data sets. High-confidence results were obtained by using the limma and rank products methods for analyses of triplicate data sets that exhibited more than 1000 features and more than 50% missing values. The maximum number of differentially represented features was identified by using limma and rank products methods in a complementary manner. We therefore recommend combined usage of these methods as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling and mass spectrometry experiments and should be applicable to large data sets of any type. An R script that implements the improved rank products algorithm and the combined analysis is available.

Involvement of GABA Transporters in Atropine-Treated Myopic Retina As Revealed by iTRAQ Quantitative Proteomics

PubMed Central

2015-01-01

Atropine, a muscarinic antagonist, is known to inhibit myopia progression in several animal models and humans. However, the mode of action is not established yet. In this study, we compared quantitative iTRAQ proteomic analysis in the retinas collected from control and lens-induced myopic (LIM) mouse eyes treated with atropine. The myopic group received a (−15D) spectacle lens over the right eye on postnatal day 10 with or without atropine eye drops starting on postnatal day 24. Axial length was measured by optical low coherence interferometry (OLCI), AC-Master, and refraction was measured by automated infrared photorefractor at postnatal 24, 38, and 52 days. Retinal tissue samples were pooled from six eyes for each group. The experiments were repeated twice, and technical replicates were also performed for liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis. MetaCore was used to perform protein profiling for pathway analysis. We identified a total of 3882 unique proteins with <1% FDR by analyzing the samples in replicates for two independent experiments. This is the largest number of mouse retina proteome reported to date. Thirty proteins were found to be up-regulated (ratio for myopia/control > global mean ratio + 1 standard deviation), and 28 proteins were down-regulated (ratio for myopia/control < global mean ratio - 1 standard deviation) in myopic eyes as compared with control retinas. Pathway analysis using MetaCore revealed regulation of γ-aminobutyric acid (GABA) levels in the myopic eyes. Detailed analysis of the quantitative proteomics data showed that the levels of GABA transporter 1 (GAT-1) were elevated in myopic retina and significantly reduced after atropine treatment. These results were further validated with immunohistochemistry and Western blot analysis. In conclusion, this study provides a comprehensive quantitative proteomic analysis of atropine-treated mouse retina and suggests the involvement of GABAergic signaling in the antimyopic effects of atropine in mouse eyes. The GABAergic transmission in the neural retina plays a pivotal role in the maintenance of axial eye growth in mammals. PMID:25211393

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

[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.

The Response of the Root Proteome to the Synthetic Strigolactone GR24 in Arabidopsis*

PubMed Central

Walton, Alan; Stes, Elisabeth; Goeminne, Geert; Braem, Lukas; Vuylsteke, Marnik; Matthys, Cedrick; De Cuyper, Carolien; Staes, An; Vandenbussche, Jonathan; Boyer, François-Didier; Vanholme, Ruben; Fromentin, Justine; Boerjan, Wout; Gevaert, Kris; Goormachtig, Sofie

2016-01-01

Strigolactones are plant metabolites that act as phytohormones and rhizosphere signals. Whereas most research on unraveling the action mechanisms of strigolactones is focused on plant shoots, we investigated proteome adaptation during strigolactone signaling in the roots of Arabidopsis thaliana. Through large-scale, time-resolved, and quantitative proteomics, the impact of the strigolactone analog rac-GR24 was elucidated on the root proteome of the wild type and the signaling mutant more axillary growth 2 (max2). Our study revealed a clear MAX2-dependent rac-GR24 response: an increase in abundance of enzymes involved in flavonol biosynthesis, which was reduced in the max2–1 mutant. Mass spectrometry-driven metabolite profiling and thin-layer chromatography experiments demonstrated that these changes in protein expression lead to the accumulation of specific flavonols. Moreover, quantitative RT-PCR revealed that the flavonol-related protein expression profile was caused by rac-GR24-induced changes in transcript levels of the corresponding genes. This induction of flavonol production was shown to be activated by the two pure enantiomers that together make up rac-GR24. Finally, our data provide much needed clues concerning the multiple roles played by MAX2 in the roots and a comprehensive view of the rac-GR24-induced response in the root proteome. PMID:27317401

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

PubMed

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

2012-02-01

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

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

PubMed

Röst, Hannes L; Liu, Yansheng; D'Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

Condenser: a statistical aggregation tool for multi-sample quantitative proteomic data from Matrix Science Mascot Distiller™.

PubMed

Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan

2014-05-30

We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Simulated linear test applied to quantitative proteomics.

PubMed

Pham, T V; Jimenez, C R

2016-09-01

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

Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

PubMed Central

Van, Phu T.; Schmid, Amy K.; King, Nichole L.; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T.; Goo, Young-Ah; Deutsch, Eric W.; Reiss, David J.; Mallick, Parag; Baliga, Nitin S.

2009-01-01

The relatively small numbers of proteins and fewer possible posttranslational modifications in microbes provides a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a Peptide Atlas (PA) for 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636,000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has helped highlight plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics. PMID:18652504

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

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.

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.

A tutorial in displaying mass spectrometry-based proteomic data using heat maps.

PubMed

Key, Melissa

2012-01-01

Data visualization plays a critical role in interpreting experimental results of proteomic experiments. Heat maps are particularly useful for this task, as they allow us to find quantitative patterns across proteins and biological samples simultaneously. The quality of a heat map can be vastly improved by understanding the options available to display and organize the data in the heat map. This tutorial illustrates how to optimize heat maps for proteomics data by incorporating known characteristics of the data into the image. First, the concepts used to guide the creating of heat maps are demonstrated. Then, these concepts are applied to two types of analysis: visualizing spectral features across biological samples, and presenting the results of tests of statistical significance. For all examples we provide details of computer code in the open-source statistical programming language R, which can be used for biologists and clinicians with little statistical background. Heat maps are a useful tool for presenting quantitative proteomic data organized in a matrix format. Understanding and optimizing the parameters used to create the heat map can vastly improve both the appearance and the interoperation of heat map data.

Analysis of Reproducibility of Proteome Coverage and Quantitation Using Isobaric Mass Tags (iTRAQ and TMT).

PubMed

Casey, Tammy M; Khan, Javed M; Bringans, Scott D; Koudelka, Tomas; Takle, Pari S; Downs, Rachael A; Livk, Andreja; Syme, Robert A; Tan, Kar-Chun; Lipscombe, Richard J

2017-02-03

This study aimed to compare the depth and reproducibility of total proteome and differentially expressed protein coverage in technical duplicates and triplicates using iTRAQ 4-plex, iTRAQ 8-plex, and TMT 6-plex reagents. The analysis was undertaken because comprehensive comparisons of isobaric mass tag reproducibility have not been widely reported in the literature. The highest number of proteins was identified with 4-plex, followed by 8-plex and then 6-plex reagents. Quantitative analyses revealed that more differentially expressed proteins were identified with 4-plex reagents than 8-plex reagents and 6-plex reagents. Replicate reproducibility was determined to be ≥69% for technical duplicates and ≥57% for technical triplicates. The results indicate that running an 8-plex or 6-plex experiment instead of a 4-plex experiment resulted in 26 or 39% fewer protein identifications, respectively. When 4-plex spectra were searched with three software tools-ProteinPilot, Mascot, and Proteome Discoverer-the highest number of protein identifications were obtained with Mascot. The analysis of negative controls demonstrated the importance of running experiments as replicates. Overall, this study demonstrates the advantages of using iTRAQ 4-plex reagents over iTRAQ 8-plex and TMT 6-plex reagents, provides estimates of technical duplicate and triplicate reproducibility, and emphasizes the value of running replicate samples.

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage.

PubMed

Van, Phu T; Schmid, Amy K; King, Nichole L; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T; Goo, Young Ah; Deutsch, Eric W; Reiss, David J; Mallick, Parag; Baliga, Nitin S

2008-09-01

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.

Quantitative proteomics to study carbapenem resistance in Acinetobacter baumannii

PubMed Central

Tiwari, Vishvanath; Tiwari, Monalisa

2014-01-01

Acinetobacter baumannii is an opportunistic pathogen causing pneumonia, respiratory infections and urinary tract infections. The prevalence of this lethal pathogen increases gradually in the clinical setup where it can grow on artificial surfaces, utilize ethanol as a carbon source. Moreover it resists desiccation. Carbapenems, a β-lactam, are the most commonly prescribed drugs against A. baumannii. Resistance against carbapenem has emerged in Acinetobacter baumannii which can create significant health problems and is responsible for high morbidity and mortality. With the development of quantitative proteomics, a considerable progress has been made in the study of carbapenem resistance of Acinetobacter baumannii. Recent updates showed that quantitative proteomics has now emerged as an important tool to understand the carbapenem resistance mechanism in Acinetobacter baumannii. Present review also highlights the complementary nature of different quantitative proteomic methods used to study carbapenem resistance and suggests to combine multiple proteomic methods for understanding the response to antibiotics by Acinetobacter baumannii. PMID:25309531

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.

Liquid Chromatography-Mass Spectrometry-based Quantitative Proteomics

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

Xie, Fang; Liu, Tao; Qian, Weijun

2011-07-22

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

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments*

PubMed Central

Searle, Brian C.; Egertson, Jarrett D.; Bollinger, James G.; Stergachis, Andrew B.; MacCoss, Michael J.

2015-01-01

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature. PMID:26100116

Final Report: Proteomic study of brassinosteroid responses in Arabidopsis

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

Wang, Zhiyong; Burlingame, Alma

2017-11-29

The steroid hormone brassinosteroid (BR) is a major growth-promoting phytohormone. The specific aim of the current project is to identify BR-regulated proteins and characterize their functions in various aspects of plant growth, development, and adaptation. Our research has significantly advanced our understanding of how BR signal is transduced from the receptor at the cell surface to changes of nuclear gene expression and other cellular responses such as vesicle trafficking, as well as developmental transitions such as seed germination and flowering. We have also developed effective proteomic methods for quantitative analysis of protein phosphorylation and for identification of glycosylated proteins. Throughmore » this DOE funding, we have performed several proteomic experiments and made major discoveries.« less

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

PubMed

Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

2017-11-01

P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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.

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.

Endogenous protein "barcode" for data validation and normalization in quantitative MS analysis.

PubMed

Lee, Wooram; Lazar, Iulia M

2014-07-01

Quantitative proteomic experiments with mass spectrometry detection are typically conducted by using stable isotope labeling and label-free quantitation approaches. Proteins with housekeeping functions and stable expression level such actin, tubulin, and glyceraldehyde-3-phosphate dehydrogenase are frequently used as endogenous controls. Recent studies have shown that the expression level of such common housekeeping proteins is, in fact, dependent on various factors such as cell type, cell cycle, or disease status and can change in response to a biochemical stimulation. The interference of such phenomena can, therefore, substantially compromise their use for data validation, alter the interpretation of results, and lead to erroneous conclusions. In this work, we advance the concept of a protein "barcode" for data normalization and validation in quantitative proteomic experiments. The barcode comprises a novel set of proteins that was generated from cell cycle experiments performed with MCF7, an estrogen receptor positive breast cancer cell line, and MCF10A, a nontumorigenic immortalized breast cell line. The protein set was selected from a list of ~3700 proteins identified in different cellular subfractions and cell cycle stages of MCF7/MCF10A cells, based on the stability of spectral count data generated with an LTQ ion trap mass spectrometer. A total of 11 proteins qualified as endogenous standards for the nuclear and 62 for the cytoplasmic barcode, respectively. The validation of the protein sets was performed with a complementary SKBR3/Her2+ cell line.

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.

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

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

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

2012-01-01

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

PROTICdb: a web-based application to store, track, query, and compare plant proteome data.

PubMed

Ferry-Dumazet, Hélène; Houel, Gwenn; Montalent, Pierre; Moreau, Luc; Langella, Olivier; Negroni, Luc; Vincent, Delphine; Lalanne, Céline; de Daruvar, Antoine; Plomion, Christophe; Zivy, Michel; Joets, Johann

2005-05-01

PROTICdb is a web-based application, mainly designed to store and analyze plant proteome data obtained by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS). The purposes of PROTICdb are (i) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements, and (ii) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of post-translational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs of image analysis and MS identification software, or by filling web forms. 2-D PAGE annotated maps can be displayed, queried, and compared through a graphical interface. Links to external databases are also available. Quantitative data can be easily exported in a tabulated format for statistical analyses. PROTICdb is based on the Oracle or the PostgreSQL Database Management System and is freely available upon request at the following URL: http://moulon.inra.fr/ bioinfo/PROTICdb.

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.

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.

Quantitative Proteomic Profiles of Androgen Receptor Signaling in the Liver of Fathead Minnows Pimephalus promelas

EPA Science Inventory

Androgenic chemicals are present in the environment at concentrations that impair reproductive processes in fish. The objective of this experiment was to identify proteins altered by an androgen receptor agonist (17â-trenbolone) and antagonist (flutamide) in the liver. Female fa...

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

PubMed

Van Oudenhove, Laurence; Devreese, Bart

2013-06-01

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

Statistical issues in quality control of proteomic analyses: good experimental design and planning.

PubMed

Cairns, David A

2011-03-01

Quality control is becoming increasingly important in proteomic investigations as experiments become more multivariate and quantitative. Quality control applies to all stages of an investigation and statistics can play a key role. In this review, the role of statistical ideas in the design and planning of an investigation is described. This involves the design of unbiased experiments using key concepts from statistical experimental design, the understanding of the biological and analytical variation in a system using variance components analysis and the determination of a required sample size to perform a statistically powerful investigation. These concepts are described through simple examples and an example data set from a 2-D DIGE pilot experiment. Each of these concepts can prove useful in producing better and more reproducible data. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields.

PubMed

Kuzniar, Arnold; Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A Peter M; Demmers, Jeroen; Lebbink, Joyce H G; Kanaar, Roland

2017-01-01

The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture.

Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields

PubMed Central

Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A. Peter M.; Demmers, Jeroen; Lebbink, Joyce H. G.; Kanaar, Roland

2017-01-01

The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture. PMID:28234898

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

Inhibition of glycogen phosphorylation induces changes in cellular proteome and signaling pathways in MIA pancreatic cancer cells

PubMed Central

Ma, Danjun; Wang, Jiarui; Zhao, Yingchun; Lee, Wai-Nang Paul; Xiao, Jing; Go, Vay Liang W.; Wang, Qi; Recker, Robert; Xiao, Gary Guishan

2011-01-01

Objectives Novel quantitative proteomic approaches were used to study the effects of inhibition of glycogen phosphorylase on proteome and signaling pathways in MIA PaCa-2 pancreatic cancer cells. Methods We performed quantitative proteomic analysis in MIA PaCa-2 cancer cells treated with a stratified dose of CP-320626 (25 μM, 50 μM and 100 μM). The effect of metabolic inhibition on cellular protein turnover dynamics was also studied using the modified SILAC method (mSILAC). Results A total of twenty-two protein spots and four phosphoprotein spots were quantitatively analyzed. We found that dynamic expression of total proteins and phosphoproteins was significantly changed in MIA PaCa-2 cells treated with an incremental dose of CP-320626. Functional analyses suggested that most of the proteins differentially expressed were in the pathways of MAPK/ERK and TNF-α/NF-κB. Conclusions Signaling pathways and metabolic pathways share many common cofactors and substrates forming an extended metabolic network. The restriction of substrate through one pathway such as inhibition of glycogen phosphorylation induces pervasive metabolomic and proteomic changes manifested in protein synthesis, breakdown and post-translational modification of signaling molecules. Our results suggest that quantitative proteomic is an important approach to understand the interaction between metabolism and signaling pathways. PMID:22158071

Quantitative proteome profile of water deficit stress responses in eastern cottonwood ( Populus deltoides) leaves

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

Abraham, Paul E.; Garcia, Benjamin J.; Gunter, Lee E.

Drought stress is a recurring feature of world climate and the single most important factor influencing agricultural yield worldwide. Plants display highly variable, species-specific responses to drought and these responses are multifaceted, requiring physiological and morphological changes influenced by genetic and molecular mechanisms. Moreover, the reproducibility of water deficit studies is very cumbersome, which significantly impedes research on drought tolerance, because how a plant responds is highly influenced by the timing, duration, and intensity of the water deficit. Despite progress in the identification of drought-related mechanisms in many plants, the molecular basis of drought resistance remains to be fully understoodmore » in trees, particularly in poplar species because their wide geographic distribution results in varying tolerances to drought. Herein, we aimed to better understand this complex phenomenon in eastern cottonwood ( Populus deltoides) by performing a detailed contrast of the proteome changes between two different water deficit experiments to identify functional intersections and divergences in proteome responses. We investigated plants subjected to cyclic water deficit and compared these responses to plants subjected to prolonged acute water deficit. In total, we identified 108,012 peptide sequences across both experiments that provided insight into the quantitative state of 22,737 Populus gene models and 8,199 functional protein groups in response to drought. Together, these datasets provide the most comprehensive insight into proteome drought responses in poplar to date and a direct proteome comparison between short period dehydration shock and cyclic, post-drought re-watering. Altogether, this investigation provides novel insights into drought avoidance mechanisms that are distinct from progressive drought stress. Additionally, we identified proteins that have been associated as drought-relevant in previous studies. Importantly, we highlight the RD26 transcription factor as a gene regulated at both the transcript and protein level, regardless of species and drought condition, and, thus, represents a key, universal drought marker for Populus species.« less

Quantitative proteome profile of water deficit stress responses in eastern cottonwood ( Populus deltoides) leaves

DOE PAGES

Abraham, Paul E.; Garcia, Benjamin J.; Gunter, Lee E.; ...

2018-02-15

Drought stress is a recurring feature of world climate and the single most important factor influencing agricultural yield worldwide. Plants display highly variable, species-specific responses to drought and these responses are multifaceted, requiring physiological and morphological changes influenced by genetic and molecular mechanisms. Moreover, the reproducibility of water deficit studies is very cumbersome, which significantly impedes research on drought tolerance, because how a plant responds is highly influenced by the timing, duration, and intensity of the water deficit. Despite progress in the identification of drought-related mechanisms in many plants, the molecular basis of drought resistance remains to be fully understoodmore » in trees, particularly in poplar species because their wide geographic distribution results in varying tolerances to drought. Herein, we aimed to better understand this complex phenomenon in eastern cottonwood ( Populus deltoides) by performing a detailed contrast of the proteome changes between two different water deficit experiments to identify functional intersections and divergences in proteome responses. We investigated plants subjected to cyclic water deficit and compared these responses to plants subjected to prolonged acute water deficit. In total, we identified 108,012 peptide sequences across both experiments that provided insight into the quantitative state of 22,737 Populus gene models and 8,199 functional protein groups in response to drought. Together, these datasets provide the most comprehensive insight into proteome drought responses in poplar to date and a direct proteome comparison between short period dehydration shock and cyclic, post-drought re-watering. Altogether, this investigation provides novel insights into drought avoidance mechanisms that are distinct from progressive drought stress. Additionally, we identified proteins that have been associated as drought-relevant in previous studies. Importantly, we highlight the RD26 transcription factor as a gene regulated at both the transcript and protein level, regardless of species and drought condition, and, thus, represents a key, universal drought marker for Populus species.« less

ProteoSign: an end-user online differential proteomics statistical analysis platform.

PubMed

Efstathiou, Georgios; Antonakis, Andreas N; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Divanach, Peter; Trudgian, David C; Thomas, Benjamin; Papanikolaou, Nikolas; Aivaliotis, Michalis; Acuto, Oreste; Iliopoulos, Ioannis

2017-07-03

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed Central

Lavallée-Adam, Mathieu

2017-01-01

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

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

PubMed

MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J

2010-04-01

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

A draft map of the mouse pluripotent stem cell spatial proteome

PubMed Central

Christoforou, Andy; Mulvey, Claire M.; Breckels, Lisa M.; Geladaki, Aikaterini; Hurrell, Tracey; Hayward, Penelope C.; Naake, Thomas; Gatto, Laurent; Viner, Rosa; Arias, Alfonso Martinez; Lilley, Kathryn S.

2016-01-01

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. PMID:26754106

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

PubMed Central

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

2012-01-01

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

Quantitative proteomic characterization of the lung extracellular matrix in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis.

PubMed

Åhrman, Emma; Hallgren, Oskar; Malmström, Lars; Hedström, Ulf; Malmström, Anders; Bjermer, Leif; Zhou, Xiao-Hong; Westergren-Thorsson, Gunilla; Malmström, Johan

2018-03-01

Remodeling of the extracellular matrix (ECM) is a common feature in lung diseases such as chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). Here, we applied a sequential tissue extraction strategy to describe disease-specific remodeling of human lung tissue in disease, using end-stages of COPD and IPF. Our strategy was based on quantitative comparison of the disease proteomes, with specific focus on the matrisome, using data-independent acquisition and targeted data analysis (SWATH-MS). Our work provides an in-depth proteomic characterization of human lung tissue during impaired tissue remodeling. In addition, we show important quantitative and qualitative effects of the solubility of matrisome proteins. COPD was characterized by a disease-specific increase in ECM regulators, metalloproteinase inhibitor 3 (TIMP3) and matrix metalloproteinase 28 (MMP-28), whereas for IPF, impairment in cell adhesion proteins, such as collagen VI and laminins, was most prominent. For both diseases, we identified increased levels of proteins involved in the regulation of endopeptidase activity, with several proteins belonging to the serpin family. The established human lung quantitative proteome inventory and the construction of a tissue-specific protein assay library provides a resource for future quantitative proteomic analyses of human lung tissues. We present a sequential tissue extraction strategy to determine changes in extractability of matrisome proteins in end-stage COPD and IPF compared to healthy control tissue. Extensive quantitative analysis of the proteome changes of the disease states revealed altered solubility of matrisome proteins involved in ECM regulators and cell-ECM communication. The results highlight disease-specific remodeling mechanisms associated with COPD and IPF. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative proteomics reveals a role of JAZ7 in plant defense response to Pseudomonas syringae DC3000.

PubMed

Zhang, Tong; Meng, Li; Kong, Wenwen; Yin, Zepeng; Wang, Yang; Schneider, Jacqueline D; Chen, Sixue

2018-03-20

Jasmonate ZIM-domain (JAZ) proteins are key transcriptional repressors regulating various biological processes. Although many studies have studied JAZ proteins by genetic and biochemical analyses, little is known about JAZ7-associated global protein networks and how JAZ7 contributes to bacterial pathogen defense. In this study, we aim to fill this knowledge gap by conducting unbiased large-scale quantitative proteomics using tandem mass tags (TMT). We compared the proteomes of a JAZ7 knock-out line, a JAZ7 overexpression line, as well as the wild type Arabidopsis plants in the presence and absence of Pseudomonas syringae DC3000 infection. Both pairwise comparison and multi-factor analysis of variance reveal that differential proteins are enriched in biological processes such as primary and secondary metabolism, redox regulation, and response to stress. The differential regulation in these pathways may account for the alterations in plant size, redox homeostasis and accumulation of glucosinolates. In addition, possible interplay between genotype and environment is suggested as the abundance of seven proteins is influenced by the interaction of the two factors. Collectively, we demonstrate a role of JAZ7 in pathogen defense and provide a list of proteins that are uniquely responsive to genetic disruption, pathogen infection, or the interaction between genotypes and environmental factors. We report proteomic changes as a result of genetic perturbation of JAZ7, and the contribution of JAZ7 in plant immunity. Specifically, the similarity between the proteomes of a JAZ7 knockout mutant and the wild type plants confirmed the functional redundancy of JAZs. In contrast, JAZ7 overexpression plants were much different, and proteomic analysis of the JAZ7 overexpression plants under Pst DC3000 infection revealed that JAZ7 may regulate plant immunity via ROS modulation, energy balance and glucosinolate biosynthesis. Multiple variate analysis for this two-factor proteomics experiment suggests that protein abundance is determined by genotype, environment and the interaction between them. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-01-29

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

The PROTICdb database for 2-DE proteomics.

PubMed

Langella, Olivier; Zivy, Michel; Joets, Johann

2007-01-01

PROTICdb is a web-based database mainly designed to store and analyze plant proteome data obtained by 2D polyacrylamide gel electrophoresis (2D PAGE) and mass spectrometry (MS). The goals of PROTICdb are (1) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements; and (2) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of posttranslational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs from Mélanie, PDQuest, IM2d, ImageMaster(tm) 2D Platinum v5.0, Progenesis, Sequest, MS-Fit, and Mascot software, or by filling in web forms (experimental design and methods). 2D PAGE-annotated maps can be displayed, queried, and compared through the GelBrowser. Quantitative data can be easily exported in a tabulated format for statistical analyses with any third-party software. PROTICdb is based on the Oracle or the PostgreSQLDataBase Management System (DBMS) and is freely available upon request at http://cms.moulon.inra.fr/content/view/14/44/.

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

PubMed

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

2014-03-07

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

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

DOE PAGES

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

2018-03-09

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

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

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

Mass Spectrometry Data Collection in Parallel at Multiple Core Facilities Operating TripleTOF 5600 and Orbitrap Elite/Velos Pro/Q Exactive Mass Spectrometers

PubMed Central

Jones, K.; Kim, K.; Patel, B.; Kelsen, S.; Braverman, A.; Swinton, D.; Gafken, P.; Jones, L.; Lane, W.; Neveu, J.; Leung, H.; Shaffer, S.; Leszyk, J.; Stanley, B.; Fox, T.; Stanley, A.; Yeung, Anthony

2013-01-01

Proteomic research can benefit from simultaneous access to multiple cutting-edge mass spectrometers. 18 core facilities responded to our investigators seeking service through the ABRF Discussion Forum. Five of the facilities selected completed four plasma proteomics experiments as routine fee-for-service. Each biological experiment entailed an iTRAQ 4-plex proteome comparison of immunodepleted plasma provided as 30 labeled-peptide fractions. Identical samples were analyzed by two AB SCIEX TripleTOF 5600 and three Thermo Orbitrap (Elite/Velos Pro/Q Exactive) instruments. 480 LC-MS/MS runs delivered >250 GB of data over two months. We compare herein routine service analyses of three peptide fractions of different peptide abundance. Data files from each instrument were studied to develop optimal analysis parameters to compare with default parameters in Mascot Distiller 2.4, ProteinPilot 4.5 beta, AB Sciex MS Data Converter 1.3 beta, and Proteome Discover 1.3. Peak-picking for TripleTOFs was best by ProteinPilot 4.5 beta while Mascot Distiller and Proteome Discoverer were comparable for the Orbitraps. We compared protein identification and quantitation in SwissProt 2012_07 database by Mascot Server 2.4.01 versus ProteinPilot. By all search methods, more proteins, up to two fold, were identified using the Q Exactive than others. Q Exactive excelled also at the number of unique significant peptide ion sequences. However, software-dependent impact on subsequent interpretation, due to peptide modifications, can be critical. These findings may have special implications for iTRAQ plasma proteomics. For the low abundance peptide ions, the slope of the dynamic range drop-off in the plasma proteome is uniquely sharp compared with cell lysates. Our study provides data for testable improvements in the operation of these mass spectrometers. More importantly, we have demonstrated a new affordable expedient workflow for investigators to perform proteomic experiments through the ABRF infrastructure. (We acknowledge John Cottrell for optimizing the peak-picking parameters for Mascot Distiller).

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

Assay Portal | Office of Cancer Clinical Proteomics Research

Cancer.gov

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

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

PubMed

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

2014-08-01

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

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

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

2016-08-01

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

How well can morphology assess cell death modality? A proteomics study

PubMed Central

Chernobrovkin, Alexey L; Zubarev, Roman A

2016-01-01

While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200–500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment. PMID:27752363

NCI's Proteome Characterization Centers Announced | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI), part of the National Institutes of Health, announces the launch of a Clinical Proteomic Tumor Analysis Consortium (CPTAC). CPTAC is a comprehensive, coordinated team effort to accelerate the understanding of the molecular basis of cancer through the application of robust, quantitative, proteomic technologies and workflows.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

PubMed

Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

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

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

2016-03-04

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

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

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

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

Quantitative proteomic analysis of human lung tumor xenografts treated with the ectopic ATP synthase inhibitor citreoviridin.

PubMed

Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2013-01-01

ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy.

Quantitative Proteomic Analysis of Human Lung Tumor Xenografts Treated with the Ectopic ATP Synthase Inhibitor Citreoviridin

PubMed Central

Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2013-01-01

ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy. PMID:23990911

Oestrus synchronisation and superovulation alter the cervicovaginal mucus proteome of the ewe.

PubMed

Maddison, Jessie W; Rickard, Jessica P; Bernecic, Naomi C; Tsikis, Guillaume; Soleilhavoup, Clement; Labas, Valerie; Combes-Soia, Lucie; Harichaux, Gregoire; Druart, Xavier; Leahy, Tamara; de Graaf, Simon P

2017-02-23

Although essential for artificial insemination (AI) and MOET (multiple ovulation and embryo transfer), oestrus synchronisation and superovulation are associated with increased female reproductive tract mucus production and altered sperm transport. The effects of such breeding practices on the ovine cervicovaginal (CV) mucus proteome have not been detailed. The aim of this study was to qualitatively and quantitatively investigate the Merino CV mucus proteome in naturally cycling (NAT) ewes at oestrus and mid-luteal phase, and quantitatively compare CV oestrus mucus proteomes of NAT, progesterone synchronised (P4) and superovulated (SOV) ewes. Quantitative analysis revealed 60 proteins were more abundant during oestrus and 127 were more abundant during the luteal phase, with 27 oestrus specific and 40 luteal specific proteins identified. The oestrus proteins most disparate in abundance compared to mid-luteal phase were ceruloplasmin (CP), chitinase-3-like protein 1 (CHI3L1), clusterin (CLU), alkaline phosphatase (ALPL) and mucin-16 (MUC16). Exogenous hormones greatly altered the proteome with 51 and 32 proteins more abundant and 98 and 53 proteins less abundant, in P4 and SOV mucus, respectively when compared to NAT mucus. Investigation of the impact of these proteomic changes on sperm motility and longevity within mucus may help improve sperm transport and fertility following cervical AI. This manuscript is the first to detail the proteome of ovine cervicovaginal mucus using qualitative and quantitative proteomic methods over the oestrous cycle in naturally cycling ewes, and also after application of common oestrus synchronisation and superovulation practices. The investigation of the mucus proteome throughout both the follicular and luteal periods of the oestrous cycle, and also after oestrous synchronisation and superovulation provides information about the endocrine control and the effects that exogenous hormones have on protein expression in the female reproductive tract. This information contributes to the field by providing important information on the changes that occur to the cervicovaginal mucus proteome after use of exogenous hormones in controlled breeding programs, which are commonly used on farm and also in a research setting. Copyright © 2017 Elsevier B.V. All rights reserved.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

PubMed Central

MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.

2010-01-01

Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306

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.

Integrated Proteomic Approaches for Understanding Toxicity of Environmental Chemicals

EPA Science Inventory

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

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

PubMed

Lavallée-Adam, Mathieu; Yates, John R

2016-03-24

PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the Web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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

PubMed Central

2015-01-01

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

A practical data processing workflow for multi-OMICS projects.

PubMed

Kohl, Michael; Megger, Dominik A; Trippler, Martin; Meckel, Hagen; Ahrens, Maike; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-Claudius; Baba, Hideo A; Sitek, Barbara; Schlaak, Jörg F; Meyer, Helmut E; Stephan, Christian; Eisenacher, Martin

2014-01-01

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

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

Cancer.gov

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

False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform.

PubMed

Strickland, Erin C; Geer, M Ariel; Hong, Jiyong; Fitzgerald, Michael C

2014-01-01

Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2% and <0.8% are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.

PubMed

Moradian, Annie; Porras-Yakushi, Tanya R; Sweredoski, Michael J; Hess, Sonja

2016-01-01

When deciding to perform a quantitative proteomics analysis, selectivity, sensitivity, and reproducibility are important criteria to consider. The use of multiple reaction monitoring (MRM) has emerged as a powerful proteomics technique in that regard since it avoids many of the problems typically observed in discovery-based analyses. A prerequisite for such a targeted approach is that the protein targets are known, either as a result of previous global proteomics experiments or because a specific hypothesis is to be tested. When guidelines that have been established in the pharmaceutical industry many decades ago are taken into account, setting up an MRM assay is relatively straightforward. Typically, proteotypic peptides with favorable mass spectrometric properties are synthesized with a heavy isotope for each protein that is to be monitored. Retention times and calibration curves are determined using triple-quadrupole mass spectrometers. The use of iRT peptide standards is both recommended and fully integrated into the bioinformatics pipeline. Digested biological samples are mixed with the heavy and iRT standards and quantified. Here we present a generic protocol for the development of an MRM assay.

C-STrap Sample Preparation Method--In-Situ Cysteinyl Peptide Capture for Bottom-Up Proteomics Analysis in the STrap Format.

PubMed

Zougman, Alexandre; Banks, Rosamonde E

2015-01-01

Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.

Multiple testing corrections in quantitative proteomics: A useful but blunt tool.

PubMed

Pascovici, Dana; Handler, David C L; Wu, Jemma X; Haynes, Paul A

2016-09-01

Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics.

PubMed

Bertsch, Andreas; Jung, Stephan; Zerck, Alexandra; Pfeifer, Nico; Nahnsen, Sven; Henneges, Carsten; Nordheim, Alfred; Kohlbacher, Oliver

2010-05-07

Targeted proteomic approaches such as multiple reaction monitoring (MRM) overcome problems associated with classical shotgun mass spectrometry experiments. Developing MRM quantitation assays can be time consuming, because relevant peptide representatives of the proteins must be found and their retention time and the product ions must be determined. Given the transitions, hundreds to thousands of them can be scheduled into one experiment run. However, it is difficult to select which of the transitions should be included into a measurement. We present a novel algorithm that allows the construction of MRM assays from the sequence of the targeted proteins alone. This enables the rapid development of targeted MRM experiments without large libraries of transitions or peptide spectra. The approach relies on combinatorial optimization in combination with machine learning techniques to predict proteotypicity, retention time, and fragmentation of peptides. The resulting potential transitions are scheduled optimally by solving an integer linear program. We demonstrate that fully automated construction of MRM experiments from protein sequences alone is possible and over 80% coverage of the targeted proteins can be achieved without further optimization of the assay.

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.

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

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

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

PubMed Central

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

2009-01-01

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

Quantitative proteomics in teleost fish: insights and challenges for neuroendocrine and neurotoxicology research.

PubMed

Martyniuk, Christopher J; Popesku, Jason T; Chown, Brittany; Denslow, Nancy D; Trudeau, Vance L

2012-05-01

Neuroendocrine systems integrate both extrinsic and intrinsic signals to regulate virtually all aspects of an animal's physiology. In aquatic toxicology, studies have shown that pollutants are capable of disrupting the neuroendocrine system of teleost fish, and many chemicals found in the environment can also have a neurotoxic mode of action. Omics approaches are now used to better understand cell signaling cascades underlying fish neurophysiology and the control of pituitary hormone release, in addition to identifying adverse effects of pollutants in the teleostean central nervous system. For example, both high throughput genomics and proteomic investigations of molecular signaling cascades for both neurotransmitter and nuclear receptor agonists/antagonists have been reported. This review highlights recent studies that have utilized quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ) in neuroendocrine regions and uses these examples to demonstrate the challenges of using proteomics in neuroendocrinology and neurotoxicology research. To begin to characterize the teleost neuroproteome, we functionally annotated 623 unique proteins found in the fish hypothalamus and telencephalon. These proteins have roles in biological processes that include synaptic transmission, ATP production, receptor activity, cell structure and integrity, and stress responses. The biological processes most represented by proteins detected in the teleost neuroendocrine brain included transport (8.4%), metabolic process (5.5%), and glycolysis (4.8%). We provide an example of using sub-network enrichment analysis (SNEA) to identify protein networks in the fish hypothalamus in response to dopamine receptor signaling. Dopamine signaling altered the abundance of proteins that are binding partners of microfilaments, integrins, and intermediate filaments, consistent with data suggesting dopaminergic regulation of neuronal stability and structure. Lastly, for fish neuroendocrine studies using both high-throughput genomics and proteomics, we compare gene and protein relationships in the hypothalamus and demonstrate that correlation is often poor for single time point experiments. These studies highlight the need for additional time course analyses to better understand gene-protein relationships and adverse outcome pathways. This is important if both transcriptomics and proteomics are to be used together to investigate neuroendocrine signaling pathways or as bio-monitoring tools in ecotoxicology. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Development and application of a quantitative multiplexed small GTPase activity assay using targeted proteomics.

PubMed

Zhang, Cheng-Cheng; Li, Ru; Jiang, Honghui; Lin, Shujun; Rogalski, Jason C; Liu, Kate; Kast, Juergen

2015-02-06

Small GTPases are a family of key signaling molecules that are ubiquitously expressed in various types of cells. Their activity is often analyzed by western blot, which is limited by its multiplexing capability, the quality of isoform-specific antibodies, and the accuracy of quantification. To overcome these issues, a quantitative multiplexed small GTPase activity assay has been developed. Using four different binding domains, this assay allows the binding of up to 12 active small GTPase isoforms simultaneously in a single experiment. To accurately quantify the closely related small GTPase isoforms, a targeted proteomic approach, i.e., selected/multiple reaction monitoring, was developed, and its functionality and reproducibility were validated. This assay was successfully applied to human platelets and revealed time-resolved coactivation of multiple small GTPase isoforms in response to agonists and differential activation of these isoforms in response to inhibitor treatment. This widely applicable approach can be used for signaling pathway studies and inhibitor screening in many cellular systems.

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

PubMed Central

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

2015-01-01

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

Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

PubMed

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

2018-06-07

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

Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

PubMed

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

2017-04-07

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

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

PubMed

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

2016-02-01

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes. © 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.

Quantitative analysis of cellular proteome alterations in human influenza A virus-infected mammalian cell lines.

PubMed

Vester, Diana; Rapp, Erdmann; Gade, Dörte; Genzel, Yvonne; Reichl, Udo

2009-06-01

Over the last years virus-host cell interactions were investigated in numerous studies. Viral strategies for evasion of innate immune response, inhibition of cellular protein synthesis and permission of viral RNA and protein production were disclosed. With quantitative proteome technology, comprehensive studies concerning the impact of viruses on the cellular machinery of their host cells at protein level are possible. Therefore, 2-D DIGE and nanoHPLC-nanoESI-MS/MS analysis were used to qualitatively and quantitatively determine the dynamic cellular proteome responses of two mammalian cell lines to human influenza A virus infection. A cell line used for vaccine production (MDCK) was compared with a human lung carcinoma cell line (A549) as a reference model. Analyzing 2-D gels of the proteomes of uninfected and influenza-infected host cells, 16 quantitatively altered protein spots (at least +/-1.7-fold change in relative abundance, p<0.001) were identified for both cell lines. Most significant changes were found for keratins, major components of the cytoskeleton system, and for Mx proteins, interferon-induced key components of the host cell defense. Time series analysis of infection processes allowed the identification of further proteins that are described to be involved in protein synthesis, signal transduction and apoptosis events. Most likely, these proteins are required for supporting functions during influenza viral life cycle or host cell stress response. Quantitative proteome-wide profiling of virus infection can provide insights into complexity and dynamics of virus-host cell interactions and may accelerate antiviral research and support optimization of vaccine manufacturing processes.

Optimization of Quantitative Proteomics Using 2-Dimensional Difference Gel Electrophoresis to Characterize Molecular Mechanisms of Chemical Warfare Nerve Agent Exposure in the Rat Brain

DTIC Science & Technology

2010-11-01

minced finely with scissors, and transferred to a pre-cooled hand-held glass dounce homogenizer. The pestle was passed through the dounce until the...Nakajima, Sarin experiences in Japan : acute toxicity and long-term effects. Journal of the Neurological Sciences, 2006. 249(1): p. 76-85. 9. Shih, T.-M

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.

Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

PubMed Central

Schilling, Birgit; Gibson, Bradford W.; Hunter, Christie L.

2017-01-01

Data-independent acquisition is a powerful mass spectrometry technique that enables comprehensive MS and MS/MS analysis of all detectable species, providing an information rich data file that can be mined deeply. Here, we describe how to acquire high-quality SWATH® Acquisition data to be used for large quantitative proteomic studies. We specifically focus on using variable sized Q1 windows for acquisition of MS/MS data for generating higher specificity quantitative data. PMID:28188533

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

PubMed

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

2015-11-03

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

Comparative analysis of cerebrospinal fluid from the meningo-encephalitic stage of T. b. gambiense and rhodesiense sleeping sickness patients using TMT quantitative proteomics.

PubMed

Tiberti, Natalia; Sanchez, Jean-Charles

2015-09-01

The quantitative proteomics data here reported are part of a research article entitled "Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense", published by Tiberti et al., 2015. Transl. Proteomics 6, 1-9. Sleeping sickness (human African trypanosomiasis - HAT) is a deadly neglected tropical disease affecting mainly rural communities in sub-Saharan Africa. This parasitic disease is caused by the Trypanosoma brucei (T. b.) parasite, which is transmitted to the human host through the bite of the tse-tse fly. Two parasite sub-species, T. b. rhodesiense and T. b. gambiense, are responsible for two clinically different and geographically separated forms of sleeping sickness. The objective of the present study was to characterise and compare the cerebrospinal fluid (CSF) proteome of stage 2 (meningo-encephalitic stage) HAT patients suffering from T. b. gambiense or T. b. rhodesiense disease using high-throughput quantitative proteomics and the Tandem Mass Tag (TMT(®)) isobaric labelling. In order to evaluate the CSF proteome in the context of HAT pathophysiology, the protein dataset was then submitted to gene ontology and pathway analysis. Two significantly differentially expressed proteins (C-reactive protein and orosomucoid 1) were further verified on a larger population of patients (n=185) by ELISA, confirming the mass spectrometry results. By showing a predominant involvement of the acute immune response in rhodesiense HAT, the proteomics results obtained in this work will contribute to further understand the mechanisms of pathology occurring in HAT and to propose new biomarkers of potential clinical utility. The mass spectrometry raw data are available in the Pride Archive via ProteomeXchange through the identifier PXD001082.

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

PubMed

Lehmann, Sylvain; Hoofnagle, Andrew; Hochstrasser, Denis; Brede, Cato; Glueckmann, Matthias; Cocho, José A; Ceglarek, Uta; Lenz, Christof; Vialaret, Jérôme; Scherl, Alexander; Hirtz, Christophe

2013-05-01

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

Proteome Dynamics in Biobanked Horse Peripheral Blood Derived Lymphocytes (PBL) with Induced Autoimmune Uveitis.

PubMed

Hauck, Stefanie M; Lepper, Marlen F; Hertl, Michael; Sekundo, Walter; Deeg, Cornelia A

2017-10-01

Equine recurrent uveitis is the only spontaneous model for recurrent autoimmune uveitis in humans, where T cells target retinal proteins. Differences between normal and autoaggressive lymphocytes were identified in this study by analyzing peripheral blood derived lymphocytes (PBL) proteomes from the same case with interphotoreceptor retinoid binding protein induced uveitis sampled before (Day 0), during (Day 15), and after uveitic attack (Day 23). Relative protein abundances of PBL were investigated in a quantitative, label-free differential proteome analysis in cells that were kept frozen for 14 years since the initial experiment. Quantitative data could be acquired for 2632 proteins at all three time points. Profound changes (≥2-fold change) in PBL protein abundance were observed when comparing Day 0 with 15, representing acute inflammation (1070 regulated proteins) and Day 0 with 23 (cessation; 1571 regulated). Significant differences applied to proteins with functions in integrin signaling during active uveitis, involving "Erk and pi-3 kinase are necessary for collagen binding in corneal epithelia," "integrins in angiogenesis," and "integrin-linked kinase signaling" pathways. In contrast, at cessation of uveitic attack, significantly changed proteins belonged to pathways of "nongenotropic androgen signaling," "classical complement pathway," and "Amb2 integrin signaling." Several members of respective pathways were earlier shown to be changed in naturally occurring uveitis, underscoring the significance of these findings here and proofing the value of the induced model in mimicking spontaneous autoimmune uveitis. All MS data have been deposited to the ProteomeXchange consortium via the PRIDE partner repository (dataset identifier PXD005580). © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A tutorial for software development in quantitative proteomics using PSI standard formats☆

PubMed Central

Gonzalez-Galarza, Faviel F.; Qi, Da; Fan, Jun; Bessant, Conrad; Jones, Andrew R.

2014-01-01

The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23584085

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

PubMed Central

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

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887. PMID:27379110

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

PubMed

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

2016-01-01

Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset will serve as a useful resource for future studies in this plant. Data are available via ProteomeXchange with identifier PXD003887.

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

PubMed Central

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

2012-01-01

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

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques

NASA Astrophysics Data System (ADS)

Lespinats, Sylvain; Pinker-Domenig, Katja; Wengert, Georg; Houben, Ivo; Lobbes, Marc; Stadlbauer, Andreas; Meyer-Bäse, Anke

2016-05-01

Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques are insufficient to interpret and visualize these resulting experimental data. The emphasis of this paper lies in the application of novel approaches for the visualization, clustering and projection representation to unveil hidden data structures relevant for the accurate interpretation of biological experiments. These qualitative and quantitative methods are applied to the proteomic analysis of data sets derived from the GSCs. The achieved clustering and visualization results provide a more detailed insight into the protein-level fold changes and putative upstream regulators for the GSCs. However the extracted molecular information is insufficient in classifying GSCs and paving the pathway to an improved therapeutics of the heterogeneous glioma.

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation

PubMed Central

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-01-01

Objective: This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Methods: Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Results: Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. Conclusions: High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms mediating a sustained ‘perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity. PMID:27110685

Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutic targets of appetite regulation.

PubMed

Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D

2016-04-25

This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms mediating a sustained 'perpetual cycle' of appetite enhancement were observed. The GlyR protein may constitute a novel treatment target for the reduction of central orexigenic signals in obesity.

Plant proteome analysis: a 2006 update.

PubMed

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

2007-08-01

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

Qualis-SIS: automated standard curve generation and quality assessment for multiplexed targeted quantitative proteomic experiments with labeled standards.

PubMed

Mohammed, Yassene; Percy, Andrew J; Chambers, Andrew G; Borchers, Christoph H

2015-02-06

Multiplexed targeted quantitative proteomics typically utilizes multiple reaction monitoring and allows the optimized quantification of a large number of proteins. One challenge, however, is the large amount of data that needs to be reviewed, analyzed, and interpreted. Different vendors provide software for their instruments, which determine the recorded responses of the heavy and endogenous peptides and perform the response-curve integration. Bringing multiplexed data together and generating standard curves is often an off-line step accomplished, for example, with spreadsheet software. This can be laborious, as it requires determining the concentration levels that meet the required accuracy and precision criteria in an iterative process. We present here a computer program, Qualis-SIS, that generates standard curves from multiplexed MRM experiments and determines analyte concentrations in biological samples. Multiple level-removal algorithms and acceptance criteria for concentration levels are implemented. When used to apply the standard curve to new samples, the software flags each measurement according to its quality. From the user's perspective, the data processing is instantaneous due to the reactivity paradigm used, and the user can download the results of the stepwise calculations for further processing, if necessary. This allows for more consistent data analysis and can dramatically accelerate the downstream data analysis.

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

PubMed

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

2012-04-18

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

Proteomic and transcriptional analysis of Lactobacillus johnsonii PF01 during bile salt exposure by iTRAQ shotgun proteomics and quantitative RT-PCR.

PubMed

Lee, Ji Yoon; Pajarillo, Edward Alain B; Kim, Min Jeong; Chae, Jong Pyo; Kang, Dae-Kyung

2013-01-04

Lactobacillus johnsonii PF01 has been reported to be highly resistant to bile, a key property of probiotic microorganisms. Here, we examine the nature of the bile-salt tolerance of L. johnsonii PF01. Growth inhibition and surface morphology and physiology aberrations were observed after overnight exposure to bile stress. Quantitative proteomic profiles using iTRAQ-LC-MS/MS technology identified 8307 peptides from both untreated PF01 cells and those exposed to 0.1%, 0.2%, and 0.3% bile salts. Some 215 proteins exhibited changed levels in response to bile stress; of these, levels of 94 peptides increased while those of 121 decreased. These were classified into the following categories: stress responses, cell division, transcription, translation, nucleotide metabolism, carbohydrate transport and metabolism, cell wall biosynthesis, and amino acid biosynthesis, and 16 of unidentified function. Analysis of the mRNA expression of selected genes by quantitative reverse transcriptase-PCR verified the proteomic data. Both proteomic and mRNA data provided evidence for increased phosphotransferase activity and cell wall biosynthesis. In addition, three bile salt hydrolases were significantly upregulated by bile exposure. These findings provide a basis for future evaluations of the tolerance of potential probiotic strains toward the various gastrointestinal challenges, including bile stress.

Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

PubMed

Megger, Dominik Andre; Rosowski, Kristin; Ahrens, Maike; Bracht, Thilo; Eisenacher, Martin; Schlaak, Jörg F; Weber, Frank; Hoffmann, Andreas-Claudius; Meyer, Helmut E; Baba, Hideo A; Sitek, Barbara

2017-03-01

Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. RAB1A was verified to be a potent biomarker candidate for HCC.

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

PubMed

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

2016-10-01

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

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

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

Teaching Expression Proteomics: From the Wet-Lab to the Laptop

ERIC Educational Resources Information Center

Teixeira, Miguel C.; Santos, Pedro M.; Rodrigues, Catarina; Sa-Correia, Isabel

2009-01-01

Expression proteomics has become, in recent years, a key genome-wide expression approach in fundamental and applied life sciences. This postgenomic technology aims the quantitative analysis of all the proteins or protein forms (the so-called proteome) of a given organism in a given environmental and genetic context. It is a challenge to provide…

Strigolactone-regulated proteins revealed by iTRAQ-based quantitative proteomics in Arabidopsis.

PubMed

Li, Zhou; Czarnecki, Olaf; Chourey, Karuna; Yang, Jun; Tuskan, Gerald A; Hurst, Gregory B; Pan, Chongle; Chen, Jin-Gui

2014-03-07

Strigolactones (SLs) are a new class of plant hormones. In addition to acting as a key inhibitor of shoot branching, SLs stimulate seed germination of root parasitic plants and promote hyphal branching and root colonization of symbiotic arbuscular mycorrhizal fungi. They also regulate many other aspects of plant growth and development. At the transcription level, SL-regulated genes have been reported. However, nothing is known about the proteome regulated by this new class of plant hormones. A quantitative proteomics approach using an isobaric chemical labeling reagent, iTRAQ, to identify the proteome regulated by SLs in Arabidopsis seedlings is presented. It was found that SLs regulate the expression of about three dozen proteins that have not been previously assigned to SL pathways. These findings provide a new tool to investigate the molecular mechanism of action of SLs.

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

PubMed

Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

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

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.

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

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

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

iTRAQ-based proteomic analysis of LI-F type peptides produced by Paenibacillus polymyxa JSa-9 mode of action against Bacillus cereus.

PubMed

Han, Jinzhi; Gao, Peng; Zhao, Shengming; Bie, Xiaomei; Lu, Zhaoxin; Zhang, Chong; Lv, Fengxia

2017-01-06

LI-F type peptides (AMP-jsa9) produced by Paenibacillus polymyxa JSa-9 are a group of cyclic lipodepsipeptide antibiotics that exhibit a broad antimicrobial spectrum against Gram-positive bacteria and filamentous fungi, especially Bacillus cereus and Fusarium moniliforme. In this study, to better understand the antibacterial mechanism of AMP-jsa9 against B. cereus, the ultrastructure of AMP-jsa9-treated B. cereus cells was observed by both atomic force microscopy and transmission electron microscopy, and quantitative proteomic analysis was performed on proteins extracted from treated and untreated bacterial cells by using isobaric tag for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to access differentially expressed proteins. Furthermore, multiple experiments were conducted to validate the results of the proteomic analysis, including determinations of ATP, NAD (+) H, NADP (+) H, reactive oxygen species (ROS), the activities of catalase (CAT) and superoxide dismutase (SOD), and the relative expression of target genes by quantitative real-time PCR. Bacterial cells exposed to AMP-jsa9 showed irregular surfaces with bleb projections and concaves; we hypothesize that AMP-jsa9 penetrated the cell wall and was anchored on the cytoplasmic membrane and that ROS accumulated in the cell membrane after treatment with AMP-jsa9, modulating the bacterial membrane properties and increasing membrane permeability. Consequently, the blebs were formed on the cell wall by the impulsive force of the leakage of intercellular contents. iTRAQ-based proteomic analysis detected a total of 1317 proteins, including 176 differentially expressed proteins (75 upregulated (fold >2) and 101 downregulated (fold <0.5)). Based on proteome analysis, the putative pathways of AMP-jsa9 action against B. cereus can be summarized as: (i) inhibition of bacterial sporulation, thiamine biosynthesis, energy metabolism, DNA transcription and translation, and cell wall biosynthesis, through direct regulation of protein levels; and (ii) indirect effects on the same pathways through the accumulation of ROS and the consequent impairment of cellular functions, resulting from downregulation of antioxidant proteins, especially CAT and SOD. The mode of action of LI-F type antimicrobial peptides (AMP-jsa9) against B. cereus was elucidated at the proteomic level. Two pathways of AMP-jsa9 action upon B. cereus cells were identified and the mechanism of bleb formation on the surfaces of bacterial cells was predicted based on the results of ultrastructural observation and proteomic analysis. These results are helpful in understanding the mechanism of LI-F type peptides and in providing the theoretical base for applying AMP-jsa9 or its analogs to combat Gram-positive pathogenic bacteria in the food and feed industries. Copyright © 2016 Elsevier B.V. All rights reserved.

A Multi-layered Quantitative In Vivo Expression Atlas of the Podocyte Unravels Kidney Disease Candidate Genes.

PubMed

Rinschen, Markus M; Gödel, Markus; Grahammer, Florian; Zschiedrich, Stefan; Helmstädter, Martin; Kretz, Oliver; Zarei, Mostafa; Braun, Daniela A; Dittrich, Sebastian; Pahmeyer, Caroline; Schroder, Patricia; Teetzen, Carolin; Gee, HeonYung; Daouk, Ghaleb; Pohl, Martin; Kuhn, Elisa; Schermer, Bernhard; Küttner, Victoria; Boerries, Melanie; Busch, Hauke; Schiffer, Mario; Bergmann, Carsten; Krüger, Marcus; Hildebrandt, Friedhelm; Dengjel, Joern; Benzing, Thomas; Huber, Tobias B

2018-05-22

Damage to and loss of glomerular podocytes has been identified as the culprit lesion in progressive kidney diseases. Here, we combine mass spectrometry-based proteomics with mRNA sequencing, bioinformatics, and hypothesis-driven studies to provide a comprehensive and quantitative map of mammalian podocytes that identifies unanticipated signaling pathways. Comparison of the in vivo datasets with proteomics data from podocyte cell cultures showed a limited value of available cell culture models. Moreover, in vivo stable isotope labeling by amino acids uncovered surprisingly rapid synthesis of mitochondrial proteins under steady-state conditions that was perturbed under autophagy-deficient, disease-susceptible conditions. Integration of acquired omics dimensions suggested FARP1 as a candidate essential for podocyte function, which could be substantiated by genetic analysis in humans and knockdown experiments in zebrafish. This work exemplifies how the integration of multi-omics datasets can identify a framework of cell-type-specific features relevant for organ health and disease. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative proteomic analysis of human breast epithelial cells with differential telomere length

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

Yu, Li-Rong; Chan, King C.; Tahara, Hidetoshi

Telomeres play important functional roles in cell proliferation, cell cycle regulation, and genetic stability, in which telomere length is critical. In this study, quantitative proteome comparisons for the human breast epithelial cells with short and long telomeres (184-hTERT{sub L} vs. 184-hTERT{sub S} and 90P-hTERT{sub L} vs. 90P-hTERT{sub S}), resulting from transfection of the human telomerase reverse transcriptase (hTERT) gene, were performed using cleavable isotope-coded affinity tags. More than 2000 proteins were quantified in each comparative experiment, with approximately 77% of the proteins identified in both analyses. In the cells with long telomeres, significant and consistent alterations were observed in metabolismmore » (amino acid, nucleotide, and lipid metabolism), genetic information transmission (transcription and translation regulation, spliceosome and ribosome complexes), and cell signaling. Interestingly, the DNA excision repair pathway is enhanced, while integrin and its ligands are downregulated in the cells with long telomeres. These results may provide valuable information related to telomere functions.« less

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

PubMed

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

2008-02-01

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

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

PubMed Central

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

2014-01-01

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

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.

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

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.

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

PubMed

Terzi, F; Cambridge, S

2017-01-01

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

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data*

PubMed Central

Mitchell, Christopher J.; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-01-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, 15N, 13C, or 18O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25–45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. PMID:27231314

The impact of carbon-13 and deuterium on relative quantification of proteins using stable isotope diethyl labeling.

PubMed

Koehler, Christian J; Arntzen, Magnus Ø; Thiede, Bernd

2015-05-15

Stable isotopic labeling techniques are useful for quantitative proteomics. A cost-effective and convenient method for diethylation by reductive amination was established. The impact using either carbon-13 or deuterium on quantification accuracy and precision was investigated using diethylation. We established an effective approach for stable isotope labeling by diethylation of amino groups of peptides. The approach was validated using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and nanospray liquid chromatography/electrospray ionization (nanoLC/ESI)-ion trap/orbitrap for mass spectrometric analysis as well as MaxQuant for quantitative data analysis. Reaction conditions with low reagent costs, high yields and minor side reactions were established for diethylation. Furthermore, we showed that diethylation can be applied to up to sixplex labeling. For duplex experiments, we compared diethylation in the analysis of the proteome of HeLa cells using acetaldehyde-(13) C(2)/(12) C(2) and acetaldehyde-(2) H(4)/(1) H(4). Equal numbers of proteins could be identified and quantified; however, (13) C(4)/(12) C(4) -diethylation revealed a lower variance of quantitative peptide ratios within proteins resulting in a higher precision of quantified proteins and less falsely regulated proteins. The results were compared with dimethylation showing minor effects because of the lower number of deuteriums. The described approach for diethylation of primary amines is a cost-effective and accurate method for up to sixplex relative quantification of proteomes. (13) C(4)/(12) C(4) -diethylation enables duplex quantification based on chemical labeling without using deuterium which reduces identification of false-negatives and increases the quality of the quantification results. Copyright © 2015 John Wiley & Sons, Ltd.

Quantitative proteome analysis of barley seeds using ruthenium(II)-tris-(bathophenanthroline-disulphonate) staining.

PubMed

Witzel, Katja; Surabhi, Giridara-Kumar; Jyothsnakumari, Gottimukkala; Sudhakar, Chinta; Matros, Andrea; Mock, Hans-Peter

2007-04-01

This paper describes the application of the recently introduced fluorescence stain Ruthenium(II)-tris-(bathophenanthroline-disulphonate) (RuBP) on a comparative proteome analysis of two phenotypically different barley lines. We carried out an analysis of protein patterns from 2-D gels of the parental lines of the Oregon Wolfe Barley mapping population DOM and REC and stained with either the conventional colloidal Coomassie Brilliant Blue (cCBB) or with the novel RuBP solution. We wished to experimentally verify the usefulness of such a stain in evaluating the complex pattern of a seed proteome, in comparison to the previously used cCBB staining technique. To validate the efficiency of visualization by both stains, we first compared the overall number of detected protein spots. On average, 790 spots were visible by cCBB staining and 1200 spots by RuBP staining. Then, the intensity of a set of spots was assessed, and changes in relative abundance were determined using image analysis software. As expected, staining with RuBP performed better in quantitation in terms of sensitivity and dynamic range. Furthermore, spots from a cultivar-specific region in the protein map were chosen for identification to asses the gain of biological information due to the staining procedure. From this particular region, eight spots were visualized exclusively by RuBP and identification was successful for all spots, proving the ability to identify even very low abundant proteins. Performance in MS analysis was comparable for both protein stains. Proteins were identified by MALDI-TOF MS peptide mass fingerprinting. This approach was not successful for all spots, due to the restricted entry number for barley in the database. Therefore, we subsequently used LC-ESI-Q-TOF MS/MS and de novo sequencing for identification. Because only an insufficient number of proteins from barley is annotated, an EST-based identification strategy was chosen for our experiment. We wished to test whether under these limitations the application of a more sensitive stain would lead to a more advanced proteome approach. In summary, we demonstrate here that the application of RuBP as an economical but reliable and sensitive fluorescence stain is highly suitable for quantitative proteome analysis of plant seeds.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

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

Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis.

PubMed

Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J

2015-10-20

Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

Determination of burn patient outcome by large-scale quantitative discovery proteomics

PubMed Central

Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

2013-01-01

Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

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.

Proteomic analysis of acquired tamoxifen resistance in MCF-7 cells reveals expression signatures associated with enhanced migration

PubMed Central

2012-01-01

Introduction Acquired tamoxifen resistance involves complex signaling events that are not yet fully understood. Successful therapeutic intervention to delay the onset of hormone resistance depends critically on mechanistic elucidation of viable molecular targets associated with hormone resistance. This study was undertaken to investigate the global proteomic alterations in a tamoxifen resistant MCF-7 breast cancer cell line obtained by long term treatment of the wild type MCF-7 cell line with 4-hydroxytamoxifen (4-OH Tam). Methods We cultured MCF-7 cells with 4-OH Tam over a period of 12 months to obtain the resistant cell line. A gel-free, quantitative proteomic method was used to identify and quantify the proteome of the resistant cell line. Nano-flow high-performance liquid chromatography coupled to high resolution Fourier transform mass spectrometry was used to analyze fractionated peptide mixtures that were isobarically labeled from the resistant and control cell lysates. Real time quantitative PCR and Western blots were used to verify selected proteomic changes. Lentiviral vector transduction was used to generate MCF-7 cells stably expressing S100P. Online pathway analysis was performed to assess proteomic signatures in tamoxifen resistance. Survival analysis was done to evaluate clinical relevance of altered proteomic expressions. Results Quantitative proteomic analysis revealed a wide breadth of signaling events during transition to acquired tamoxifen resistance. A total of 629 proteins were found significantly changed with 364 up-regulated and 265 down-regulated. Collectively, these changes demonstrated the suppressed state of estrogen receptor (ER) and ER-regulated genes, activated survival signaling and increased migratory capacity of the resistant cell line. The protein S100P was found to play a critical role in conferring tamoxifen resistance and enhanced cell motility. Conclusions Our data demonstrate that the adaptive changes in the proteome of tamoxifen resistant breast cancer cells are characterized by down-regulated ER signaling, activation of alternative survival pathways, and enhanced cell motility through regulation of the actin cytoskeleton dynamics. Evidence also emerged that S100P mediates acquired tamoxifen resistance and migration capacity. PMID:22417809

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

PubMed Central

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

2011-01-01

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

Quantitative proteomic view on secreted, cell surface-associated, and cytoplasmic proteins of the methicillin-resistant human pathogen Staphylococcus aureus under iron-limited conditions.

PubMed

Hempel, Kristina; Herbst, Florian-Alexander; Moche, Martin; Hecker, Michael; Becher, Dörte

2011-04-01

Staphylococcus aureus is capable of colonizing and infecting humans by its arsenal of surface-exposed and secreted proteins. Iron-limited conditions in mammalian body fluids serve as a major environmental signal to bacteria to express virulence determinants. Here we present a comprehensive, gel-free, and GeLC-MS/MS-based quantitative proteome profiling of S. aureus under this infection-relevant situation. (14)N(15)N metabolic labeling and three complementing approaches were combined for relative quantitative analyses of surface-associated proteins. The surface-exposed and secreted proteome profiling approaches comprise trypsin shaving, biotinylation, and precipitation of the supernatant. By analysis of the outer subproteomic and cytoplasmic protein fraction, 1210 proteins could be identified including 221 surface-associated proteins. Thus, access was enabled to 70% of the predicted cell wall-associated proteins, 80% of the predicted sortase substrates, two/thirds of lipoproteins and more than 50% of secreted and cytoplasmic proteins. For iron-deficiency, 158 surface-associated proteins were quantified. Twenty-nine proteins were found in altered amounts showing particularly surface-exposed proteins strongly induced, such as the iron-regulated surface determinant proteins IsdA, IsdB, IsdC and IsdD as well as lipid-anchored iron compound-binding proteins. The work presents a crucial subject for understanding S. aureus pathophysiology by the use of methods that allow quantitative surface proteome profiling.

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.

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

Thermo-msf-parser: an open source Java library to parse and visualize Thermo Proteome Discoverer msf files.

PubMed

Colaert, Niklaas; Barsnes, Harald; Vaudel, Marc; Helsens, Kenny; Timmerman, Evy; Sickmann, Albert; Gevaert, Kris; Martens, Lennart

2011-08-05

The Thermo Proteome Discoverer program integrates both peptide identification and quantification into a single workflow for peptide-centric proteomics. Furthermore, its close integration with Thermo mass spectrometers has made it increasingly popular in the field. Here, we present a Java library to parse the msf files that constitute the output of Proteome Discoverer. The parser is also implemented as a graphical user interface allowing convenient access to the information found in the msf files, and in Rover, a program to analyze and validate quantitative proteomics information. All code, binaries, and documentation is freely available at http://thermo-msf-parser.googlecode.com.

Proteomics Analysis Reveals Abnormal Electron Transport and Excessive Oxidative Stress Cause Mitochondrial Dysfunction in Placental Tissues of Early-Onset Preeclampsia.

PubMed

Xu, Zhongwei; Jin, Xiaohan; Cai, Wei; Zhou, Maobin; Shao, Ping; Yang, Zhen; Fu, Rong; Cao, Jin; Liu, Yan; Yu, Fang; Fan, Rong; Zhang, Yan; Zou, Shuang; Zhou, Xin; Yang, Ning; Chen, Xu; Li, Yuming

2018-04-20

Early-onset preeclampsia (EOS-PE) refers to preeclampsia that occurred before 34 gestation weeks. This study is conducted to explore the relationship between mitochondrial dysfunction and the pathogenesis of EOS-PE using proteomic strategy. To identify altering expressed mitochondrial proteins between severe EOS-PE and healthy pregnancies, enrichment of mitochondria coupled with iTRAQ-based quantitative proteomic method is performed. Immunohistochemistry (IHC) and western blot are performed to detect the alteration of changing expression proteins, and confirmed the accuracy of proteomic results. A total of 1372 proteins were quantified and 132 altering expressed proteins were screened, including 86 downregulated expression proteins and 46 upregulated expression proteins (p < 0.05). Bioinformatics analysis showed that differentially expressed proteins participated in numerous biological processes, including oxidation-reduction process, respiratory electron transport chain, and oxidative phosphorylation. Especially, mitochondria-related molecules, PRDX2, PARK7, BNIP3, BCL2, PDHA1, SUCLG1, ACADM, and NDUFV1, are involved in energy-production process in the matrix and membrane of mitochondria. Results of the experiment show that abnormal electron transport, excessive oxidative stress, and mitochondrion disassembly might be the main cause of mitochondrial dysfunction, and is related to the pathogenesis of EOS-PE. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative evaluation of saliva collection methods for proteome analysis.

PubMed

Golatowski, Claas; Salazar, Manuela Gesell; Dhople, Vishnu Mukund; Hammer, Elke; Kocher, Thomas; Jehmlich, Nico; Völker, Uwe

2013-04-18

Saliva collection devices are widely used for large-scale screening approaches. This study was designed to compare the suitability of three different whole-saliva collection approaches for subsequent proteome analyses. From 9 young healthy volunteers (4 women and 5 men) saliva samples were collected either unstimulated by passive drooling or stimulated using a paraffin gum or Salivette® (cotton swab). Saliva volume, protein concentration and salivary protein patterns were analyzed comparatively. Samples collected using paraffin gum showed the highest saliva volume (4.1±1.5 ml) followed by Salivette® collection (1.8±0.4 ml) and drooling (1.0±0.4 ml). Saliva protein concentrations (average 1145 μg/ml) showed no significant differences between the three sampling schemes. Each collection approach facilitated the identification of about 160 proteins (≥2 distinct peptides) per subject, but collection-method dependent variations in protein composition were observed. Passive drooling, paraffin gum and Salivette® each allows similar coverage of the whole saliva proteome, but the specific proteins observed depended on the collection approach. Thus, only one type of collection device should be used for quantitative proteome analysis in one experiment, especially when performing large-scale cross-sectional or multi-centric studies. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-08-11

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

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

Proteomic Data Resources for EDRN Ovary Cancer Researchers within the EDRN — EDRN Public Portal

Cancer.gov

This project will generate a highly valuable data resource and make it available to all EDRN ovarian cancer researchers. The resource will include comprehensive proteomic (tandem mass spectrometry, MS/MS) data generated from plasma samples that have been collected between four months and four years prior to clinical detection of ovarian cancer. These pre-clinical samples, provided from the Beta Carotene and Retinol Efficacy Trial (CARET) prospective study, will be interrogated using IPAS, the proteomic profiling method developed by the Hanash Laboratory and with the quantitative methods developed by the McIntosh laboratory. In addition, we will combine these pre-clinical data with already completed IPAS interrogations of plasma collected at the time of ovarian cancer diagnosis. Thus together we will provide information on both pre-clinical and clinical behavior of a large number of proteins. Based on our preliminary work we are able to quantify over 500 plasma proteins in each of these experiments, many of which are putative ovarian cancer biomarkers, showing the platform is capable of providing useful information regarding biomarker candidates.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

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.

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.

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.

Proteomic landscape in Central and Eastern Europe: the 9th Central and Eastern European Proteomic Conference, Poznań, Poland.

PubMed

Gadher, Suresh Jivan; Marczak, Łukasz; Łuczak, Magdalena; Stobiecki, Maciej; Widlak, Piotr; Kovarova, Hana

2016-01-01

Every year since 2007, the Central and Eastern European Proteomic Conference (CEEPC) has excelled in representing state-of-the-art proteomics in and around Central and Eastern Europe, and linking it to international institutions worldwide. Its mission remains to contribute to all approaches of proteomics including traditional and often-revisited methodologies as well as the latest technological achievements in clinical, quantitative and structural proteomics with a view to systems biology of a variety of processes. The 9th CEEPC was held from June 15th to 18th, 2015, at the Institute of Bioorganic Chemistry, Polish Academy of Sciences in Poznań, Poland. The scientific program stimulated exchange of proteomic knowledge whilst the spectacular venue of the conference allowed participants to enjoy the cobblestoned historical city of Poznań.

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

PubMed Central

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

2014-01-01

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

Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

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

Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora

Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow thatmore » with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.« less

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-12-16

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

Quantitative Proteomic Analysis of the Hfq-Regulon in Sinorhizobium meliloti 2011

PubMed Central

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with 15N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti. PMID:23119037

Quantitative proteomic analysis of the Hfq-regulon in Sinorhizobium meliloti 2011.

PubMed

Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio

2012-01-01

Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with (15)N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti.

Quantitative proteomic view associated with resistance to clinically important antibiotics in Gram-positive bacteria: a systematic review

PubMed Central

Lee, Chang-Ro; Lee, Jung Hun; Park, Kwang Seung; Jeong, Byeong Chul; Lee, Sang Hee

2015-01-01

The increase of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) poses a worldwide and serious health threat. Although new antibiotics, such as daptomycin and linezolid, have been developed for the treatment of infections of Gram-positive pathogens, the emergence of daptomycin-resistant and linezolid-resistant strains during therapy has now increased clinical treatment failures. In the past few years, studies using quantitative proteomic methods have provided a considerable progress in understanding antibiotic resistance mechanisms. In this review, to understand the resistance mechanisms to four clinically important antibiotics (methicillin, vancomycin, linezolid, and daptomycin) used in the treatment of Gram-positive pathogens, we summarize recent advances in studies on resistance mechanisms using quantitative proteomic methods, and also examine proteins playing an important role in the bacterial mechanisms of resistance to the four antibiotics. Proteomic researches can identify proteins whose expression levels are changed in the resistance mechanism to only one antibiotic, such as LiaH in daptomycin resistance and PrsA in vancomycin resistance, and many proteins simultaneously involved in resistance mechanisms to various antibiotics. Most of resistance-related proteins, which are simultaneously associated with resistance mechanisms to several antibiotics, play important roles in regulating bacterial envelope biogenesis, or compensating for the fitness cost of antibiotic resistance. Therefore, proteomic data confirm that antibiotic resistance requires the fitness cost and the bacterial envelope is an important factor in antibiotic resistance. PMID:26322035

The developmental proteome of Drosophila melanogaster

PubMed Central

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

2017-01-01

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

Advancing Cell Biology Through Proteomics in Space and Time (PROSPECTS)*

PubMed Central

Lamond, Angus I.; Uhlen, Mathias; Horning, Stevan; Makarov, Alexander; Robinson, Carol V.; Serrano, Luis; Hartl, F. Ulrich; Baumeister, Wolfgang; Werenskiold, Anne Katrin; Andersen, Jens S.; Vorm, Ole; Linial, Michal; Aebersold, Ruedi; Mann, Matthias

2012-01-01

The term “proteomics” encompasses the large-scale detection and analysis of proteins and their post-translational modifications. Driven by major improvements in mass spectrometric instrumentation, methodology, and data analysis, the proteomics field has burgeoned in recent years. It now provides a range of sensitive and quantitative approaches for measuring protein structures and dynamics that promise to revolutionize our understanding of cell biology and molecular mechanisms in both human cells and model organisms. The Proteomics Specification in Time and Space (PROSPECTS) Network is a unique EU-funded project that brings together leading European research groups, spanning from instrumentation to biomedicine, in a collaborative five year initiative to develop new methods and applications for the functional analysis of cellular proteins. This special issue of Molecular and Cellular Proteomics presents 16 research papers reporting major recent progress by the PROSPECTS groups, including improvements to the resolution and sensitivity of the Orbitrap family of mass spectrometers, systematic detection of proteins using highly characterized antibody collections, and new methods for absolute as well as relative quantification of protein levels. Manuscripts in this issue exemplify approaches for performing quantitative measurements of cell proteomes and for studying their dynamic responses to perturbation, both during normal cellular responses and in disease mechanisms. Here we present a perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new “third generation” proteomics strategy that offers an indispensible tool for cell biology and molecular medicine. PMID:22311636

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

PubMed

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

2013-12-06

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

Monitoring Peptidase Activities in Complex Proteomes by MALDI-TOF Mass Spectrometry

PubMed Central

Villanueva, Josep; Nazarian, Arpi; Lawlor, Kevin; Tempst, Paul

2009-01-01

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semi-quantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide-substrates using robotic extraction and a MALDI-TOF mass spectrometric read-out. Relative quantitation of the peptide metabolites is done by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be employed for diagnostic or predictive purposes and enables profiling of 96 samples in 30 hours. It could be tailored to many diagnostic and pharmaco-dynamic purposes, as a read-out of catalytic and metabolic activities in body fluids or tissues. PMID:19617888

Mapping the Extracellular and Membrane Proteome Associated with the Vasculature and the Stroma in the Embryo*

PubMed Central

Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas

2013-01-01

In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615

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

PubMed

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

2015-08-01

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

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

PubMed

Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

2015-08-03

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

PubMed

Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-02-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

PubMed Central

Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-01-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice

PubMed Central

2013-01-01

Proteomics has opened a new horizon in biological sciences. Global proteomic analysis is a promising technology for the discovery of thousands of proteins, post-translational modifications, polymorphisms, and molecular interactions in a variety of biological systems. The activities and roles of the identified proteins must also be elucidated, but this is complicated by the inability of conventional proteomic methods to yield quantitative information for protein expression. Thus, a variety of biological systems remain “black boxes”. Quantitative targeted absolute proteomics (QTAP) enables the determination of absolute expression levels (mol) of any target protein, including low-abundance functional proteins, such as transporters and receptors. Therefore, QTAP will be useful for understanding the activities and roles of individual proteins and their differences, including normal/disease, human/animal, or in vitro/in vivo. Here, we describe the study protocols and precautions for QTAP experiments including in silico target peptide selection, determination of peptide concentration by amino acid analysis, setup of selected/multiple reaction monitoring (SRM/MRM) analysis in liquid chromatography–tandem mass spectrometry, preparation of protein samples (brain capillaries and plasma membrane fractions) followed by the preparation of peptide samples, simultaneous absolute quantification of target proteins by SRM/MRM analysis, data analysis, and troubleshooting. An application of QTAP in biological sciences was introduced that utilizes data from inter-strain differences in the protein expression levels of transporters, receptors, tight junction proteins and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice. Among 18 molecules, 13 (abcb1a/mdr1a/P-gp, abcc4/mrp4, abcg2/bcrp, slc2a1/glut1, slc7a5/lat1, slc16a1/mct1, slc22a8/oat3, insr, lrp1, tfr1, claudin-5, Na+/K+-ATPase, and γ-gtp) were detected in the isolated brain capillaries, and their protein expression levels were within a range of 0.637-101 fmol/μg protein. The largest difference in the levels between the three strains was 2.2-fold for 13 molecules, although bcrp and mct1 displayed statistically significant differences between C57BL/6J and the other strain(s). Highly sensitive simultaneous absolute quantification achieved by QTAP will increase the usefulness of proteomics in biological sciences and is expected to advance the new research field of pharmacoproteomics (PPx). PMID:23758935

A multiplexed quantitative proteomics approach for investigating protein expression in the developing central nervous system.

PubMed

Orme, Rowan P; Gates, Monte A; Fricker-Gates, Rosemary A

2010-08-15

Cell transplantation using stem cell-derived neurons is commonly viewed as a candidate therapy for neurodegenerative diseases. However, methods for differentiating stem cells into homogenous populations of neurons suitable for transplant remain elusive. This suggests that there are as yet unknown signalling factors working in vivo to specify neuronal cell fate during development. These factors could be manipulated to better differentiate stem cells into neural populations useful for therapeutic transplantation. Here a quantitative proteomics approach is described for investigating cell signalling in the developing central nervous system (CNS), using the embryonic ventral mesencephalon as a model. Briefly, total protein was extracted from embryonic ventral midbrain tissue before, during and after the birth of dopaminergic neurons, and digested using trypsin. Two-dimensional liquid chromatography, coupled with tandem mass spectrometry, was then used to identify proteins from the tryptic peptides. Isobaric tagging for relative and absolute quantification (iTRAQ) reagents were used to label the tryptic peptides and facilitate relative quantitative analysis. The success of the experiment was confirmed by the identification of proteins known to be expressed in the developing ventral midbrain, as well as by Western blotting, and immunolabelling of embryonic tissue sections. This method of protein discovery improves upon previous attempts to identify novel signalling factors through microarray analysis. Importantly, the methods described here could be applied to virtually any aspect of development. (c) 2010 Elsevier B.V. All rights reserved.

Quantitative Dynamics of Proteome, Acetylome, and Succinylome during Stem-Cell Differentiation into Hepatocyte-like Cells.

PubMed

Liu, Zekun; Zhang, Qing-Bin; Bu, Chen; Wang, Dawei; Yu, Kai; Gan, Zhixue; Chang, Jianfeng; Cheng, Zhongyi; Liu, Zexian

2018-06-21

Stem-cell differentiation is a complex biological process controlled by a series of functional protein clusters and signaling transductions, especially metabolism-related pathways. Although previous studies have quantified the proteome and phosphoproteome for stem-cell differentiation, the investigation of acylation-mediated regulation is still absent. In this study, we quantitatively profiled the proteome, acetylome, and succinylome in pluripotent human embryonic stem cells (hESCs) and differentiated hepatocyte-like cells (HLCs). In total, 3843 proteins, 185 acetylation sites in 103 proteins, and 602 succinylation sites in 391 proteins were quantified. The quantitative proteome showed that in differentiated HLCs the TGF-β, JAK-STAT, and RAS signaling pathways were activated, whereas ECM-related processes such as sulfates and leucine degradation were depressed. Interestingly, it was observed that the acetylation and succinylation were more intensive in hESCs, whereas protein processing in endoplasmic reticulum and the carbon metabolic pathways were especially highly succinylated. Because the metabolism patterns in pluripotent hESCs and the differentiated HLCs were different, we proposed that the dynamic acylations, especially succinylation, might regulate the Warburg-like effect and TCA cycle during differentiation. Taken together, we systematically profiled the protein and acylation levels of regulation in pluripotent hESCs and differentiated HLCs, and the results indicated the important roles of acylation in pluripotency maintenance and differentiation.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer.

PubMed

Shah, Anup D; Inder, Kerry L; Shah, Alok K; Cristino, Alexandre S; McKie, Arthur B; Gabra, Hani; Davis, Melissa J; Hill, Michelle M

2016-10-07

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

Proteomic analysis of mitochondria in respiratory epithelial cells infected with human respiratory syncytial virus and functional implications for virus and cell biology.

PubMed

Munday, Diane C; Howell, Gareth; Barr, John N; Hiscox, Julian A

2015-03-01

The aim of this study was to quantitatively characterise the mitochondrial proteome of airway epithelial cells infected with human respiratory syncytial virus (HRSV), a major cause of paediatric illness. Quantitative proteomics, underpinned by stable isotope labelling with amino acids in cell culture, coupled to LC-MS/MS, was applied to mitochondrial fractions prepared from HRSV-infected and mock-infected cells 12 and 24 h post-infection. Datasets were analysed using ingenuity pathway analysis, and the results were validated and characterised using bioimaging, targeted inhibition and gene depletion. The data quantitatively indicated that antiviral signalling proteins converged on mitochondria during HRSV infection. The mitochondrial receptor protein Tom70 was found to act in an antiviral manner, while its chaperone, Hsp90, was confirmed to be a positive viral factor. Proteins associated with different organelles were also co-enriched in the mitochondrial fractions from HRSV-infected cells, suggesting that alterations in organelle dynamics and membrane associations occur during virus infection. Protein and pathway-specific alterations occur to the mitochondrial proteome in a spatial and temporal manner during HRSV infection, suggesting that this organelle may have altered functions. These could be targeted as part of potential therapeutic strategies to disrupt virus biology. © 2014 Royal Pharmaceutical Society.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Proteomes and Phosphoproteomes of Anther and Pollen: Availability and Progress.

PubMed

Zhang, Zaibao; Hu, Menghui; Feng, Xiaobing; Gong, Andong; Cheng, Lin; Yuan, Hongyu

2017-10-01

In flowering plants, anther development plays crucial role in sexual reproduction. Within the anther, microspore mother cells meiosis produces microspores, which further develop into pollen grains that play decisive role in plant reproduction. Previous studies on anther biology mainly focused on single gene functions relying on genetic and molecular methods. Recently, anther development has been expanded from multiple OMICS approaches like transcriptomics, proteomics/phosphoproteomics, and metabolomics. The development of proteomics techniques allowing increased proteome coverage and quantitative measurements of proteins which can characterize proteomes and their modulation during normal development, biotic and abiotic stresses in anther development. In this review, we summarize the achievements of proteomics and phosphoproteomics with anther and pollen organs from model plant and crop species (i.e. Arabidopsis, rice, tobacco). The increased proteomic information facilitated translation of information from the models to crops and thus aid in agricultural improvement. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2015-04-29

To elucidate the mechanisms contributing to fruit responses to senescence and stressful environmental stimuli under low temperature (LT) and controlled atmosphere (CA) storage, a label-free quantitative proteomic investigation was conducted in strawberry (Fragaria ananassa, Duch. cv. 'Akihime'). Postharvest physiological quality traits including firmness, total soluble solids, total acidity, ascorbic acid and volatile production were characterized following storage under different conditions. The observed post-storage protein expression profiles may be associated with delayed senescence features in strawberry. A total of 454 proteins were identified in differentially treated strawberry fruits. Quantitative analysis, using normalized spectral counts, revealed 73 proteins common to all treatments, which formed three clusters in a hierarchical clustering analysis. The proteins spanned a range of functions in various metabolic pathways and networks involved in carbohydrate and energy metabolism, volatile biosynthesis, phenylpropanoid activity, stress response and protein synthesis, degradation and folding. After CA and LT storage, 16 (13) and 11 (17) proteins, respectively, were significantly increased (decreased) in abundance, while expression profile of 12 proteins was significantly changed by both CA and LT. To summarize, the differential variability of abundance in strawberry proteome, working in a cooperative manner, provided an overview of the biological processes that occurred during CA and LT storage. Controlled atmosphere storage at an optimal temperature is regarded to be an effective postharvest technology to delay fruit senescence and maintain fruit quality during shelf life. Nonetheless, little information on fruit proteomic changes under controlled atmosphere and/or low temperature storage is available. The significance of this paper is that it is the first study employing a label-free approach in the investigation of strawberry fruit response to controlled atmosphere and cold storage. Changes in postharvest physiological quality traits including volatile production, firmness, ascorbic acid, soluble solids and total acidity were also characterized. Significant biological changes associated with senescence were revealed and differentially abundant proteins under various storage conditions were identified. Proteomic profiles were linked to physiological aspects of strawberry fruit senescence in order to provide new insights into possible regulation mechanisms. Findings from this study not only provide proteomic information on fruit regulation, but also pave the way for further quantitative studies at the transcriptomic and metabolomic levels. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of Mature Atherosclerotic Plaque Proteome Signatures Using Data-Independent Acquisition Mass Spectrometry.

PubMed

Hansmeier, Nicole; Buttigieg, Josef; Kumar, Pankaj; Pelle, Shaneen; Choi, Kyoo Yoon; Kopriva, David; Chao, Tzu-Chiao

2018-01-05

Atherosclerosis is a chronic inflammatory disease with complex pathobiology and one of the most common causes of cardiovascular events. The process is characterized by complex vascular remodeling processes that require the actions of numerous proteins. The composition of atherosclerotic plaque is increasingly recognized as a major factor governing the occurrence of cardiovascular or neurological symptoms. To gain deeper insights into the composition of atherosclerotic plaques, we created quantitative proteome profiles of advanced plaque tissues of six male patients undergoing carotid endarterectomy for stroke prevention. Using a quantitative, data-independent proteome approach, we identified 4181 proteins with an average protein coverage of 45%. An analysis of the quantitative composition of the tissue revealed key players of vascular remodeling processes. Moreover, compared with proximal arterial tissue, 20 proteins in mature plaques were enriched, whereas 52 proteins were found in lower quantities. Among the proteins with increased abundance were prominent extracellular matrix proteins such as biglycan and lumican, whereas cytoskeletal markers for contractile smooth muscle cells (SMCs) were decreased. Taken together, this study provides the most comprehensive quantitative assessment of mature human plaque tissue to date, which indicates a central role of SMCs in the structure of advanced atherosclerotic plaques.

Embryology in the era of proteomics.

PubMed

Katz-Jaffe, Mandy G; McReynolds, Susanna

2013-03-15

Proteomic technologies have begun providing evidence that viable embryos possess unique protein profiles. Some of these potential protein biomarkers have been identified as extracellular and could be used in the development of a noninvasive quantitative method for embryo assessment. The field of assisted reproductive technologies would benefit from defining the human embryonic proteome and secretome, thereby expanding our current knowledge of embryonic cellular processes. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2013-04-05

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

A 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

Quantitative Analysis of the Human Milk Whey Proteome Reveals Developing Milk and Mammary-Gland Functions across the First Year of Lactation

PubMed Central

Zhang, Qiang; Cundiff, Judy K.; Maria, Sarah D.; McMahon, Robert J.; Woo, Jessica G.; Davidson, Barbara S.; Morrow, Ardythe L.

2013-01-01

In-depth understanding of the changing functions of human milk (HM) proteins and the corresponding physiological adaptions of the lactating mammary gland has been inhibited by incomplete knowledge of the HM proteome. We analyzed the HM whey proteome (n = 10 women with samples at 1 week and 1, 3, 6, 9 and 12 months) using a quantitative proteomic approach. One thousand three hundred and thirty three proteins were identified with 615 being quantified. Principal component analysis revealed a transition in the HM whey proteome-throughout the first year of lactation. Abundance changes in IgG, sIgA and sIgM display distinct features during the first year. Complement components and other acute-phase proteins are generally at higher levels in early lactation. Proteomic analysis further suggests that the sources of milk fatty acids (FA) shift from more direct blood influx to more de novo mammary synthesis over lactation. The abundances of the majority of glycoproteins decline over lactation, which is consistent with increased enzyme expression in glycoprotein degradation and decreased enzyme expression in glycoprotein synthesis. Cellular detoxification machinery may be transformed as well, thereby accommodating increased metabolic activities in late lactation. The multiple developing functions of HM proteins and the corresponding mammary adaption become more apparent from this study. PMID:28250401

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.

Differential effect of TGFβ on the proteome of cancer associated fibroblasts and cancer epithelial cells in a co-culture approach - a short report.

PubMed

Koczorowska, Maria Magdalena; Friedemann, Charlotte; Geiger, Klaus; Follo, Marie; Biniossek, Martin Lothar; Schilling, Oliver

2017-12-01

Solid tumors contain various components that together form the tumor microenvironment. Cancer associated fibroblasts (CAFs) are capable of secreting and responding to signaling molecules and growth factors. Due to their role in tumor development, CAFs are considered as potential therapeutic targets. A prominent tumor-associated signaling molecule is transforming growth factor β (TGFβ), an inducer of epithelial-to-mesenchymal transition (EMT). The differential action of TGFβ on CAFs and ETCs (epithelial tumor cells) has recently gained interest. Here, we aimed to investigate the effects of TGFβ on CAFs and ETCs at the proteomic level. We established a 2D co-culture system of differentially fluorescently labeled CAFs and ETCs and stimulated this co-culture system with TGFβ. The respective cell types were separated using FACS and subjected to quantitative analyses of individual proteomes using mass spectrometry. We found that TGFβ treatment had a strong impact on the proteome composition of CAFs, whereas ETCs responded only marginally to TGFβ. Quantitative proteomic analyses of the different cell types revealed up-regulation of extracellular matrix (ECM) proteins in TGFβ treated CAFs. In addition, we found that the TGFβ treated CAFs exhibited increased N-cadherin levels. From our data we conclude that CAFs respond to TGFβ treatment by changing their proteome composition, while ETCs appear to be rather resilient.

Hybrid data acquisition and processing strategies with increased throughput and selectivity: pSMART analysis for global qualitative and quantitative analysis.

PubMed

Prakash, Amol; Peterman, Scott; Ahmad, Shadab; Sarracino, David; Frewen, Barbara; Vogelsang, Maryann; Byram, Gregory; Krastins, Bryan; Vadali, Gouri; Lopez, Mary

2014-12-05

Data-dependent acquisition (DDA) and data-independent acquisition strategies (DIA) have both resulted in improved understanding of proteomics samples. Both strategies have advantages and disadvantages that are well-published, where DDA is typically applied for deep discovery and DIA may be used to create sample records. In this paper, we present a hybrid data acquisition and processing strategy (pSMART) that combines the strengths of both techniques and provides significant benefits for qualitative and quantitative peptide analysis. The performance of pSMART is compared to published DIA strategies in an experiment that allows the objective assessment of DIA performance with respect to interrogation of previously acquired MS data. The results of this experiment demonstrate that pSMART creates fewer decoy hits than a standard DIA strategy. Moreover, we show that pSMART is more selective, sensitive, and reproducible than either standard DIA or DDA strategies alone.

USING GENOMICS AND PROTEOMICS TO DIAGNOSE EXPOSURE OF AQUATIC ORGANISMS TO ENVIRONMENTAL CONTAMINANTS

EPA Science Inventory

Advances in molecular biology allow the use of cutting-edge genomic and proteomic tools to assess the effects of environmental contaminants on aquatic organisms. Techniques are available to measure changes in expression of single genes (quantitative real-time PCR) or to measure g...

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

PubMed

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

2011-01-01

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

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

PubMed Central

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms. PMID:23176545

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics.

PubMed

Mani, D R; Abbatiello, Susan E; Carr, Steven A

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.

pyQms enables universal and accurate quantification of mass spectrometry data.

PubMed

Leufken, Johannes; Niehues, Anna; Sarin, L Peter; Wessel, Florian; Hippler, Michael; Leidel, Sebastian A; Fufezan, Christian

2017-10-01

Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2016-08-16

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

A proteomics performance standard to support measurement quality in proteomics.

PubMed

Beasley-Green, Ashley; Bunk, David; Rudnick, Paul; Kilpatrick, Lisa; Phinney, Karen

2012-04-01

The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.

PubMed

Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal; Lu, Xiaodong; Mani, D R

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.

Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Jaffe, Jacob D.; Feeney, Caitlin M.; Patel, Jinal; Lu, Xiaodong; Mani, D. R.

2016-11-01

Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques.

Tyrosine-Nitrated Proteins: Proteomic and Bioanalytical Aspects.

PubMed

Batthyány, Carlos; Bartesaghi, Silvina; Mastrogiovanni, Mauricio; Lima, Analía; Demicheli, Verónica; Radi, Rafael

2017-03-01

"Nitroproteomic" is under active development, as 3-nitrotyrosine in proteins constitutes a footprint left by the reactions of nitric oxide-derived oxidants that are usually associated to oxidative stress conditions. Moreover, protein tyrosine nitration can cause structural and functional changes, which may be of pathophysiological relevance for human disease conditions. Biological protein tyrosine nitration is a free radical process involving the intermediacy of tyrosyl radicals; in spite of being a nonenzymatic process, nitration is selectively directed toward a limited subset of tyrosine residues. Precise identification and quantitation of 3-nitrotyrosine in proteins has represented a "tour de force" for researchers. Recent Advances: A small number of proteins are preferential targets of nitration (usually less than 100 proteins per proteome), contrasting with the large number of proteins modified by other post-translational modifications such as phosphorylation, acetylation, and, notably, S-nitrosation. Proteomic approaches have revealed key features of tyrosine nitration both in vivo and in vitro, including selectivity, site specificity, and effects in protein structure and function. Identification of 3-nitrotyrosine-containing proteins and mapping nitrated residues is challenging, due to low abundance of this oxidative modification in biological samples and its unfriendly behavior in mass spectrometry (MS)-based technologies, that is, MALDI, electrospray ionization, and collision-induced dissociation. The use of (i) classical two-dimensional electrophoresis with immunochemical detection of nitrated proteins followed by protein ID by regular MS/MS in combination with (ii) immuno-enrichment of tyrosine-nitrated peptides and (iii) identification of nitrated peptides by a MIDAS™ experiment is arising as a potent methodology to unambiguously map and quantitate tyrosine-nitrated proteins in vivo. Antioxid. Redox Signal. 26, 313-328.

Detection of Elevated Plasma Levels of EGF Receptor Prior to Breast Cancer Diagnosis among Hormone Therapy Users

PubMed Central

Pitteri, Sharon J.; Amon, Lynn M.; Buson, Tina Busald; Zhang, Yuzheng; Johnson, Melissa M.; Chin, Alice; Kennedy, Jacob; Wong, Chee-Hong; Zhang, Qing; Wang, Hong; Lampe, Paul D.; Prentice, Ross L.; McIntosh, Martin W.; Hanash, Samir M.; Li, Christopher I.

2010-01-01

Applying advanced proteomic technologies to prospectively collected specimens from large studies is one means of identifying preclinical changes in plasma proteins that are potentially relevant to the early detection of diseases like breast cancer. We conducted fourteen independent quantitative proteomics experiments comparing pooled plasma samples collected from 420 estrogen receptor positive (ER+) breast cancer patients ≤17 months prior to their diagnosis and matched controls. Based on the over 3.4 million tandem mass spectra collected in the discovery set, 503 proteins were quantified of which 57 differentiated cases from controls with a p-value<0.1. Seven of these proteins, for which quantitative ELISA assays were available, were assessed in an independent validation set. Of these candidates, epidermal growth factor receptor (EGFR) was validated as a predictor of breast cancer risk in an independent set of preclinical plasma samples for women overall [odds ratio (OR)=1.44, p-value=0.0008], and particularly for current users of estrogen plus progestin (E+P) menopausal hormone therapy (OR=2.49, p-value=0.0001). Among current E+P users EGFR's sensitivity for breast cancer risk was 31% with 90% specificity. While EGFR's sensitivity and specificity are insufficient for a clinically useful early detection biomarker, this study suggests that proteins that are elevated preclinically in women who go on to develop breast cancer can be discovered and validated using current proteomic technologies. Further studies are warranted to both examine the role of EGFR and to discover and validate other proteins that could potentially be used for breast cancer early detection. PMID:20959476

An introduction to statistical process control in research proteomics.

PubMed

Bramwell, David

2013-12-16

Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays [3] making it an ideal methodology to apply to this area of biological research. To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate. We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies. Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance. This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 The Author. Published by Elsevier B.V. All rights reserved.

Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.

PubMed

Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J

2013-03-01

Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.

Click-MS: Tagless Protein Enrichment Using Bioorthogonal Chemistry for Quantitative Proteomics.

PubMed

Smits, Arne H; Borrmann, Annika; Roosjen, Mark; van Hest, Jan C M; Vermeulen, Michiel

2016-12-16

Epitope-tagging is an effective tool to facilitate protein enrichment from crude cell extracts. Traditionally, N- or C-terminal fused tags are employed, which, however, can perturb protein function. Unnatural amino acids (UAAs) harboring small reactive handles can be site-specifically incorporated into proteins, thus serving as a potential alternative for conventional protein tags. Here, we introduce Click-MS, which combines the power of site-specific UAA incorporation, bioorthogonal chemistry, and quantitative mass spectrometry-based proteomics to specifically enrich a single protein of interest from crude mammalian cell extracts. By genetic encoding of p-azido-l-phenylalanine, the protein of interest can be selectively captured using copper-free click chemistry. We use Click-MS to enrich proteins that function in different cellular compartments, and we identify protein-protein interactions, showing the great potential of Click-MS for interaction proteomics workflows.

pH-regulated formation of side products in the reductive amination approach for differential labeling of peptides in relative quantitative experiments.

PubMed

Levi Mortera, Stefano; Dioni, Ilaria; Greco, Viviana; Neri, Cristina; Rovero, Paolo; Urbani, Andrea

2014-05-01

Among the most common stable-isotope labeling strategies, the reaction of formaldehyde with peptides in the presence of NaCNBH₃ features many attractive aspects that are conducive to its employment in quantitation experiments in proteomics. Reductive amination, with formaldehyde and d(2)-formaldehyde, is reported to be a fast, easy, and specific reaction, undoubtedly inexpensive if compared with commercially available kits for differential isotope coding. Acetaldehyde and d(4)-acetaldehyde could be employed as well without a substantial increase in terms of cost, and should provide a wider spacing between the differentially tagged peptides in the mass spectrum. Nevertheless, only a single paper reports about a diethylation approach for quantitation. We undertook a systematic analytical investigation on the reductive amination of some standard peptides pointing out the occasional occurrence of side reactions in dependence of pH or reagents order of addition, particularly observing the formation of cyclic adducts ascribable to rearrangements involving the generated Schiff-base and all the nucleophilic sites of its chemical environment. We also tried to evaluate how much this side-products amount may impair isotope coded relative quantitation.

The Escherichia coli O157:H7 bovine rumen fluid proteome reflects adaptive bacterial responses.

PubMed

Kudva, Indira T; Stanton, Thaddeus B; Lippolis, John D

2014-02-21

To obtain insights into Escherichia coli O157:H7 (O157) survival mechanisms in the bovine rumen, we defined the growth characteristics and proteome of O157 cultured in rumen fluid (RF; pH 6.0-7.2 and low volatile fatty acid content) obtained from rumen-fistulated cattle fed low protein content "maintenance diet" under diverse in vitro conditions. Bottom-up proteomics (LC-MS/MS) of whole cell-lysates of O157 cultured under anaerobic conditions in filter-sterilized RF (fRF; devoid of normal ruminal microbiota) and nutrient-depleted and filtered RF (dRF) resulted in an anaerobic O157 fRF-and dRF-proteome comprising 35 proteins functionally associated with cell structure, motility, transport, metabolism and regulation, but interestingly, not with O157 virulence. Shotgun proteomics-based analysis using isobaric tags for relative and absolute quantitation used to further study differential protein expression in unfiltered RF (uRF; RF containing normal rumen microbial flora) complemented these results. Our results indicate that in the rumen, the first anatomical compartment encountered by this human pathogen within the cattle gastrointestinal tract (GIT), O157 initiates a program of specific gene expression that enables it to adapt to the in vivo environment, and successfully transit to its colonization sites in the bovine GIT. Further experiments in vitro using uRF from animals fed different diets and with additional O157 strains, and in vivo using rumen-fistulated cattle will provide a comprehensive understanding of the adaptive mechanisms involved, and help direct evolution of novel modalities for blocking O157 infection of cattle.

Consistency of the Proteome in Primary Human Keratinocytes With Respect to Gender, Age, and Skin Localization*

PubMed Central

Sprenger, Adrian; Weber, Sebastian; Zarai, Mostafa; Engelke, Rudolf; Nascimento, Juliana M.; Gretzmeier, Christine; Hilpert, Martin; Boerries, Melanie; Has, Cristina; Busch, Hauke; Bruckner-Tuderman, Leena; Dengjel, Jörn

2013-01-01

Keratinocytes account for 95% of all cells of the epidermis, the stratified squamous epithelium forming the outer layer of the skin, in which a significant number of skin diseases takes root. Immortalized keratinocyte cell lines are often used as research model systems providing standardized, reproducible, and homogenous biological material. Apart from that, primary human keratinocytes are frequently used for medical studies because the skin provides an important route for drug administration and is readily accessible for biopsies. However, comparability of these cell systems is not known. Cell lines may undergo phenotypic shifts and may differ from the in vivo situation in important aspects. Primary cells, on the other hand, may vary in biological functions depending on gender and age of the donor and localization of the biopsy specimen. Here we employed metabolic labeling in combination with quantitative mass spectrometry-based proteomics to assess A431 and HaCaT cell lines for their suitability as model systems. Compared with cell lines, comprehensive profiling of the primary human keratinocyte proteome with respect to gender, age, and skin localization identified an unexpected high proteomic consistency. The data were analyzed by an improved ontology enrichment analysis workflow designed for the study of global proteomics experiments. It enables a quick, comprehensive and unbiased overview of altered biological phenomena and links experimental data to literature. We guide through our workflow, point out its advantages compared with other methods and apply it to visualize differences of cell lines compared with primary human keratinocytes. PMID:23722187

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

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

PubMed

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

2015-06-06

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

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

Data Generated by Quantitative Liquid Chromatography-Mass Spectrometry Proteomics Are Only the Start and Not the Endpoint: Optimization of Quantitative Concatemer-Based Measurement of Hepatic Uridine-5'-Diphosphate-Glucuronosyltransferase Enzymes with Reference to Catalytic Activity.

PubMed

Achour, Brahim; Dantonio, Alyssa; Niosi, Mark; Novak, Jonathan J; Al-Majdoub, Zubida M; Goosen, Theunis C; Rostami-Hodjegan, Amin; Barber, Jill

2018-06-01

Quantitative proteomic methods require optimization at several stages, including sample preparation, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and data analysis, with the final analysis stage being less widely appreciated by end-users. Previously reported measurement of eight uridine-5'-diphospho-glucuronosyltransferases (UGT) generated by two laboratories [using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT)] reflected significant disparity between proteomic methods. Initial analysis of QconCAT data showed lack of correlation with catalytic activity for several UGTs (1A4, 1A6, 1A9, 2B15) and moderate correlations for UGTs 1A1, 1A3, and 2B7 ( R s = 0.40-0.79, P < 0.05; R 2 = 0.30); good correlations were demonstrated between cytochrome P450 activities and abundances measured in the same experiments. Consequently, a systematic review of data analysis, starting from unprocessed LC-MS/MS data, was undertaken, with the aim of improving accuracy, defined by correlation against activity. Three main criteria were found to be important: choice of monitored peptides and fragments, correction for isotope-label incorporation, and abundance normalization using fractional protein mass. Upon optimization, abundance-activity correlations improved significantly for six UGTs ( R s = 0.53-0.87, P < 0.01; R 2 = 0.48-0.73); UGT1A9 showed moderate correlation ( R s = 0.47, P = 0.02; R 2 = 0.34). No spurious abundance-activity relationships were identified. However, methods remained suboptimal for UGT1A3 and UGT1A9; here hydrophobicity of standard peptides is believed to be limiting. This commentary provides a detailed data analysis strategy and indicates, using examples, the significance of systematic data processing following acquisition. The proposed strategy offers significant improvement on existing guidelines applicable to clinically relevant proteins quantified using QconCAT. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

The protein expression landscape of mitosis and meiosis in diploid budding yeast.

PubMed

Becker, Emmanuelle; Com, Emmanuelle; Lavigne, Régis; Guilleux, Marie-Hélène; Evrard, Bertrand; Pineau, Charles; Primig, Michael

2017-03-06

Saccharomyces cerevisiae is an established model organism for the molecular analysis of fundamental biological processes. The genomes of numerous strains have been sequenced, and the transcriptome and proteome ofmajor phases during the haploid and diploid yeast life cycle have been determined. However, much less is known about dynamic changes of the proteome when cells switch from mitotic growth to meiotic development. We report a quantitative protein profiling analysis of yeast cell division and differentiation based on mass spectrometry. Information about protein levels was integrated with strand-specific tiling array expression data. We identified a total of 2366 proteins in at least one condition, including 175 proteins showing a statistically significant>5-fold change across the sample set, and 136 proteins detectable in sporulating but not respiring cells. We correlate protein expression patterns with biological processes and molecular function by Gene Ontology term enrichment, chemoprofiling, transcription interference and the formation of double stranded RNAs by overlapping sense/antisense transcripts. Our work provides initial quantitative insight into protein expression in diploid respiring and differentiating yeast cells. Critically, it associates developmentally regulated induction of antisense long noncoding RNAs and double stranded RNAs with fluctuating protein concentrations during growth and development. This integrated genomics analysis helps better understand how the transcriptome and the proteome correlate in diploid yeast cells undergoing mitotic growth in the presence of acetate (respiration) versus meiotic differentiation (Meiosis I and II). The study (i) provides quantitative expression data for 2366 proteins and their cognate mRNAs in at least one sample, (ii) shows strongly fluctuating protein levels during growth and differentiation for 175 cases, and (iii) identifies 136 proteins absent in mitotic but present in meiotic yeast cells. We have integrated protein profiling data using mass spectrometry with tiling array RNA profiling data and information on double-stranded RNAs (dsRNAs) by overlapping sense/antisense transcripts from an RNA-Sequencing experiment. This work therefore provides quantitative insight into protein expression during cell division and development and associates changing protein levels with developmental stage specific induction of antisense transcripts and the formation of dsRNAs. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data.

PubMed

Mitchell, Christopher J; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-08-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, (15)N, (13)C, or (18)O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25-45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

A Novel Pulse-Chase SILAC Strategy Measures Changes in Protein Decay and Synthesis Rates Induced by Perturbation of Proteostasis with an Hsp90 Inhibitor

PubMed Central

Fierro-Monti, Ivo; Racle, Julien; Hernandez, Celine; Waridel, Patrice; Hatzimanikatis, Vassily; Quadroni, Manfredo

2013-01-01

Standard proteomics methods allow the relative quantitation of levels of thousands of proteins in two or more samples. While such methods are invaluable for defining the variations in protein concentrations which follow the perturbation of a biological system, they do not offer information on the mechanisms underlying such changes. Expanding on previous work [1], we developed a pulse-chase (pc) variant of SILAC (stable isotope labeling by amino acids in cell culture). pcSILAC can quantitate in one experiment and for two conditions the relative levels of proteins newly synthesized in a given time as well as the relative levels of remaining preexisting proteins. We validated the method studying the drug-mediated inhibition of the Hsp90 molecular chaperone, which is known to lead to increased synthesis of stress response proteins as well as the increased decay of Hsp90 “clients”. We showed that pcSILAC can give information on changes in global cellular proteostasis induced by treatment with the inhibitor, which are normally not captured by standard relative quantitation techniques. Furthermore, we have developed a mathematical model and computational framework that uses pcSILAC data to determine degradation constants kd and synthesis rates Vs for proteins in both control and drug-treated cells. The results show that Hsp90 inhibition induced a generalized slowdown of protein synthesis and an increase in protein decay. Treatment with the inhibitor also resulted in widespread protein-specific changes in relative synthesis rates, together with variations in protein decay rates. The latter were more restricted to individual proteins or protein families than the variations in synthesis. Our results establish pcSILAC as a viable workflow for the mechanistic dissection of changes in the proteome which follow perturbations. Data are available via ProteomeXchange with identifier PXD000538. PMID:24312217

Quantitative Proteomics of Sleep-Deprived Mouse Brains Reveals Global Changes in Mitochondrial Proteins

PubMed Central

Li, Tie-Mei; Zhang, Ju-en; Lin, Rui; Chen, She; Luo, Minmin; Dong, Meng-Qiu

2016-01-01

Sleep is a ubiquitous, tightly regulated, and evolutionarily conserved behavior observed in almost all animals. Prolonged sleep deprivation can be fatal, indicating that sleep is a physiological necessity. However, little is known about its core function. To gain insight into this mystery, we used advanced quantitative proteomics technology to survey the global changes in brain protein abundance. Aiming to gain a comprehensive profile, our proteomics workflow included filter-aided sample preparation (FASP), which increased the coverage of membrane proteins; tandem mass tag (TMT) labeling, for relative quantitation; and high resolution, high mass accuracy, high throughput mass spectrometry (MS). In total, we obtained the relative abundance ratios of 9888 proteins encoded by 6070 genes. Interestingly, we observed significant enrichment for mitochondrial proteins among the differentially expressed proteins. This finding suggests that sleep deprivation strongly affects signaling pathways that govern either energy metabolism or responses to mitochondrial stress. Additionally, the differentially-expressed proteins are enriched in pathways implicated in age-dependent neurodegenerative diseases, including Parkinson’s, Huntington’s, and Alzheimer’s, hinting at possible connections between sleep loss, mitochondrial stress, and neurodegeneration. PMID:27684481

SILAC-Based Comparative Proteomic Analysis of Lysosomes from Mammalian Cells Using LC-MS/MS.

PubMed

Thelen, Melanie; Winter, Dominic; Braulke, Thomas; Gieselmann, Volkmar

2017-01-01

Mass spectrometry-based proteomics of lysosomal proteins has led to significant advances in understanding lysosomal function and pathology. The ever-increasing sensitivity and resolution of mass spectrometry in combination with labeling procedures which allow comparative quantitative proteomics can be applied to shed more light on the steadily increasing range of lysosomal functions. In addition, investigation of alterations in lysosomal protein composition in the many lysosomal storage diseases may yield further insights into the molecular pathology of these disorders. Here, we describe a protocol which allows to determine quantitative differences in the lysosomal proteome of cells which are genetically and/or biochemically different or have been exposed to certain stimuli. The method is based on stable isotope labeling of amino acids in cell culture (SILAC). Cells are exposed to superparamagnetic iron oxide particles which are endocytosed and delivered to lysosomes. After homogenization of cells, intact lysosomes are rapidly enriched by passing the cell homogenates over a magnetic column. Lysosomes are eluted after withdrawal of the magnetic field and subjected to mass spectrometry.

The jmzQuantML programming interface and validator for the mzQuantML data standard.

PubMed

Qi, Da; Krishna, Ritesh; Jones, Andrew R

2014-03-01

The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data. We present a Java application programming interface (API) for mzQuantML called jmzQuantML. The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file. The API provides read and write capabilities, and is designed to be embedded in other software packages, enabling mzQuantML support to be added to proteomics software tools (http://code.google.com/p/jmzquantml/). The mzQuantML standard is designed around a multilevel validation system to ensure that files are structurally and semantically correct for different proteomics quantitative techniques. In this article, we also describe a Java software tool (http://code.google.com/p/mzquantml-validator/) for validating mzQuantML files, which is a formal part of the data standard. © 2014 The Authors. Proteomics published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Analysis of Pathogenic Fungi Reveals Highly Expressed Conserved Cell Wall Proteins

PubMed Central

Champer, Jackson; Ito, James I.; Clemons, Karl V.; Stevens, David A.; Kalkum, Markus

2016-01-01

We are presenting a quantitative proteomics tally of the most commonly expressed conserved fungal proteins of the cytosol, the cell wall, and the secretome. It was our goal to identify fungi-typical proteins that do not share significant homology with human proteins. Such fungal proteins are of interest to the development of vaccines or drug targets. Protein samples were derived from 13 fungal species, cultured in rich or in minimal media; these included clinical isolates of Aspergillus, Candida, Mucor, Cryptococcus, and Coccidioides species. Proteomes were analyzed by quantitative MSE (Mass Spectrometry—Elevated Collision Energy). Several thousand proteins were identified and quantified in total across all fractions and culture conditions. The 42 most abundant proteins identified in fungal cell walls or supernatants shared no to very little homology with human proteins. In contrast, all but five of the 50 most abundant cytosolic proteins had human homologs with sequence identity averaging 59%. Proteomic comparisons of the secreted or surface localized fungal proteins highlighted conserved homologs of the Aspergillus fumigatus proteins 1,3-β-glucanosyltransferases (Bgt1, Gel1-4), Crf1, Ecm33, EglC, and others. The fact that Crf1 and Gel1 were previously shown to be promising vaccine candidates, underlines the value of the proteomics data presented here. PMID:26878023

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

PubMed

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

2016-04-13

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-04-01

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

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

PubMed

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

2017-09-01

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

Response of Human Osteoblast to n-HA/PEEK—Quantitative Proteomic Study of Bio-effects of Nano-Hydroxyapatite Composite

NASA Astrophysics Data System (ADS)

Zhao, Minzhi; Li, Haiyun; Liu, Xiaochen; Wei, Jie; Ji, Jianguo; Yang, Shu; Hu, Zhiyuan; Wei, Shicheng

2016-03-01

Nano-sized hydroxyapatite (n-HA) is considered as a bio-active material, which is often mixed into bone implant material, polyetheretherketone (PEEK). To reveal the global protein expression modulations of osteoblast in response to direct contact with the PEEK composite containing high level (40%) nano-sized hydroxyapatite (n-HA/PEEK) and explain its comprehensive bio-effects, quantitative proteomic analysis was conducted on human osteoblast-like cells MG-63 cultured on n-HA/PEEK in comparison with pure PEEK. Results from quantitative proteomic analysis showed that the most enriched categories in the up-regulated proteins were related to calcium ion processes and associated functions while the most enriched categories in the down-regulated proteins were related to RNA process. This enhanced our understanding to the molecular mechanism of the promotion of the cell adhesion and differentiation with the inhibition of the cell proliferation on n-HA/PEEK composite. It also exhibited that although the calcium ion level of incubate environment hadn’t increased, merely the calcium fixed on the surface of material had influence to intracellular calcium related processes, which was also reflect by the higher intracellular Ca2+ concentration of n-HA/PEEK. This study could lead to more comprehensive cognition to the versatile biocompatibility of composite materials. It further proves that proteomics is useful in new bio-effect discovery.

Proteome-wide Light/Dark Modulation of Thiol Oxidation in Cyanobacteria Revealed by Quantitative Site-specific Redox Proteomics*

PubMed Central

Guo, Jia; Nguyen, Amelia Y.; Dai, Ziyu; Su, Dian; Gaffrey, Matthew J.; Moore, Ronald J.; Jacobs, Jon M.; Monroe, Matthew E.; Smith, Richard D.; Koppenaal, David W.; Pakrasi, Himadri B.; Qian, Wei-Jun

2014-01-01

Reversible protein thiol oxidation is an essential regulatory mechanism of photosynthesis, metabolism, and gene expression in photosynthetic organisms. Herein, we present proteome-wide quantitative and site-specific profiling of in vivo thiol oxidation modulated by light/dark in the cyanobacterium Synechocystis sp. PCC 6803, an oxygenic photosynthetic prokaryote, using a resin-assisted thiol enrichment approach. Our proteomic approach integrates resin-assisted enrichment with isobaric tandem mass tag labeling to enable site-specific and quantitative measurements of reversibly oxidized thiols. The redox dynamics of ∼2,100 Cys-sites from 1,060 proteins under light, dark, and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosystem II inhibitor) conditions were quantified. In addition to relative quantification, the stoichiometry or percentage of oxidation (reversibly oxidized/total thiols) for ∼1,350 Cys-sites was also quantified. The overall results revealed broad changes in thiol oxidation in many key biological processes, including photosynthetic electron transport, carbon fixation, and glycolysis. Moreover, the redox sensitivity along with the stoichiometric data enabled prediction of potential functional Cys-sites for proteins of interest. The functional significance of redox-sensitive Cys-sites in NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin (AhpC/TSA family protein Sll1621), and glucose 6-phosphate dehydrogenase was further confirmed with site-specific mutagenesis and biochemical studies. Together, our findings provide significant insights into the broad redox regulation of photosynthetic organisms. PMID:25118246

Response of Human Osteoblast to n-HA/PEEK--Quantitative Proteomic Study of Bio-effects of Nano-Hydroxyapatite Composite.

PubMed

Zhao, Minzhi; Li, Haiyun; Liu, Xiaochen; Wei, Jie; Ji, Jianguo; Yang, Shu; Hu, Zhiyuan; Wei, Shicheng

2016-03-09

Nano-sized hydroxyapatite (n-HA) is considered as a bio-active material, which is often mixed into bone implant material, polyetheretherketone (PEEK). To reveal the global protein expression modulations of osteoblast in response to direct contact with the PEEK composite containing high level (40%) nano-sized hydroxyapatite (n-HA/PEEK) and explain its comprehensive bio-effects, quantitative proteomic analysis was conducted on human osteoblast-like cells MG-63 cultured on n-HA/PEEK in comparison with pure PEEK. Results from quantitative proteomic analysis showed that the most enriched categories in the up-regulated proteins were related to calcium ion processes and associated functions while the most enriched categories in the down-regulated proteins were related to RNA process. This enhanced our understanding to the molecular mechanism of the promotion of the cell adhesion and differentiation with the inhibition of the cell proliferation on n-HA/PEEK composite. It also exhibited that although the calcium ion level of incubate environment hadn't increased, merely the calcium fixed on the surface of material had influence to intracellular calcium related processes, which was also reflect by the higher intracellular Ca(2+) concentration of n-HA/PEEK. This study could lead to more comprehensive cognition to the versatile biocompatibility of composite materials. It further proves that proteomics is useful in new bio-effect discovery.

Quantitative Temporal in Vivo Proteomics Deciphers the Transition of Virus-Driven Myeloid Cells into M2 Macrophages

PubMed Central

2017-01-01

Myeloid cells play a central role in the context of viral eradication, yet precisely how these cells differentiate throughout the course of acute infections is poorly understood. In this study, we have developed a novel quantitative temporal in vivo proteomics (QTiPs) platform to capture proteomic signatures of temporally transitioning virus-driven myeloid cells directly in situ, thus taking into consideration host–virus interactions throughout the course of an infection. QTiPs, in combination with phenotypic, functional, and metabolic analyses, elucidated a pivotal role for inflammatory CD11b+, Ly6G–, Ly6Chigh-low cells in antiviral immune response and viral clearance. Most importantly, the time-resolved QTiPs data set showed the transition of CD11b+, Ly6G–, Ly6Chigh-low cells into M2-like macrophages, which displayed increased antigen-presentation capacities and bioenergetic demands late in infection. We elucidated the pivotal role of myeloid cells in virus clearance and show how these cells phenotypically, functionally, and metabolically undergo a timely transition from inflammatory to M2-like macrophages in vivo. With respect to the growing appreciation for in vivo examination of viral–host interactions and for the role of myeloid cells, this study elucidates the use of quantitative proteomics to reveal the role and response of distinct immune cell populations throughout the course of virus infection. PMID:28768414

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Recent 5-year Findings and Technological Advances in the Proteomic Study of HIV-associated Disorders.

PubMed

Zhang, Lijun; Jia, Xiaofang; Jin, Jun-O; Lu, Hongzhou; Tan, Zhimi

2017-04-01

Human immunodeficiency virus-1 (HIV-1) mainly relies on host factors to complete its life cycle. Hence, it is very important to identify HIV-regulated host proteins. Proteomics is an excellent technique for this purpose because of its high throughput and sensitivity. In this review, we summarized current technological advances in proteomics, including general isobaric tags for relative and absolute quantitation (iTRAQ) and stable isotope labeling by amino acids in cell culture (SILAC), as well as subcellular proteomics and investigation of posttranslational modifications. Furthermore, we reviewed the applications of proteomics in the discovery of HIV-related diseases and HIV infection mechanisms. Proteins identified by proteomic studies might offer new avenues for the diagnosis and treatment of HIV infection and the related diseases. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

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

2016-01-01

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

Quantitative Assays for RAS Pathway Proteins and Phosphorylation States

Cancer.gov

The NCI CPTAC program is applying its expertise in quantitative proteomics to develop assays for RAS pathway proteins. Targets include key phosphopeptides that should increase our understanding of how the RAS pathway is regulated.

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

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

PubMed Central

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

2015-01-01

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

Common and Specific Protein Accumulation Patterns in Different Albino/Pale-Green Mutants Reveals Regulon Organization at the Proteome Level1[W

PubMed Central

Motohashi, Reiko; Rödiger, Anja; Agne, Birgit; Baerenfaller, Katja; Baginsky, Sacha

2012-01-01

Research interest in proteomics is increasingly shifting toward the reverse genetic characterization of gene function at the proteome level. In plants, several distinct gene defects perturb photosynthetic capacity, resulting in the loss of chlorophyll and an albino or pale-green phenotype. Because photosynthesis is interconnected with the entire plant metabolism and its regulation, all albino plants share common characteristics that are determined by the switch from autotrophic to heterotrophic growth. Reverse genetic characterizations of such plants often cannot distinguish between specific consequences of a gene defect from generic effects in response to perturbations in photosynthetic capacity. Here, we set out to define common and specific features of protein accumulation in three different albino/pale-green plant lines. Using quantitative proteomics, we report a common molecular phenotype that connects the loss of photosynthetic capacity with other chloroplast and cellular functions, such as protein folding and stability, plastid protein import, and the expression of stress-related genes. Surprisingly, we do not find significant differences in the expression of key transcriptional regulators, suggesting that substantial regulation occurs at the posttranscriptional level. We examine the influence of different normalization schemes on the quantitative proteomics data and report all identified proteins along with their fold changes and P values in albino plants in comparison with the wild type. Our analysis provides initial guidance for the distinction between general and specific adaptations of the proteome in photosynthesis-impaired plants. PMID:23027667

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.

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

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

Mu, Jun; Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing; Chongqing Key Laboratory of Neurobiology, Chongqing

Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology andmore » proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of ApoB gives insights into the pathogenesis of TBM.« less

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

PubMed Central

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

2010-01-01

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

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Comprehensive and Quantitative Proteomic Analysis of Metamorphosis-Related Proteins in the Veined Rapa Whelk, Rapana venosa.

PubMed

Song, Hao; Wang, Hai-Yan; Zhang, Tao

2016-06-15

Larval metamorphosis of the veined rapa whelk (Rapana venosa) is a pelagic to benthic transition that involves considerable structural and physiological changes. Because metamorphosis plays a pivotal role in R. venosa commercial breeding and natural populations, the endogenous proteins that drive this transition attract considerable interest. This study is the first to perform a comprehensive and quantitative proteomic analysis related to metamorphosis in a marine gastropod. We analyzed the proteomes of competent R. venosa larvae and post-larvae, resulting in the identification of 5312 proteins, including 470 that were downregulated and 668 that were upregulated after metamorphosis. The differentially expressed proteins reflected multiple processes involved in metamorphosis, including cytoskeleton and cell adhesion, ingestion and digestion, stress response and immunity, as well as specific tissue development. Our data improve understanding of the physiological traits controlling R. venosa metamorphosis and provide a solid basis for further study.

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.

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.

Bovine milk proteome: Quantitative changes in normal milk exosomes, milk fat globule membranes and whey proteomes resulting from Staphylococcus aureus mastitis

USDA-ARS?s Scientific Manuscript database

Knowledge of milk protein composition/expression in healthy cows and cows with mastitis will provide information important for the dairy food industry, mammary biology and immune function in the mammary gland. To facilitate maximum protein discovery, milk was fractioned into whey, milk fat globule ...

Statistical issues in the design and planning of proteomic profiling experiments.

PubMed

Cairns, David A

2015-01-01

The statistical design of a clinical proteomics experiment is a critical part of well-undertaken investigation. Standard concepts from experimental design such as randomization, replication and blocking should be applied in all experiments, and this is possible when the experimental conditions are well understood by the investigator. The large number of proteins simultaneously considered in proteomic discovery experiments means that determining the number of required replicates to perform a powerful experiment is more complicated than in simple experiments. However, by using information about the nature of an experiment and making simple assumptions this is achievable for a variety of experiments useful for biomarker discovery and initial validation.

Proteomic dataset of the sea urchin Paracentrotus lividus adhesive organs and secreted adhesive.

PubMed

Lebesgue, Nicolas; da Costa, Gonçalo; Ribeiro, Raquel Mesquita; Ribeiro-Silva, Cristina; Martins, Gabriel G; Matranga, Valeria; Scholten, Arjen; Cordeiro, Carlos; Heck, Albert J R; Santos, Romana

2016-06-01

Sea urchins have specialized adhesive organs called tube feet, which mediate strong but reversible adhesion. Tube feet are composed by a disc, producing adhesive and de-adhesive secretions for substratum attachment, and a stem for movement. After detachment the secreted adhesive remains bound to the substratum as a footprint. Recently, a label-free quantitative proteomic approach coupled with the latest mass-spectrometry technology was used to analyze the differential proteome of Paracentrotus lividus adhesive organ, comparing protein expression levels in the tube feet adhesive part (the disc) versus the non-adhesive part (the stem), and also to profile the proteome of the secreted adhesive (glue). This data article contains complementary figures and results related to the research article "Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: a quantitative proteomics approach" (Lebesgue et al., 2016) [1]. Here we provide a dataset of 1384 non-redundant proteins, their fragmented peptides and expression levels, resultant from the analysis of the tube feet differential proteome. Of these, 163 highly over-expressed tube feet disc proteins (>3-fold), likely representing the most relevant proteins for sea urchin reversible adhesion, were further annotated in order to determine the potential functions. In addition, we provide a dataset of 611 non-redundant proteins identified in the secreted adhesive proteome, as well as their functional annotation and grouping in 5 major protein groups related with adhesive exocytosis, and microbial protection. This list was further analyzed to identify the most abundant protein groups and pinpoint putative adhesive proteins, such as Nectin, the most abundant adhesive protein in sea urchin glue. The obtained data uncover the key proteins involved in sea urchins reversible adhesion, representing a step forward to the development of new wet-effective bio-inspired adhesives.

Venom-gland transcriptomics and venom proteomics of the black-back scorpion (Hadrurus spadix) reveal detectability challenges and an unexplored realm of animal toxin diversity.

PubMed

Rokyta, Darin R; Ward, Micaiah J

2017-03-15

The order Scorpiones is one of the most ancient and diverse lineages of venomous animals, having originated approximately 430 million years ago and diversified into 14 extant families. Although partial venom characterizations have been described for numerous scorpion species, we provided the first quantitative transcriptome/proteome comparison for a scorpion species using single-animal approaches. We sequenced the venom-gland transcriptomes of a male and female black-back scorpion (Hadrurus spadix) from the family Caraboctonidae using the Illumina sequencing platform and conducted independent quantitative mass-spectrometry analyses of their venoms. We identified 79 proteomically confirmed venom proteins, an additional 69 transcripts with homology to toxins from other species, and 596 nontoxin proteins expressed at high levels in the venom glands. The venom of H. spadix was rich in antimicrobial peptides, K + -channel toxins, and several classes of peptidases. However, the most diverse and one of the most abundant classes of putative toxins could not be assigned even a tentative functional role on the basis of homology, indicating that this venom contained a wealth of previously unexplored animal toxin diversity. We found good agreement between both transcriptomic and proteomic abundances across individuals, but transcriptomic and proteomic abundandances differed substantially within each individual. Small peptide toxins such as K + -channel toxins and antimicrobial peptides proved challenging to detect proteomically, at least in part due to the significant proteolytic processing involved in their maturation. In addition, we found a significant tendency for our proteomic approach to overestimate the abundances of large putative toxins and underestimate the abundances of smaller toxins. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Functional Network of the Arabidopsis Plastoglobule Proteome Based on Quantitative Proteomics and Genome-Wide Coexpression Analysis1[C][W][OA

PubMed Central

Lundquist, Peter K.; Poliakov, Anton; Bhuiyan, Nazmul H.; Zybailov, Boris; Sun, Qi; van Wijk, Klaas J.

2012-01-01

Plastoglobules (PGs) in chloroplasts are thylakoid-associated monolayer lipoprotein particles containing prenyl and neutral lipids and several dozen proteins mostly with unknown functions. An integrated view of the role of the PG is lacking. Here, we better define the PG proteome and provide a conceptual framework for further studies. The PG proteome from Arabidopsis (Arabidopsis thaliana) leaf chloroplasts was determined by mass spectrometry of isolated PGs and quantitative comparison with the proteomes of unfractionated leaves, thylakoids, and stroma. Scanning electron microscopy showed the purity and size distribution of the isolated PGs. Compared with previous PG proteome analyses, we excluded several proteins and identified six new PG proteins, including an M48 metallopeptidase and two Absence of bc1 complex (ABC1) atypical kinases, confirmed by immunoblotting. This refined PG proteome consisted of 30 proteins, including six ABC1 kinases and seven fibrillins together comprising more than 70% of the PG protein mass. Other fibrillins were located predominantly in the stroma or thylakoid and not in PGs; we discovered that this partitioning can be predicted by their isoelectric point and hydrophobicity. A genome-wide coexpression network for the PG genes was then constructed from mRNA expression data. This revealed a modular network with four distinct modules that each contained at least one ABC1K and/or fibrillin gene. Each module showed clear enrichment in specific functions, including chlorophyll degradation/senescence, isoprenoid biosynthesis, plastid proteolysis, and redox regulators and phosphoregulators of electron flow. We propose a new testable model for the PGs, in which sets of genes are associated with specific PG functions. PMID:22274653

Proteomic dataset of the sea urchin Paracentrotus lividus adhesive organs and secreted adhesive

PubMed Central

Lebesgue, Nicolas; da Costa, Gonçalo; Ribeiro, Raquel Mesquita; Ribeiro-Silva, Cristina; Martins, Gabriel G.; Matranga, Valeria; Scholten, Arjen; Cordeiro, Carlos; Heck, Albert J.R.; Santos, Romana

2016-01-01

Sea urchins have specialized adhesive organs called tube feet, which mediate strong but reversible adhesion. Tube feet are composed by a disc, producing adhesive and de-adhesive secretions for substratum attachment, and a stem for movement. After detachment the secreted adhesive remains bound to the substratum as a footprint. Recently, a label-free quantitative proteomic approach coupled with the latest mass-spectrometry technology was used to analyze the differential proteome of Paracentrotus lividus adhesive organ, comparing protein expression levels in the tube feet adhesive part (the disc) versus the non-adhesive part (the stem), and also to profile the proteome of the secreted adhesive (glue). This data article contains complementary figures and results related to the research article “Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: a quantitative proteomics approach” (Lebesgue et al., 2016) [1]. Here we provide a dataset of 1384 non-redundant proteins, their fragmented peptides and expression levels, resultant from the analysis of the tube feet differential proteome. Of these, 163 highly over-expressed tube feet disc proteins (>3-fold), likely representing the most relevant proteins for sea urchin reversible adhesion, were further annotated in order to determine the potential functions. In addition, we provide a dataset of 611 non-redundant proteins identified in the secreted adhesive proteome, as well as their functional annotation and grouping in 5 major protein groups related with adhesive exocytosis, and microbial protection. This list was further analyzed to identify the most abundant protein groups and pinpoint putative adhesive proteins, such as Nectin, the most abundant adhesive protein in sea urchin glue. The obtained data uncover the key proteins involved in sea urchins reversible adhesion, representing a step forward to the development of new wet-effective bio-inspired adhesives. PMID:27182547

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

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

Cancer.gov

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

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

PubMed Central

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

2015-01-01

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

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.

Quantitative Secretome Analysis of Activated Jurkat Cells Using Click Chemistry-Based Enrichment of Secreted Glycoproteins.

PubMed

Witzke, Kathrin E; Rosowski, Kristin; Müller, Christian; Ahrens, Maike; Eisenacher, Martin; Megger, Dominik A; Knobloch, Jürgen; Koch, Andrea; Bracht, Thilo; Sitek, Barbara

2017-01-06

Quantitative secretome analyses are a high-performance tool for the discovery of physiological and pathophysiological changes in cellular processes. However, serum supplements in cell culture media limit secretome analyses, but serum depletion often leads to cell starvation and consequently biased results. To overcome these limiting factors, we investigated a model of T cell activation (Jurkat cells) and performed an approach for the selective enrichment of secreted proteins from conditioned medium utilizing metabolic marking of newly synthesized glycoproteins. Marked glycoproteins were labeled via bioorthogonal click chemistry and isolated by affinity purification. We assessed two labeling compounds conjugated with either biotin or desthiobiotin and the respective secretome fractions. 356 proteins were quantified using the biotin probe and 463 using desthiobiotin. 59 proteins were found differentially abundant (adjusted p-value ≤0.05, absolute fold change ≥1.5) between inactive and activated T cells using the biotin method and 86 using the desthiobiotin approach, with 31 mutual proteins cross-verified by independent experiments. Moreover, we analyzed the cellular proteome of the same model to demonstrate the benefit of secretome analyses and provide comprehensive data sets of both. 336 proteins (61.3%) were quantified exclusively in the secretome. Data are available via ProteomeXchange with identifier PXD004280.

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

PubMed

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

2018-01-01

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

Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

PubMed

Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

2015-01-01

Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.

Tyrosine-Nitrated Proteins: Proteomic and Bioanalytical Aspects

PubMed Central

Batthyány, Carlos; Bartesaghi, Silvina; Mastrogiovanni, Mauricio; Lima, Analía; Demicheli, Verónica

2017-01-01

Abstract Significance: “Nitroproteomic” is under active development, as 3-nitrotyrosine in proteins constitutes a footprint left by the reactions of nitric oxide-derived oxidants that are usually associated to oxidative stress conditions. Moreover, protein tyrosine nitration can cause structural and functional changes, which may be of pathophysiological relevance for human disease conditions. Biological protein tyrosine nitration is a free radical process involving the intermediacy of tyrosyl radicals; in spite of being a nonenzymatic process, nitration is selectively directed toward a limited subset of tyrosine residues. Precise identification and quantitation of 3-nitrotyrosine in proteins has represented a “tour de force” for researchers. Recent Advances: A small number of proteins are preferential targets of nitration (usually less than 100 proteins per proteome), contrasting with the large number of proteins modified by other post-translational modifications such as phosphorylation, acetylation, and, notably, S-nitrosation. Proteomic approaches have revealed key features of tyrosine nitration both in vivo and in vitro, including selectivity, site specificity, and effects in protein structure and function. Critical Issues: Identification of 3-nitrotyrosine-containing proteins and mapping nitrated residues is challenging, due to low abundance of this oxidative modification in biological samples and its unfriendly behavior in mass spectrometry (MS)-based technologies, that is, MALDI, electrospray ionization, and collision-induced dissociation. Future Directions: The use of (i) classical two-dimensional electrophoresis with immunochemical detection of nitrated proteins followed by protein ID by regular MS/MS in combination with (ii) immuno-enrichment of tyrosine-nitrated peptides and (iii) identification of nitrated peptides by a MIDAS™ experiment is arising as a potent methodology to unambiguously map and quantitate tyrosine-nitrated proteins in vivo. Antioxid. Redox Signal. 26, 313–328. PMID:27324931

Quantitative changes in proteins responsible for flavonoid and anthocyanin biosynthesis in strawberry fruit at different ripening stages: A targeted quantitative proteomic investigation employing multiple reaction monitoring.

PubMed

Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong

2015-06-03

To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides and proteins provided reliable design and validation of quantitative approaches using SRM on targeted proteins proposed involved in strawberry fruit. Our data revealed the identifying candidate proteins and their quantitative changes in relation to fruit ripening and flavonoids and anthocyanin biosynthesis and regulation. More importantly, this quantitative proteomic data is also compared with chemical analysis to reveal possible control levels of this important quality trait. Although, MRM approach is not new in plant biology research, the application has been very rare. This is the first systematic multi-targeted interrogation of the possible regulation of entire pathway of flavonoids and anthocyanin biosynthesis in strawberry fruit at different ripening stages using quantitative MRM technique on mass spectrometry. Our results demonstrate the power of targeted quantitative mass spectrometry data for analysis of proteins in biological regulation. These results indicate that distinct and diverse control of flavonoids and anthocyanin biosynthesis mechanisms at metabolism and proteins levels. This important and complementary knowledge will be useful for systematically characterizing the flavonoids and anthocyanin biosynthesis pathway of any fruit/plant species. Copyright © 2015. Published by Elsevier B.V.

Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

PubMed

Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

2016-04-29

Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

PubMed Central

Zhang, Xi

2015-01-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834

Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

PubMed Central

Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

2014-01-01

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

PubMed

Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

2013-12-06

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

Quantitative proteome analysis of plasma microparticles for the characterization of HCV-induced hepatic cirrhosis and hepatocellular carcinoma.

PubMed

Taleb, Raghda Saad Zaghloul; Moez, Pacint; Younan, Doreen; Eisenacher, Martin; Tenbusch, Matthias; Sitek, Barbara; Bracht, Thilo

2017-12-01

Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor and a leading cause of cancer-related deaths worldwide. Cirrhosis induced by hepatitis-C virus (HCV) infection is the most critical risk factor for HCC. However, the mechanism of HCV-induced carcinogenesis is not fully understood. Plasma microparticles (PMP) contribute to numerous physiological and pathological processes and contain proteins whose composition correlates to the respective pathophysiological conditions. We analyzed PMP from 22 HCV-induced cirrhosis patients, 16 HCV-positive HCC patients with underlying cirrhosis and 18 healthy controls. PMP were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS. We identified 840 protein groups and quantified 507 proteins. 159 proteins were found differentially abundant between the three experimental groups. PMP in both disease entities displayed remarkable differences in the proteome composition compared to healthy controls. Conversely, the proteome difference between both diseases was minimal. GO analysis revealed that PMP isolated from both diseases were significantly enriched in proteins involved in complement activation, while endopeptidase activity was downregulated exclusively in HCC patients. This study reports for the first time a quantitative proteome analysis for PMP from patients with HCV-induced cirrhosis and HCC. Data are available via ProteomeXchange with identifier PXD005777. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Population-specific plasma proteomes of marine and freshwater three-spined sticklebacks (Gasterosteus aculeatus).

PubMed

Kültz, Dietmar; Li, Johnathon; Zhang, Xuezhen; Villarreal, Fernando; Pham, Tuan; Paguio, Darlene

2015-12-01

Molecular phenotypes that distinguish resident marine (Bodega Harbor) from landlocked freshwater (FW, Lake Solano) three-spined sticklebacks were revealed by label-free quantitative proteomics. Secreted plasma proteins involved in lipid transport, blood coagulation, proteolysis, plasminogen-activating cascades, extracellular stimulus responses, and immunity are most abundant in this species. Globulins and albumins are much less abundant than in mammalian plasma. Unbiased quantitative proteome profiling identified 45 highly population-specific plasma proteins. Population-specific abundance differences were validated by targeted proteomics based on data-independent acquisition. Gene ontology enrichment analyses and known functions of population-specific plasma proteins indicate enrichment of processes controlling cell adhesion, tissue remodeling, proteolytic processing, and defense signaling in marine sticklebacks. Moreover, fetuin B and leukocyte cell derived chemotaxin 2 are much more abundant in marine fish. These proteins promote bone morphogenesis and likely contribute to population-specific body armor differences. Plasma proteins enriched in FW fish promote translation, heme biosynthesis, and lipid transport, suggesting a greater presence of plasma microparticles. Many prominent population-specific plasma proteins (e.g. apoptosis-associated speck-like protein containing a CARD) lack any homolog of known function or adequate functional characterization. Their functional characterization and the identification of population-specific environmental contexts and selective pressures that cause plasma proteome diversification are future directions emerging from this study. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

iTRAQ-Based Quantitative Proteomic Analysis of the Initiation of Head Regeneration in Planarians.

PubMed

Geng, Xiaofang; Wang, Gaiping; Qin, Yanli; Zang, Xiayan; Li, Pengfei; Geng, Zhi; Xue, Deming; Dong, Zimei; Ma, Kexue; Chen, Guangwen; Xu, Cunshuan

2015-01-01

The planarian Dugesia japonica has amazing ability to regenerate a head from the anterior ends of the amputated stump with maintenance of the original anterior-posterior polarity. Although planarians present an attractive system for molecular investigation of regeneration and research has focused on clarifying the molecular mechanism of regeneration initiation in planarians at transcriptional level, but the initiation mechanism of planarian head regeneration (PHR) remains unclear at the protein level. Here, a global analysis of proteome dynamics during the early stage of PHR was performed using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy, and our data are available via ProteomeXchange with identifier PXD002100. The results showed that 162 proteins were differentially expressed at 2 h and 6 h following amputation. Furthermore, the analysis of expression patterns and functional enrichment of the differentially expressed proteins showed that proteins involved in muscle contraction, oxidation reduction and protein synthesis were up-regulated in the initiation of PHR. Moreover, ingenuity pathway analysis showed that predominant signaling pathways such as ILK, calcium, EIF2 and mTOR signaling which were associated with cell migration, cell proliferation and protein synthesis were likely to be involved in the initiation of PHR. The results for the first time demonstrated that muscle contraction and ILK signaling might played important roles in the initiation of PHR at the global protein level. The findings of this research provide a molecular basis for further unraveling the mechanism of head regeneration initiation in planarians.

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 Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

PubMed Central

Megger, Dominik A.; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus. PMID:28959263

Proteomic Analyses of the Effects of Drugs of Abuse on Monocyte-Derived Mature Dendritic Cells

PubMed Central

Reynolds, Jessica L.; Mahajan, Supriya D.; Aalinkeel, Ravikunar; Nair, B.; Sykes, Donald E.; Schwartz, Stanley A.

2010-01-01

Drug abuse has become a global health concern. Understanding how drug abuse modulates the immune system and how the immune system responds to pathogens associated with drug abuse, such hepatitis C virus (HCV) and human immunodeficiency virus (HIV-1), can be assessed by an integrated approach comparing proteomic analyses and quantitation of gene expression. Two-dimensional (2D) difference gel electrophoresis was used to determine the molecular mechanisms underlying the proteomic changes that alter normal biological processes when monocyte-derived mature dendritic cells were treated with cocaine or methamphetamine. Both drugs differentially regulated the expression of several functional classes of proteins including those that modulate apoptosis, protein folding, protein kinase activity, and metabolism and proteins that function as intracellular signal transduction molecules. Proteomic data were validated using a combination of quantitative, real-time PCR and Western blot analyses. These studies will help to identify the molecular mechanisms, including the expression of several functionally important classes of proteins that have emerged as potential mediators of pathogenesis. These proteins may predispose immunocompetent cells, including dendritic cells, to infection with viruses such as HCV and HIV-1, which are associated with drug abuse. PMID:19811410

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry*

PubMed Central

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.; Monroe, Matthew E.; Orton, Daniel J.; Ibrahim, Yehia M.; Gritsenko, Marina A.; Clauss, Therese R. W.; Shukla, Anil K.; Moore, Ronald J.; Purvine, Samuel O.; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S.; Smith, Richard D.

2016-01-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. PMID:27670688

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression.

PubMed

Megger, Dominik A; Philipp, Jos; Le-Trilling, Vu Thuy Khanh; Sitek, Barbara; Trilling, Mirko

2017-01-01

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

The quantitative and condition-dependent Escherichia coli proteome

PubMed Central

Schmidt, Alexander; Kochanowski, Karl; Vedelaar, Silke; Ahrné, Erik; Volkmer, Benjamin; Callipo, Luciano; Knoops, Kèvin; Bauer, Manuel; Aebersold, Ruedi; Heinemann, Matthias

2016-01-01

Measuring precise concentrations of proteins can provide insights into biological processes. Here, we use efficient protein extraction and sample fractionation and state-of-the-art quantitative mass spectrometry techniques to generate a comprehensive, condition-dependent protein abundance map of Escherichia coli. We measure cellular protein concentrations for 55% of predicted E. coli genes (>2300 proteins) under 22 different experimental conditions and identify methylation and N-terminal protein acetylations previously not known to be prevalent in bacteria. We uncover system-wide proteome allocation, expression regulation, and post-translational adaptations. These data provide a valuable resource for the systems biology and broader E. coli research communities. PMID:26641532

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

PubMed

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS(3) acquisition.

PubMed

Evans, Adam R; Robinson, Renã A S

2013-11-01

Recently, we reported a novel proteomics quantitation scheme termed "combined precursor isotopic labeling and isobaric tagging (cPILOT)" that allows for the identification and quantitation of nitrated peptides in as many as 12-16 samples in a single experiment. cPILOT offers enhanced multiplexing and posttranslational modification specificity, however excludes global quantitation for all peptides present in a mixture and underestimates reporter ion ratios similar to other isobaric tagging methods due to precursor co-isolation. Here, we present a novel chemical workflow for cPILOT that can be used for global tagging of all peptides in a mixture. Specifically, through low pH precursor dimethylation of tryptic or LysC peptides followed by high pH tandem mass tags, the same reporter ion can be used twice in a single experiment. Also, to improve triple-stage mass spectrometry (MS(3) ) data acquisition, a selective MS(3) method that focuses on product selection of the y1 fragment of lysine-terminated peptides is incorporated into the workflow. This novel cPILOT workflow has potential for global peptide quantitation that could lead to enhanced sample multiplexing and increase the number of quantifiable spectra obtained from MS(3) acquisition methods. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitation of peptides from non-invasive skin tapings using isotope dilution and tandem mass spectrometry.

PubMed

Reisdorph, Nichole; Armstrong, Michael; Powell, Roger; Quinn, Kevin; Legg, Kevin; Leung, Donald; Reisdorph, Rick

2018-05-01

Previous work from our laboratories utilized a novel skin taping method and mass spectrometry-based proteomics to discover clinical biomarkers of skin conditions; these included atopic dermatitis, Staphylococcus aureus colonization, and eczema herpeticum. While suitable for discovery purposes, semi-quantitative proteomics is generally time-consuming and expensive. Furthermore, depending on the method used, discovery-based proteomics can result in high variation and inadequate sensitivity to detect low abundant peptides. Therefore, we strove to develop a rapid, sensitive, and reproducible method to quantitate disease-related proteins from skin tapings. We utilized isotopically-labeled peptides and tandem mass spectrometry to obtain absolute quantitation values on 14 peptides from 7 proteins; these proteins had shown previous importance in skin disease. The method demonstrated good reproducibility, dynamic range, and linearity (R 2  > 0.993) when n = 3 standards were analyzed across 0.05-2.5 pmol. The method was used to determine if differences exist between skin proteins in a small group of atopic versus non-atopic individuals (n = 12). While only minimal differences were found, peptides were detected in all samples and exhibited good correlation between peptides for 5 of the 7 proteins (R 2  = 0.71-0.98). This method can be applied to larger cohorts to further establish the relationships of these proteins to skin disease. Copyright © 2017. Published by Elsevier B.V.

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.

Regulation of Lipid Metabolism by Dicer Revealed through SILAC Mice

PubMed Central

Huang, Tai-Chung; Saharabuddhe, Nandini A.; Kim, Min-Sik; Getnet, Derese; Yang, Yi; Peterson, Jonathan M.; Ghosh, Bidyut; Chaerkady, Raghothama; Leach, Steven D.; Marchionni, Luigi; Wong, G. William; Pandey, Akhilesh

2012-01-01

Dicer is a ribonuclease whose major role is to generate mature microRNAs although additional functions have been proposed. Deletion of Dicer leads to embryonic lethality in mice. To study the role of Dicer in adults, we generated mice in which administration of tamoxifen induces deletion of Dicer. Surprisingly, disruption of Dicer in adult mice induced lipid accumulation in the small intestine. To dissect the underlying mechanisms, we carried out miRNA, mRNA and proteomic profiling of small intestine. The proteomic analysis was done using mice metabolically labeled with heavy lysine (SILAC mice) for an in vivo readout. We identified 646 proteins of which 80 were upregulated >2-fold and 75 were downregulated. Consistent with the accumulation of lipids, Dicer disruption caused a marked decrease of microsomal triglyceride transfer protein, long-chain fatty acyl-CoA ligase 5, fatty acid binding protein, and very-long-chain fatty acyl-CoA dehydrogenase, among others. We validated these results using multiple reaction monitoring (MRM) experiments by targeting proteotypic peptides. Our data reveal a previously unappreciated role of Dicer in lipid metabolism. These studies demonstrate a systems biology approach by integrating mouse models, metabolic labeling, gene expression profiling and quantitative proteomics can be a powerful tool for understanding complex biological systems. PMID:22313051

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

PubMed

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

2013-11-01

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

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

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

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.

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

Halogenated peptides as internal standards (H-PINS): introduction of an MS-based internal standard set for liquid chromatography-mass spectrometry.

PubMed

Mirzaei, Hamid; Brusniak, Mi-Youn; Mueller, Lukas N; Letarte, Simon; Watts, Julian D; Aebersold, Ruedi

2009-08-01

As the application for quantitative proteomics in the life sciences has grown in recent years, so has the need for more robust and generally applicable methods for quality control and calibration. The reliability of quantitative proteomics is tightly linked to the reproducibility and stability of the analytical platforms, which are typically multicomponent (e.g. sample preparation, multistep separations, and mass spectrometry) with individual components contributing unequally to the overall system reproducibility. Variations in quantitative accuracy are thus inevitable, and quality control and calibration become essential for the assessment of the quality of the analyses themselves. Toward this end, the use of internal standards cannot only assist in the detection and removal of outlier data acquired by an irreproducible system (quality control) but can also be used for detection of changes in instruments for their subsequent performance and calibration. Here we introduce a set of halogenated peptides as internal standards. The peptides are custom designed to have properties suitable for various quality control assessments, data calibration, and normalization processes. The unique isotope distribution of halogenated peptides makes their mass spectral detection easy and unambiguous when spiked into complex peptide mixtures. In addition, they were designed to elute sequentially over an entire aqueous to organic LC gradient and to have m/z values within the commonly scanned mass range (300-1800 Da). In a series of experiments in which these peptides were spiked into an enriched N-glycosite peptide fraction (i.e. from formerly N-glycosylated intact proteins in their deglycosylated form) isolated from human plasma, we show the utility and performance of these halogenated peptides for sample preparation and LC injection quality control as well as for retention time and mass calibration. Further use of the peptides for signal intensity normalization and retention time synchronization for selected reaction monitoring experiments is also demonstrated.

Halogenated Peptides as Internal Standards (H-PINS)

PubMed Central

Mirzaei, Hamid; Brusniak, Mi-Youn; Mueller, Lukas N.; Letarte, Simon; Watts, Julian D.; Aebersold, Ruedi

2009-01-01

As the application for quantitative proteomics in the life sciences has grown in recent years, so has the need for more robust and generally applicable methods for quality control and calibration. The reliability of quantitative proteomics is tightly linked to the reproducibility and stability of the analytical platforms, which are typically multicomponent (e.g. sample preparation, multistep separations, and mass spectrometry) with individual components contributing unequally to the overall system reproducibility. Variations in quantitative accuracy are thus inevitable, and quality control and calibration become essential for the assessment of the quality of the analyses themselves. Toward this end, the use of internal standards cannot only assist in the detection and removal of outlier data acquired by an irreproducible system (quality control) but can also be used for detection of changes in instruments for their subsequent performance and calibration. Here we introduce a set of halogenated peptides as internal standards. The peptides are custom designed to have properties suitable for various quality control assessments, data calibration, and normalization processes. The unique isotope distribution of halogenated peptides makes their mass spectral detection easy and unambiguous when spiked into complex peptide mixtures. In addition, they were designed to elute sequentially over an entire aqueous to organic LC gradient and to have m/z values within the commonly scanned mass range (300–1800 Da). In a series of experiments in which these peptides were spiked into an enriched N-glycosite peptide fraction (i.e. from formerly N-glycosylated intact proteins in their deglycosylated form) isolated from human plasma, we show the utility and performance of these halogenated peptides for sample preparation and LC injection quality control as well as for retention time and mass calibration. Further use of the peptides for signal intensity normalization and retention time synchronization for selected reaction monitoring experiments is also demonstrated. PMID:19411281

Quantitative proteomics reveals the central changes of wheat in response to powdery mildew.

PubMed

Fu, Ying; Zhang, Hong; Mandal, Siddikun Nabi; Wang, Changyou; Chen, Chunhuan; Ji, Wanquan

2016-01-01

Powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most important crop diseases, causing severe economic losses to wheat production worldwide. However, there are few reports about the proteomic response to Bgt infection in resistant wheat. Hence, quantitative proteomic analysis of N9134, a resistant wheat line, was performed to explore the molecular mechanism of wheat in defense against Bgt. Comparing the leaf proteins of Bgt-inoculated N9134 with that of mock-inoculated controls, a total of 2182 protein-species were quantified by iTRAQ at 24, 48 and 72h postinoculation (hpi) with Bgt, of which 394 showed differential accumulation. These differentially accumulated protein-species (DAPs) mainly included pathogenesis-related (PR) polypeptides, oxidative stress responsive proteins and components involved in primary metabolic pathways. KEGG enrichment analysis showed that phenylpropanoid biosynthesis, phenylalanine metabolism and photosynthesis-antenna proteins were the key pathways in response to Bgt infection. InterProScan 5 and the Gibbs Motif Sampler cluster 394 DAPs into eight conserved motifs, which shared leucine repeats and histidine sites in the sequence motifs. Moreover, eight separate protein-protein interaction (PPI) networks were predicted from STRING database. This study provides a powerful platform for further exploration of the molecular mechanism underlying resistant wheat responding to Bgt. Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive pathogenic disease in wheat-producing regions worldwide, resulting in severe yield reductions. Although many resistant wheat varieties have been cultivated, there are few reports about the proteomic response to Bgt infection in resistant wheat. Therefore, an iTRAQ-based quantitative proteomic analysis of a resistant wheat line (N9134) in response to Bgt infection has been performed. This paper provides new insights into the underlying molecular mechanism of wheat in response to Bgt. The proteomic analysis can significantly narrow the field of potential defense-related protein-species, and is conducive to recognize the critical or effector protein under Bgt infection more precisely. Taken together, large amounts of high-throughput data provide a powerful platform for further exploration of the molecular mechanism on wheat-Bgt interactions. Copyright © 2015 Elsevier B.V. All rights reserved.

Global dynamics of the Escherichia coli proteome and phosphoproteome during growth in minimal medium.

PubMed

Soares, Nelson C; Spät, Philipp; Krug, Karsten; Macek, Boris

2013-06-07

Recent phosphoproteomics studies have generated relatively large data sets of bacterial proteins phosphorylated on serine, threonine, and tyrosine, implicating this type of phosphorylation in the regulation of vital processes of a bacterial cell; however, most phosphoproteomics studies in bacteria were so far qualitative. Here we applied stable isotope labeling by amino acids in cell culture (SILAC) to perform a quantitative analysis of proteome and phosphoproteome dynamics of Escherichia coli during five distinct phases of growth in the minimal medium. Combining two triple-SILAC experiments, we detected a total of 2118 proteins and quantified relative dynamics of 1984 proteins in all measured phases of growth, including 570 proteins associated with cell wall and membrane. In the phosphoproteomic experiment, we detected 150 Ser/Thr/Tyr phosphorylation events, of which 108 were localized to a specific amino acid residue and 76 were quantified in all phases of growth. Clustering analysis of SILAC ratios revealed distinct sets of coregulated proteins for each analyzed phase of growth and overrepresentation of membrane proteins in transition between exponential and stationary phases. The proteomics data indicated that proteins related to stress response typically associated with the stationary phase, including RpoS-dependent proteins, had increasing levels already during earlier phases of growth. Application of SILAC enabled us to measure median occupancies of phosphorylation sites, which were generally low (<12%). Interestingly, the phosphoproteome analysis showed a global increase of protein phosphorylation levels in the late stationary phase, pointing to a likely role of this modification in later phases of growth.

Standardized Profiling of The Membrane-Enriched Proteome of Mouse Dorsal Root Ganglia (DRG) Provides Novel Insights Into Chronic Pain.

PubMed

Rouwette, Tom; Sondermann, Julia; Avenali, Luca; Gomez-Varela, David; Schmidt, Manuela

2016-06-01

Chronic pain is a complex disease with limited treatment options. Several profiling efforts have been employed with the aim to dissect its molecular underpinnings. However, generated results are often inconsistent and nonoverlapping, which is largely because of inherent technical constraints. Emerging data-independent acquisition (DIA)-mass spectrometry (MS) has the potential to provide unbiased, reproducible and quantitative proteome maps - a prerequisite for standardization among experiments. Here, we designed a DIA-based proteomics workflow to profile changes in the abundance of dorsal root ganglia (DRG) proteins in two mouse models of chronic pain, inflammatory and neuropathic. We generated a DRG-specific spectral library containing 3067 DRG proteins, which enables their standardized quantification by means of DIA-MS in any laboratory. Using this resource, we profiled 2526 DRG proteins in each biological replicate of both chronic pain models and respective controls with unprecedented reproducibility. We detected numerous differentially regulated proteins, the majority of which exhibited pain model-specificity. Our approach recapitulates known biology and discovers dozens of proteins that have not been characterized in the somatosensory system before. Functional validation experiments and analysis of mouse pain behaviors demonstrate that indeed meaningful protein alterations were discovered. These results illustrate how the application of DIA-MS can open new avenues to achieve the long-awaited standardization in the molecular dissection of pathologies of the somatosensory system. Therefore, our findings provide a valuable framework to qualitatively extend our understanding of chronic pain and somatosensation. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Longitudinal Multiplexed Measurement of Quantitative Proteomic Signatures in Mouse Lymphoma Models Using Magneto-Nanosensors

PubMed Central

Lee, Jung-Rok; Appelmann, Iris; Miething, Cornelius; Shultz, Tyler O.; Ruderman, Daniel; Kim, Dokyoon; Mallick, Parag; Lowe, Scott W.; Wang, Shan X.

2018-01-01

Cancer proteomics is the manifestation of relevant biological processes in cancer development. Thus, it reflects the activities of tumor cells, host-tumor interactions, and systemic responses to cancer therapy. To understand the causal effects of tumorigenesis or therapeutic intervention, longitudinal studies are greatly needed. However, most of the conventional mouse experiments are unlikely to accommodate frequent collection of serum samples with a large enough volume for multiple protein assays towards single-object analysis. Here, we present a technique based on magneto-nanosensors to longitudinally monitor the protein profiles in individual mice of lymphoma models using a small volume of a sample for multiplex assays. Methods: Drug-sensitive and -resistant cancer cell lines were used to develop the mouse models that render different outcomes upon the drug treatment. Two groups of mice were inoculated with each cell line, and treated with either cyclophosphamide or vehicle solution. Serum samples taken longitudinally from each mouse in the groups were measured with 6-plex magneto-nanosensor cytokine assays. To find the origin of IL-6, experiments were performed using IL-6 knock-out mice. Results: The differences in serum IL-6 and GCSF levels between the drug-treated and untreated groups were revealed by the magneto-nanosensor measurement on individual mice. Using the multiplex assays and mouse models, we found that IL-6 is secreted by the host in the presence of tumor cells upon the drug treatment. Conclusion: The multiplex magneto-nanosensor assays enable longitudinal proteomic studies on mouse tumor models to understand tumor development and therapy mechanisms more precisely within a single biological object. PMID:29507628

Longitudinal Multiplexed Measurement of Quantitative Proteomic Signatures in Mouse Lymphoma Models Using Magneto-Nanosensors.

PubMed

Lee, Jung-Rok; Appelmann, Iris; Miething, Cornelius; Shultz, Tyler O; Ruderman, Daniel; Kim, Dokyoon; Mallick, Parag; Lowe, Scott W; Wang, Shan X

2018-01-01

Cancer proteomics is the manifestation of relevant biological processes in cancer development. Thus, it reflects the activities of tumor cells, host-tumor interactions, and systemic responses to cancer therapy. To understand the causal effects of tumorigenesis or therapeutic intervention, longitudinal studies are greatly needed. However, most of the conventional mouse experiments are unlikely to accommodate frequent collection of serum samples with a large enough volume for multiple protein assays towards single-object analysis. Here, we present a technique based on magneto-nanosensors to longitudinally monitor the protein profiles in individual mice of lymphoma models using a small volume of a sample for multiplex assays. Methods: Drug-sensitive and -resistant cancer cell lines were used to develop the mouse models that render different outcomes upon the drug treatment. Two groups of mice were inoculated with each cell line, and treated with either cyclophosphamide or vehicle solution. Serum samples taken longitudinally from each mouse in the groups were measured with 6-plex magneto-nanosensor cytokine assays. To find the origin of IL-6, experiments were performed using IL-6 knock-out mice. Results: The differences in serum IL-6 and GCSF levels between the drug-treated and untreated groups were revealed by the magneto-nanosensor measurement on individual mice. Using the multiplex assays and mouse models, we found that IL-6 is secreted by the host in the presence of tumor cells upon the drug treatment. Conclusion: The multiplex magneto-nanosensor assays enable longitudinal proteomic studies on mouse tumor models to understand tumor development and therapy mechanisms more precisely within a single biological object.

Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments.

PubMed

Albaum, Stefan P; Neuweger, Heiko; Fränzel, Benjamin; Lange, Sita; Mertens, Dominik; Trötschel, Christian; Wolters, Dirk; Kalinowski, Jörn; Nattkemper, Tim W; Goesmann, Alexander

2009-12-01

The goal of present -omics sciences is to understand biological systems as a whole in terms of interactions of the individual cellular components. One of the main building blocks in this field of study is proteomics where tandem mass spectrometry (LC-MS/MS) in combination with isotopic labelling techniques provides a common way to obtain a direct insight into regulation at the protein level. Methods to identify and quantify the peptides contained in a sample are well established, and their output usually results in lists of identified proteins and calculated relative abundance values. The next step is to move ahead from these abstract lists and apply statistical inference methods to compare measurements, to identify genes that are significantly up- or down-regulated, or to detect clusters of proteins with similar expression profiles. We introduce the Rich Internet Application (RIA) Qupe providing comprehensive data management and analysis functions for LC-MS/MS experiments. Starting with the import of mass spectra data the system guides the experimenter through the process of protein identification by database search, the calculation of protein abundance ratios, and in particular, the statistical evaluation of the quantification results including multivariate analysis methods such as analysis of variance or hierarchical cluster analysis. While a data model to store these results has been developed, a well-defined programming interface facilitates the integration of novel approaches. A compute cluster is utilized to distribute computationally intensive calculations, and a web service allows to interchange information with other -omics software applications. To demonstrate that Qupe represents a step forward in quantitative proteomics analysis an application study on Corynebacterium glutamicum has been carried out. Qupe is implemented in Java utilizing Hibernate, Echo2, R and the Spring framework. We encourage the usage of the RIA in the sense of the 'software as a service' concept, maintained on our servers and accessible at the following location: http://qupe.cebitec.uni-bielefeld.de. Supplementary data are available at Bioinformatics online.

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.

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation.

PubMed

Hulme, Charlotte H; Wilson, Emma L; Fuller, Heidi R; Roberts, Sally; Richardson, James B; Gallacher, Pete; Peffers, Mandy J; Shirran, Sally L; Botting, Catherine H; Wright, Karina T

2018-05-02

Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.

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

Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.

PubMed

Oberg, Ann L; Mahoney, Douglas W

2012-01-01

Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.

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.

Affordable proteomics: the two-hybrid systems.

PubMed

Gillespie, Marc

2003-06-01

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

Global proteomic analysis of two tick-borne emerging zoonotic agents: Anaplasma phagocytophilum and Ehrlichia chaffeensis

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

Lin, Mingqun ..; Kikuchi, Takane; Brewer, Heather M.

2011-02-17

Anaplasma phagocytophilum and Ehrlichia chaffeensis are obligatory intracellular {alpha}-proteobacteria that infect human leukocytes and cause potentially fatal emerging zoonoses. In the present study, we determined global protein expression profiles of these bacteria cultured in the human promyelocytic leukemia cell line, HL-60. Mass spectrometric (MS) analyses identified a total of 1,212 A. phagocytophilum and 1,021 E. chaffeensis proteins, representing 89.3 and 92.3% of the predicted bacterial proteomes, respectively. Nearly all bacterial proteins ({approx}99%) with known functions were expressed, whereas only approximately 80% of hypothetical proteins were detected in infected human cells. Quantitative MS/MS analyses indicated that highly expressed proteins in bothmore » bacteria included chaperones, enzymes involved in biosynthesis and metabolism, and outer membrane proteins, such as A. phagocytophilum P44 and E. chaffeensis P28/OMP-1. Among 113 A. phagocytophilum p44 paralogous genes, 110 of them were expressed and 88 of them were encoded by pseudogenes. In addition, bacterial infection of HL-60 cells up-regulated the expression of human proteins involved mostly in cytoskeleton components, vesicular trafficking, cell signaling, and energy metabolism, but down regulated some pattern recognition receptors involved in innate immunity. Our proteomics data represent a comprehensive analysis of A. phagocytophilum and E. chaffeensis proteomes, and provide a quantitative view of human host protein expression profiles regulated by bacterial infection. The availability of these proteomic data will provide new insights into biology and pathogenesis of these obligatory intracellular pathogens.« 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.

Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

PubMed

Zhang, Xi

2015-09-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

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.

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.

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients.

PubMed

Mu, Jun; Yang, Yongtao; Chen, Jin; Cheng, Ke; Li, Qi; Wei, Yongdong; Zhu, Dan; Shao, Weihua; Zheng, Peng; Xie, Peng

2015-10-30

Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Optimization of quantitative proteomic analysis of clots generated from plasma of patients with venous thromboembolism.

PubMed

Stachowicz, Aneta; Siudut, Jakub; Suski, Maciej; Olszanecki, Rafał; Korbut, Ryszard; Undas, Anetta; Wiśniewski, Jacek R

2017-01-01

It is well known that fibrin network binds a large variety of proteins, including inhibitors and activators of fibrinolysis, which may affect clot properties, such as stability and susceptibility to fibrinolysis. Specific plasma clot composition differs between individuals and may change in disease states. However, the plasma clot proteome has not yet been in-depth analyzed, mainly due to technical difficulty related to the presence of a highly abundant protein-fibrinogen and fibrin that forms a plasma clot. The aim of our study was to optimize quantitative proteomic analysis of fibrin clots prepared ex vivo from citrated plasma of the peripheral blood drawn from patients with prior venous thromboembolism (VTE). We used a multiple enzyme digestion filter aided sample preparation, a multienzyme digestion (MED) FASP method combined with LC-MS/MS analysis performed on a Proxeon Easy-nLC System coupled to the Q Exactive HF mass spectrometer. We also evaluated the impact of peptide fractionation with pipet-tip strong anion exchange (SAX) method on the obtained results. Our proteomic approach revealed 476 proteins repeatedly identified in the plasma fibrin clots from patients with VTE including extracellular vesicle-derived proteins, lipoproteins, fibrinolysis inhibitors, and proteins involved in immune responses. The MED FASP method using three different enzymes: LysC, trypsin and chymotrypsin increased the number of identified peptides and proteins and their sequence coverage as compared to a single step digestion. Peptide fractionation with a pipet-tip strong anion exchange (SAX) protocol increased the depth of proteomic analyses, but also extended the time needed for sample analysis with LC-MS/MS. The MED FASP method combined with a label-free quantification is an excellent proteomic approach for the analysis of fibrin clots prepared ex vivo from citrated plasma of patients with prior VTE.

Proteomics analyses for the global proteins in the brain tissues of different human prion diseases.

PubMed

Shi, Qi; Chen, Li-Na; Zhang, Bao-Yun; Xiao, Kang; Zhou, Wei; Chen, Cao; Zhang, Xiao-Mei; Tian, Chan; Gao, Chen; Wang, Jing; Han, Jun; Dong, Xiao-Ping

2015-04-01

Proteomics changes of brain tissues have been described in different neurodegenerative diseases including Alzheimer's disease and Parkinson's disease. However, the brain proteomics of human prion disease remains less understood. In the study, the proteomics patterns of cortex and cerebellum of brain tissues of sporadic Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD were analyzed with isobaric tags for relative and absolute quantitation combined with multidimensional liquid chromatography and MS analysis, with the brains from three normal individuals as controls. Global protein profiling, significant pathway, and functional categories were analyzed. In total, 2287 proteins were identified with quantitative information both in cortex and cerebellum regions. Cerebellum tissues appeared to contain more up- and down-regulated proteins (727 proteins) than cortex regions (312 proteins) of Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD. Viral myocarditis, Parkinson's disease, Alzheimer's disease, lysosome, oxidative phosphorylation, protein export, and drug metabolism-cytochrome P450 were the most commonly affected pathways of the three kinds of diseases. Almost coincident biological functions were identified in the brain tissues of the three diseases. In all, data here demonstrate that the brain tissues of Creutzfeldt-Jakob disease, fatal familial insomnia, and G114V genetic CJD have obvious proteomics changes at their terminal stages, which show the similarities not only among human prion diseases but also with other neurodegeneration diseases. This is the first study to provide a reference proteome map for human prion diseases and will be helpful for future studies focused on potential biomarkers for the diagnosis and therapy of human prion diseases. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2017-01-31

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

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.

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

PubMed

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

2009-06-01

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

Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

PubMed

Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteogenomics Dashboard for the Human Proteome Project.

PubMed

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

2015-09-04

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

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

Proteomic profiling of isogenic primary and metastatic medulloblastoma cell lines reveals differential expression of key metastatic factors.

PubMed

Gu, Shuo; Chen, Kai; Yin, Minzhi; Wu, Zhixiang; Wu, Yeming

2017-05-08

Medulloblastoma is the most common malignant brain tumor in children. Around 30% of medulloblastoma patients are diagnosed with metastasis, which often results in a poor prognosis. Unfortunately, molecular mechanisms of medulloblastoma metastasis remain largely unknown. In this study, we employed the recently developed deep proteome analysis approach to quantitatively profile the expression of >10,000 proteins from CHLA-01-MED and CHLA-01R-MED isogenic cell lines derived from the primary and metastatic tumor of the same patient diagnosed with a group IV medulloblastoma. Using statistical analysis, we identified ~1400 significantly altered proteins between the primary and metastatic cell lines including known factors such as placental growth factor (PLGF), LIM homeobox 1 (LHX1) and prominim 1 (PROM1), as well as the negative regulator secreted protein acidic and cysteine rich (SPARC). Additional transwell experiments and immunohistochemical analysis of clinical medulloblastoma samples implicated yes-associated protein 1 (YAP1) as a potential key factor contributing to metastasis. Taken together, our data broadly defines the metastasis-relevant regulated proteome and provides a precious resource for further investigating potential mechanisms of medulloblastoma metastasis. This study represented the first deep proteome analysis of metastatic medulloblastomas and provided a valuable candidate list of altered proteins in metastatic medulloblastomas. The primary data suggested YAP1 as a potential driver for the metastasis of medulloblastoma. These results open up numerous avenues for further investigating the underlying mechanisms of medulloblastoma metastasis and improving the prognosis of medulloblastoma patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Proteomic analysis of ligamentum flavum from patients with lumbar spinal stenosis.

PubMed

Kamita, Masahiro; Mori, Taiki; Sakai, Yoshihito; Ito, Sadayuki; Gomi, Masahiro; Miyamoto, Yuko; Harada, Atsushi; Niida, Shumpei; Yamada, Tesshi; Watanabe, Ken; Ono, Masaya

2015-05-01

Lumbar spinal stenosis (LSS) is a syndromic degenerative spinal disease and is characterized by spinal canal narrowing with subsequent neural compression causing gait disturbances. Although LSS is a major age-related musculoskeletal disease that causes large decreases in the daily living activities of the elderly, its molecular pathology has not been investigated using proteomics. Thus, we used several proteomic technologies to analyze the ligamentum flavum (LF) of individuals with LSS. Using comprehensive proteomics with strong cation exchange fractionation, we detected 1288 proteins in these LF samples. A GO analysis of the comprehensive proteome revealed that more than 30% of the identified proteins were extracellular. Next, we used 2D image converted analysis of LC/MS to compare LF obtained from individuals with LSS to that obtained from individuals with disc herniation (nondegenerative control). We detected 64 781 MS peaks and identified 1675 differentially expressed peptides derived from 286 proteins. We verified four differentially expressed proteins (fibronectin, serine protease HTRA1, tenascin, and asporin) by quantitative proteomics using SRM/MRM. The present proteomic study is the first to identify proteins from degenerated and hypertrophied LF in LSS, which will help in studying LSS. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic regulation of hepatic lipid droplet properties by diet.

PubMed

Crunk, Amanda E; Monks, Jenifer; Murakami, Aya; Jackman, Matthew; Maclean, Paul S; Ladinsky, Mark; Bales, Elise S; Cain, Shannon; Orlicky, David J; McManaman, James L

2013-01-01

Cytoplasmic lipid droplets (CLD) are organelle-like structures that function in neutral lipid storage, transport and metabolism through the actions of specific surface-associated proteins. Although diet and metabolism influence hepatic CLD levels, how they affect CLD protein composition is largely unknown. We used non-biased, shotgun, proteomics in combination with metabolic analysis, quantitative immunoblotting, electron microscopy and confocal imaging to define the effects of low- and high-fat diets on CLD properties in fasted-refed mice. We found that the hepatic CLD proteome is distinct from that of CLD from other mammalian tissues, containing enzymes from multiple metabolic pathways. The hepatic CLD proteome is also differentially affected by dietary fat content and hepatic metabolic status. High fat feeding markedly increased the CLD surface density of perilipin-2, a critical regulator of hepatic neutral lipid storage, whereas it reduced CLD levels of betaine-homocysteine S-methyltransferase, an enzyme regulator of homocysteine levels linked to fatty liver disease and hepatocellular carcinoma. Collectively our data demonstrate that the hepatic CLD proteome is enriched in metabolic enzymes, and that it is qualitatively and quantitatively regulated by diet and metabolism. These findings implicate CLD in the regulation of hepatic metabolic processes, and suggest that their properties undergo reorganization in response to hepatic metabolic demands.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

PubMed Central

Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

2016-01-01

High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

iTRAQ-Based Quantitative Proteomics of Developing and Ripening Muscadine Grape Berry

PubMed Central

Kambiranda, Devaiah; Katam, Ramesh; Basha, Sheikh M.; Siebert, Shalom

2014-01-01

Grapes are among the widely cultivated fruit crops in the world. Grape berries like other nonclimacteric fruits undergo a complex set of dynamic, physical, physiological, and biochemical changes during ripening. Muscadine grapes are widely cultivated in the southern United States for fresh fruit and wine. To date, changes in the metabolites composition of muscadine grapes have been well documented; however, the molecular changes during berry development and ripening are not fully known. The aim of this study was to investigate changes in the berry proteome during ripening in muscadine grape cv. Noble. Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS was used to detect statistically significant changes in the berry proteome. A total of 674 proteins were detected, and 76 were differentially expressed across four time points in muscadine berry. Proteins obtained were further analyzed to provide information about its potential functions during ripening. Several proteins involved in abiotic and biotic stimuli and sucrose and hexose metabolism were upregulated during berry ripening. Quantitative real-time PCR analysis validated the protein expression results for nine proteins. Identification of vicilin-like antimicrobial peptides indicates additional disease tolerance proteins are present in muscadines for berry protection during ripening. The results provide new information for characterization and understanding muscadine berry proteome and grape ripening. PMID:24251720

Dynamic Regulation of Hepatic Lipid Droplet Properties by Diet

PubMed Central

Crunk, Amanda E.; Monks, Jenifer; Murakami, Aya; Jackman, Matthew; MacLean, Paul S.; Ladinsky, Mark; Bales, Elise S.; Cain, Shannon; Orlicky, David J.; McManaman, James L.

2013-01-01

Cytoplasmic lipid droplets (CLD) are organelle-like structures that function in neutral lipid storage, transport and metabolism through the actions of specific surface-associated proteins. Although diet and metabolism influence hepatic CLD levels, how they affect CLD protein composition is largely unknown. We used non-biased, shotgun, proteomics in combination with metabolic analysis, quantitative immunoblotting, electron microscopy and confocal imaging to define the effects of low- and high-fat diets on CLD properties in fasted-refed mice. We found that the hepatic CLD proteome is distinct from that of CLD from other mammalian tissues, containing enzymes from multiple metabolic pathways. The hepatic CLD proteome is also differentially affected by dietary fat content and hepatic metabolic status. High fat feeding markedly increased the CLD surface density of perilipin-2, a critical regulator of hepatic neutral lipid storage, whereas it reduced CLD levels of betaine-homocysteine S-methyltransferase, an enzyme regulator of homocysteine levels linked to fatty liver disease and hepatocellular carcinoma. Collectively our data demonstrate that the hepatic CLD proteome is enriched in metabolic enzymes, and that it is qualitatively and quantitatively regulated by diet and metabolism. These findings implicate CLD in the regulation of hepatic metabolic processes, and suggest that their properties undergo reorganization in response to hepatic metabolic demands. PMID:23874434

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

PubMed

Burnum-Johnson, Kristin E; Nie, Song; Casey, Cameron P; Monroe, Matthew E; Orton, Daniel J; Ibrahim, Yehia M; Gritsenko, Marina A; Clauss, Therese R W; Shukla, Anil K; Moore, Ronald J; Purvine, Samuel O; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S; Smith, Richard D

2016-12-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Global, quantitative and dynamic mapping of protein subcellular localization.

PubMed

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg Hh

2016-06-09

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

PubMed

Han, Bomie; Higgs, Richard E

2008-09-01

High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

Quantitative Proteomic Analysis of Wheat Cultivars with Differing Drought Stress Tolerance

PubMed Central

Ford, Kristina L.; Cassin, Andrew; Bacic, Antony

2011-01-01

Using a series of multiplexed experiments we studied the quantitative changes in protein abundance of three Australian bread wheat cultivars (Triticum aestivum L.) in response to a drought stress. Three cultivars differing in their ability to maintain grain yield during drought, Kukri (intolerant), Excalibur (tolerant), and RAC875 (tolerant), were grown in the glasshouse with cyclic drought treatment that mimicked conditions in the field. Proteins were isolated from leaves of mature plants and isobaric tags were used to follow changes in the relative protein abundance of 159 proteins. This is the first shotgun proteomics study in wheat, providing important insights into protein responses to drought as well as identifying the largest number of wheat proteins (1,299) in a single study. The changes in the three cultivars at the different time points reflected their differing physiological responses to drought, with the two drought tolerant varieties (Excalibur and RAC875) differing in their protein responses. Excalibur lacked significant changes in proteins during the initial onset of the water deficit in contrast to RAC875 that had a large number of significant changes. All three cultivars had changes consistent with an increase in oxidative stress metabolism and reactive O2 species (ROS) scavenging capacity seen through increases in superoxide dismutases and catalases as well as ROS avoidance through the decreases in proteins involved in photosynthesis and the Calvin cycle. PMID:22639595

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

PubMed

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

2011-06-01

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

Garlic (Allium sativum L.) fertility: transcriptome and proteome analyses provide insight into flower and pollen development

PubMed Central

Shemesh-Mayer, Einat; Ben-Michael, Tomer; Rotem, Neta; Rabinowitch, Haim D.; Doron-Faigenboim, Adi; Kosmala, Arkadiusz; Perlikowski, Dawid; Sherman, Amir; Kamenetsky, Rina

2015-01-01

Commercial cultivars of garlic, a popular condiment, are sterile, making genetic studies and breeding of this plant challenging. However, recent fertility restoration has enabled advanced physiological and genetic research and hybridization in this important crop. Morphophysiological studies, combined with transcriptome and proteome analyses and quantitative PCR validation, enabled the identification of genes and specific processes involved in gametogenesis in fertile and male-sterile garlic genotypes. Both genotypes exhibit normal meiosis at early stages of anther development, but in the male-sterile plants, tapetal hypertrophy after microspore release leads to pollen degeneration. Transcriptome analysis and global gene-expression profiling showed that >16,000 genes are differentially expressed in the fertile vs. male-sterile developing flowers. Proteome analysis and quantitative comparison of 2D-gel protein maps revealed 36 significantly different protein spots, 9 of which were present only in the male-sterile genotype. Bioinformatic and quantitative PCR validation of 10 candidate genes exhibited significant expression differences between male-sterile and fertile flowers. A comparison of morphophysiological and molecular traits of fertile and male-sterile garlic flowers suggests that respiratory restrictions and/or non-regulated programmed cell death of the tapetum can lead to energy deficiency and consequent pollen abortion. Potential molecular markers for male fertility and sterility in garlic are proposed. PMID:25972879

Global response of Acidithiobacillus ferrooxidans ATCC 53993 to high concentrations of copper: A quantitative proteomics approach.

PubMed

Martínez-Bussenius, Cristóbal; Navarro, Claudio A; Orellana, Luis; Paradela, Alberto; Jerez, Carlos A

2016-08-11

Acidithiobacillus ferrooxidans is used in industrial bioleaching of minerals to extract valuable metals. A. ferrooxidans strain ATCC 53993 is much more resistant to copper than other strains of this microorganism and it has been proposed that genes present in an exclusive genomic island (GI) of this strain would contribute to its extreme copper tolerance. ICPL (isotope-coded protein labeling) quantitative proteomics was used to study in detail the response of this bacterium to copper. A high overexpression of RND efflux systems and CusF copper chaperones, both present in the genome and the GI of strain ATCC 53993 was found. Also, changes in the levels of the respiratory system proteins such as AcoP and Rus copper binding proteins and several proteins with other predicted functions suggest that numerous metabolic changes are apparently involved in controlling the effects of the toxic metal on this acidophile. Using quantitative proteomics we overview the adaptation mechanisms that biomining acidophiles use to stand their harsh environment. The overexpression of several genes present in an exclusive genomic island strongly suggests the importance of the proteins coded in this DNA region in the high tolerance of A. ferrooxidans ATCC 53993 to metals. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative proteomics links metabolic pathways to specific developmental stages of the plant-pathogenic oomycete Phytophthora capsici.

PubMed

Pang, Zhili; Srivastava, Vaibhav; Liu, Xili; Bulone, Vincent

2017-04-01

The oomycete Phytophthora capsici is a plant pathogen responsible for important losses to vegetable production worldwide. Its asexual reproduction plays an important role in the rapid propagation and spread of the disease in the field. A global proteomics study was conducted to compare two key asexual life stages of P. capsici, i.e. the mycelium and cysts, to identify stage-specific biochemical processes. A total of 1200 proteins was identified using qualitative and quantitative proteomics. The transcript abundance of some of the enriched proteins was also analysed by quantitative real-time polymerase chain reaction. Seventy-three proteins exhibited different levels of abundance between the mycelium and cysts. The proteins enriched in the mycelium are mainly associated with glycolysis, the tricarboxylic acid (or citric acid) cycle and the pentose phosphate pathway, providing the energy required for the biosynthesis of cellular building blocks and hyphal growth. In contrast, the proteins that are predominant in cysts are essentially involved in fatty acid degradation, suggesting that the early infection stage of the pathogen relies primarily on fatty acid degradation for energy production. The data provide a better understanding of P. capsici biology and suggest potential metabolic targets at the two different developmental stages for disease control. © 2016 BSPP AND JOHN WILEY & SONS LTD.

Quantitative mass spectrometry of human reticulocytes reveal proteome-wide modifications during maturation.

PubMed

Chu, Trang T T; Sinha, Ameya; Malleret, Benoit; Suwanarusk, Rossarin; Park, Jung E; Naidu, Renugah; Das, Rupambika; Dutta, Bamaprasad; Ong, Seow Theng; Verma, Navin K; Chan, Jerry K; Nosten, François; Rénia, Laurent; Sze, Siu K; Russell, Bruce; Chandramohanadas, Rajesh

2018-01-01

Erythropoiesis is marked by progressive changes in morphological, biochemical and mechanical properties of erythroid precursors to generate red blood cells (RBC). The earliest enucleated forms derived in this process, known as reticulocytes, are multi-lobular and spherical. As reticulocytes mature, they undergo a series of dynamic cytoskeletal re-arrangements and the expulsion of residual organelles, resulting in highly deformable biconcave RBCs (normocytes). To understand the significant, yet neglected proteome-wide changes associated with reticulocyte maturation, we undertook a quantitative proteomics approach. Immature reticulocytes (marked by the presence of surface transferrin receptor, CD71) and mature RBCs (devoid of CD71) were isolated from human cord blood using a magnetic separation procedure. After sub-fractionation into triton-extracted membrane proteins and luminal samples (isobaric tags for relative and absolute quantitation), quantitative mass spectrometry was conducted to identify more than 1800 proteins with good confidence and coverage. While most structural proteins (such as Spectrins, Ankyrin and Band 3) as well as surface glycoproteins were conserved, proteins associated with microtubule structures, such as Talin-1/2 and ß-Tubulin, were detected only in immature reticulocytes. Atomic force microscopy (AFM)-based imaging revealed an extended network of spectrin filaments in reticulocytes (with an average length of 48 nm), which shortened during reticulocyte maturation (average spectrin length of 41 nm in normocytes). The extended nature of cytoskeletal network may partly account for increased deformability and shape changes, as reticulocytes transform to normocytes. © 2017 John Wiley & Sons Ltd.

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.

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

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

PubMed

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

2006-09-01

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

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

PubMed

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

2013-12-16

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

Toxicoproteomics in Aquatic Toxicology: iTRAQ Reveals Insight into Proteins Affected by 17alpha-ethinylestradiol, Dieldrin, and 17â-trenbolone

EPA Science Inventory

Toxicoproteomics is an emerging discipline in toxicology for characterizing chemical modes of action at the molecular level. We have successfully utilized a quantitative proteomics method termed isobaric tagging for relative and absolute quantitation (iTRAQ) to measure protein re...

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/.

Recent advances in proteomics of cereals.

PubMed

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

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

2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments.

PubMed

Allmer, Jens; Kuhlgert, Sebastian; Hippler, Michael

2008-07-07

The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage.

Development of Best practices document for Peptide Standards | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Assay Development Working Group (ADWG) of the CPTAC Program is currently drafting a document to propose best practices for generation, quantification, storage, and handling of peptide standards used for mass spectrometry-based assays, as well as interpretation of quantitative proteomic data based on peptide standards. The ADWG is seeking input from commercial entities that provide peptide standards for mass spectrometry-based assays or that perform amino acid analysis.

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.

Changes over lactation in breast milk serum proteins involved in the maturation of immune and digestive system of the infant.

PubMed

Zhang, Lina; de Waard, Marita; Verheijen, Hester; Boeren, Sjef; Hageman, Jos A; van Hooijdonk, Toon; Vervoort, Jacques; van Goudoever, Johannes B; Hettinga, Kasper

2016-09-16

To objective of this study was to better understand the biological functions of breast milk proteins in relation to the growth and development of infants over the first six months of life. Breast milk samples from four individual women collected at seven time points in the first six months after delivery were analyzed by filter aided sample preparation and dimethyl labeling combined with liquid chromatography tandem mass spectrometry. A total of 247 and 200 milk serum proteins were identified and quantified, respectively. The milk serum proteome showed a high similarity (80% overlap) on the qualitative level between women and over lactation. The quantitative changes in milk serum proteins were mainly caused by three groups of proteins, enzymes, and transport and immunity proteins. Of these 21 significantly changed proteins, 30% were transport proteins, such as serum albumin and fatty acid binding protein, which are both involved in transporting nutrients to the infant. The decrease of the enzyme bile salt-activated lipase as well as the immunity proteins immunoglobulins and lactoferrin coincide with the gradual maturation of the digestive and immune system of infants. The human milk serum proteome didn't differ qualitatively but it did quantitatively, both between mothers and as lactation advanced. The changes of the breast milk serum proteome over lactation corresponded with the development of the digestive and immune system of infants. Breast milk proteins provide nutrition, but also contribute to healthy development of infants. Despite the previously reported large number of identified breast milk proteins and their changes over lactation, less is known on the changes of these proteins in individual mothers. This study is the first to determine the qualitative and quantitative changes of milk proteome over lactation between individual mothers. The results indicate that the differences in the milk proteome between individual mothers are more related to the quantitative level than qualitative level. The correlation between the changes of milk proteins and the gradual maturation of the gastrointestinal tract and immune system in infants, contributes to a better understanding of the biological functions of human milk proteins for the growth and development of infants. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00290k Click here for additional data file.

PubMed Central

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

2016-01-01

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously. PMID:27412694

SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC.

PubMed

Zhang, Fanglin; Lin, Hechun; Gu, Aiqin; Li, Jing; Liu, Lei; Yu, Tao; Cui, Yongqi; Deng, Wei; Yan, Mingxia; Li, Jinjun; Yao, Ming

2014-05-06

To identify cancer-related proteins, we used isobaric tags in a relative and absolute quantitation (iTRAQ) proteomic approach and SWATH™ quantification approach to analyze the secretome of an isogenic pair of highly metastatic and low metastatic non-small-cell lung cancer (NSCLC) cell lines. In addition, we compared two groups of pooled serum samples (12 early-stage and 12 late-stage patients) to mine data for candidates screened by iTRAQ-labeled proteomic analysis. A total of 110 proteins and 71 proteins were observed to be significantly differentially expressed in the cell line secretome and NSCLC sera, respectively. Among these proteins, CD109 was found to be highly expressed in both the highly metastatic cell line secretome and the group of late-stage patients. A sandwich ELISA assay also demonstrated an elevation of serum CD109 levels in individual NSCLC patients (n=30) compared with healthy subjects (n=19). Furthermore, CD109 displayed higher expression in lung cancer tissues compared with their matched noncancerous lung tissues (n=72). In addition, the knockdown of CD109 influenced several NSCLC cell bio-functions, for instance, depressing cell growth, affecting cell cycle phases. These phenomena suggest that CD109 plays a critical role in NSCLC progression. We simultaneously applied two quantitative proteomic approaches-iTRAQ-labeling and SWATH™-to analyze the secretome of metastatic cell lines, in order to explore the cancer-associated proteins in conditioned media. In this study, our results indicate that CD109 plays a critical role in non-small-cell lung cancer (NSCLC) progression, and is overexpressed in advanced NSCLC. Copyright © 2014 Elsevier B.V. All rights reserved.

Transcriptomic and Quantitative Proteomic Analyses Provide Insights Into the Phagocytic Killing of Hemocytes in the Oyster Crassostrea gigas

PubMed Central

Jiang, Shuai; Qiu, Limei; Wang, Lingling; Jia, Zhihao; Lv, Zhao; Wang, Mengqiang; Liu, Conghui; Xu, Jiachao; Song, Linsheng

2018-01-01

As invertebrates lack an adaptive immune system, they depend to a large extent on their innate immune system to recognize and clear invading pathogens. Although phagocytes play pivotal roles in invertebrate innate immunity, the molecular mechanisms underlying this killing remain unclear. Cells of this type from the Pacific oyster Crassostrea gigas were classified efficiently in this study via fluorescence-activated cell sorting (FACS) based on their phagocytosis of FITC-labeled latex beads. Transcriptomic and quantitative proteomic analyses revealed a series of differentially expressed genes (DEGs) and proteins present in phagocytes; of the 352 significantly high expressed proteins identified here within the phagocyte proteome, 262 corresponding genes were similarly high expressed in the transcriptome, while 140 of 205 significantly low expressed proteins within the proteome were transcriptionally low expressed. A pathway crosstalk network analysis of these significantly high expressed proteins revealed that phagocytes were highly activated in a number of antimicrobial-related biological processes, including oxidation–reduction and lysosomal proteolysis processes. A number of DEGs, including oxidase, lysosomal protease, and immune receptors, were also validated in this study using quantitative PCR, while seven lysosomal cysteine proteases, referred to as cathepsin Ls, were significantly high expressed in phagocytes. Results show that the expression level of cathepsin L protein in phagocytes [mean fluorescence intensity (MFI): 327 ± 51] was significantly higher (p < 0.01) than that in non-phagocytic hemocytes (MFI: 83 ± 26), while the cathepsin L protein was colocalized with the phagocytosed Vibrio splendidus in oyster hemocytes during this process. The results of this study collectively suggest that oyster phagocytes possess both potent oxidative killing and microbial disintegration capacities; these findings provide important insights into hemocyte phagocytic killing as a component of C. gigas innate immunity. PMID:29942306

Comprehensive Analysis of Proteomic Differences between Escherichia coli K-12 and B Strains Using Multiplexed Isobaric Tandem Mass Tag (TMT) Labeling.

PubMed

Han, Mee-Jung

2017-11-28

The Escherichia coli K-12 and B strains are among the most frequently used bacterial hosts for scientific research and biotechnological applications. However, omics analyses have revealed that E. coli K-12 and B exhibit notably different genotypic and phenotypic attributes, even though they were derived from the same ancestor. In a previous study, we identified a limited number of proteins from the two strains using two-dimensional gel electrophoresis and tandem mass spectrometry (MS/MS). In this study, an in-depth analysis of the physiological behavior of the E. coli K-12 and B strains at the proteomic level was performed using six-plex isobaric tandem mass tag-based quantitative MS. Additionally, the best lysis buffer for increasing the efficiency of protein extraction was selected from three tested buffers prior to the quantitative proteomic analysis. This study identifies the largest number of proteins in the two E. coli strains reported to date and is the first to show the dynamics of these proteins. Notable differences in proteins associated with key cellular properties, including some metabolic pathways, the biosynthesis and degradation of amino acids, membrane integrity, cellular tolerance, and motility, were found between the two representative strains. Compared with previous studies, these proteomic results provide a more holistic view of the overall state of E. coli cells based on a single proteomic study and reveal significant insights into why the two strains show distinct phenotypes. Additionally, the resulting data provide in-depth information that will help fine-tune processes in the future.

Time-Series Analyses of Transcriptomes and Proteomes Reveal Molecular Networks Underlying Oil Accumulation in Canola.

PubMed

Wan, Huafang; Cui, Yixin; Ding, Yijuan; Mei, Jiaqin; Dong, Hongli; Zhang, Wenxin; Wu, Shiqi; Liang, Ying; Zhang, Chunyu; Li, Jiana; Xiong, Qing; Qian, Wei

2016-01-01

Understanding the regulation of lipid metabolism is vital for genetic engineering of canola ( Brassica napus L.) to increase oil yield or modify oil composition. We conducted time-series analyses of transcriptomes and proteomes to uncover the molecular networks associated with oil accumulation and dynamic changes in these networks in canola. The expression levels of genes and proteins were measured at 2, 4, 6, and 8 weeks after pollination (WAP). Our results show that the biosynthesis of fatty acids is a dominant cellular process from 2 to 6 WAP, while the degradation mainly happens after 6 WAP. We found that genes in almost every node of fatty acid synthesis pathway were significantly up-regulated during oil accumulation. Moreover, significant expression changes of two genes, acetyl-CoA carboxylase and acyl-ACP desaturase, were detected on both transcriptomic and proteomic levels. We confirmed the temporal expression patterns revealed by the transcriptomic analyses using quantitative real-time PCR experiments. The gene set association analysis show that the biosynthesis of fatty acids and unsaturated fatty acids are the most significant biological processes from 2-4 WAP and 4-6 WAP, respectively, which is consistent with the results of time-series analyses. These results not only provide insight into the mechanisms underlying lipid metabolism, but also reveal novel candidate genes that are worth further investigation for their values in the genetic engineering of canola.

A Novel Proteomics Approach to Identify SUMOylated Proteins and Their Modification Sites in Human Cells*

PubMed Central

Galisson, Frederic; Mahrouche, Louiza; Courcelles, Mathieu; Bonneil, Eric; Meloche, Sylvain; Chelbi-Alix, Mounira K.; Thibault, Pierre

2011-01-01

The small ubiquitin-related modifier (SUMO) is a small group of proteins that are reversibly attached to protein substrates to modify their functions. The large scale identification of protein SUMOylation and their modification sites in mammalian cells represents a significant challenge because of the relatively small number of in vivo substrates and the dynamic nature of this modification. We report here a novel proteomics approach to selectively enrich and identify SUMO conjugates from human cells. We stably expressed different SUMO paralogs in HEK293 cells, each containing a His6 tag and a strategically located tryptic cleavage site at the C terminus to facilitate the recovery and identification of SUMOylated peptides by affinity enrichment and mass spectrometry. Tryptic peptides with short SUMO remnants offer significant advantages in large scale SUMOylome experiments including the generation of paralog-specific fragment ions following CID and ETD activation, and the identification of modified peptides using conventional database search engines such as Mascot. We identified 205 unique protein substrates together with 17 precise SUMOylation sites present in 12 SUMO protein conjugates including three new sites (Lys-380, Lys-400, and Lys-497) on the protein promyelocytic leukemia. Label-free quantitative proteomics analyses on purified nuclear extracts from untreated and arsenic trioxide-treated cells revealed that all identified SUMOylated sites of promyelocytic leukemia were differentially SUMOylated upon stimulation. PMID:21098080

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.

Proteomics in the genome engineering era.

PubMed

Vandemoortele, Giel; Gevaert, Kris; Eyckerman, Sven

2016-01-01

Genome engineering experiments used to be lengthy, inefficient, and often expensive, preventing a widespread adoption of such experiments for the full assessment of endogenous protein functions. With the revolutionary clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 technology, genome engineering became accessible to the broad life sciences community and is now implemented in several research areas. One particular field that can benefit significantly from this evolution is proteomics where a substantial impact on experimental design and general proteome biology can be expected. In this review, we describe the main applications of genome engineering in proteomics, including the use of engineered disease models and endogenous epitope tagging. In addition, we provide an overview on current literature and highlight important considerations when launching genome engineering technologies in proteomics workflows. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Gel Electrophoresis Markup Language (GelML) from the Proteomics Standards Initiative

PubMed Central

Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J. Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R

2011-01-01

The Human Proteome Organisation’s Proteomics Standards Initiative (HUPO-PSI) has developed the GelML data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for mass spectrometry data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications. PMID:20677327

The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative.

PubMed

Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R

2010-09-01

The Human Proteome Organisation's Proteomics Standards Initiative has developed the GelML (gel electrophoresis markup language) data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for MS data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.

Quantitative proteomics reveals altered expression of extracellular matrix related proteins of human primary dermal fibroblasts in response to sulfated hyaluronan and collagen applied as artificial extracellular matrix.

PubMed

Müller, Stephan A; van der Smissen, Anja; von Feilitzsch, Margarete; Anderegg, Ulf; Kalkhof, Stefan; von Bergen, Martin

2012-12-01

Fibroblasts are the main matrix producing cells of the dermis and are also strongly regulated by their matrix environment which can be used to improve and guide skin wound healing processes. Here, we systematically investigated the molecular effects on primary dermal fibroblasts in response to high-sulfated hyaluronan [HA] (hsHA) by quantitative proteomics. The comparison of non- and high-sulfated HA revealed regulation of 84 of more than 1,200 quantified proteins. Based on gene enrichment we found that sulfation of HA alters extracellular matrix remodeling. The collagen degrading enzymes cathepsin K, matrix metalloproteinases-2 and -14 were found to be down-regulated on hsHA. Additionally protein expression of thrombospondin-1, decorin, collagen types I and XII were reduced, whereas the expression of trophoblast glycoprotein and collagen type VI were slightly increased. This study demonstrates that global proteomics provides a valuable tool for revealing proteins involved in molecular effects of growth substrates for further material optimization.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

PubMed Central

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised. PMID:28248236

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

PubMed

Barkla, Bronwyn J

2016-09-08

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Quantitative proteomics reveals the importance of nitrogen source to control glucosinolate metabolism in Arabidopsis thaliana and Brassica oleracea

PubMed Central

Marino, Daniel; Ariz, Idoia; Lasa, Berta; Santamaría, Enrique; Fernández-Irigoyen, Joaquín; González-Murua, Carmen; Aparicio Tejo, Pedro M.

2016-01-01

Accessing different nitrogen (N) sources involves a profound adaptation of plant metabolism. In this study, a quantitative proteomic approach was used to further understand how the model plant Arabidopsis thaliana adjusts to different N sources when grown exclusively under nitrate or ammonium nutrition. Proteome data evidenced that glucosinolate metabolism was differentially regulated by the N source and that both TGG1 and TGG2 myrosinases were more abundant under ammonium nutrition, which is generally considered to be a stressful situation. Moreover, Arabidopsis plants displayed glucosinolate accumulation and induced myrosinase activity under ammonium nutrition. Interestingly, these results were also confirmed in the economically important crop broccoli (Brassica oleracea var. italica). Moreover, these metabolic changes were correlated in Arabidopsis with the differential expression of genes from the aliphatic glucosinolate metabolic pathway. This study underlines the importance of nitrogen nutrition and the potential of using ammonium as the N source in order to stimulate glucosinolate metabolism, which may have important applications not only in terms of reducing pesticide use, but also for increasing plants’ nutritional value. PMID:27085186

Quantitative proteomics of synaptic and nonsynaptic mitochondria: insights for synaptic mitochondrial vulnerability.

PubMed

Stauch, Kelly L; Purnell, Phillip R; Fox, Howard S

2014-05-02

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage.

Quantitative Proteomics of Synaptic and Nonsynaptic Mitochondria: Insights for Synaptic Mitochondrial Vulnerability

PubMed Central

2015-01-01

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage. PMID:24708184

Proteomics links the redox state to calcium signaling during bleaching of the scleractinian coral Acropora microphthalma on exposure to high solar irradiance and thermal stress.

PubMed

Weston, Andrew J; Dunlap, Walter C; Beltran, Victor H; Starcevic, Antonio; Hranueli, Daslav; Ward, Malcolm; Long, Paul F

2015-03-01

Shipboard experiments were each performed over a 2 day period to examine the proteomic response of the symbiotic coral Acropora microphthalma exposed to acute conditions of high temperature/low light or high light/low temperature stress. During these treatments, corals had noticeably bleached. The photosynthetic performance of residual algal endosymbionts was severely impaired but showed signs of recovery in both treatments by the end of the second day. Changes in the coral proteome were determined daily and, using recently available annotated genome sequences, the individual contributions of the coral host and algal endosymbionts could be extracted from these data. Quantitative changes in proteins relevant to redox state and calcium metabolism are presented. Notably, expression of common antioxidant proteins was not detected from the coral host but present in the algal endosymbiont proteome. Possible roles for elevated carbonic anhydrase in the coral host are considered: to restore intracellular pH diminished by loss of photosynthetic activity, to indirectly limit intracellular calcium influx linked with enhanced calmodulin expression to impede late-stage symbiont exocytosis, or to enhance inorganic carbon transport to improve the photosynthetic performance of algal symbionts that remain in hospite. Protein effectors of calcium-dependent exocytosis were present in both symbiotic partners. No caspase-family proteins associated with host cell apoptosis, with exception of the autophagy chaperone HSP70, were detected, suggesting that algal loss and photosynthetic dysfunction under these experimental conditions were not due to host-mediated phytosymbiont destruction. Instead, bleaching occurred by symbiont exocytosis and loss of light-harvesting pigments of algae that remain in hospite. These proteomic data are, therefore, consistent with our premise that coral endosymbionts can mediate their own retention or departure from the coral host, which may manifest as "symbiont shuffling" of Symbiodinium clades in response to environmental stress. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

Human borna disease virus infection impacts host proteome and histone lysine acetylation in human oligodendroglia cells

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

Liu, Xia; Department of Neurology, The Fifth People's Hospital of Shanghai, School of Medicine, Fudan University, Shanghai, 200240; Zhao, Libo

2014-09-15

Background: Borna disease virus (BDV) replicates in the nucleus and establishes persistent infections in mammalian hosts. A human BDV strain was used to address the first time, how BDV infection impacts the proteome and histone lysine acetylation (Kac) of human oligodendroglial (OL) cells, thus allowing a better understanding of infection-driven pathophysiology in vitro. Methods: Proteome and histone lysine acetylation were profiled through stable isotope labeling for cell culture (SILAC)-based quantitative proteomics. The quantifiable proteome was annotated using bioinformatics. Histone acetylation changes were validated by biochemistry assays. Results: Post BDV infection, 4383 quantifiable differential proteins were identified and functionally annotated tomore » metabolism pathways, immune response, DNA replication, DNA repair, and transcriptional regulation. Sixteen of the thirty identified Kac sites in core histones presented altered acetylation levels post infection. Conclusions: BDV infection using a human strain impacted the whole proteome and histone lysine acetylation in OL cells. - Highlights: • A human strain of BDV (BDV Hu-H1) was used to infect human oligodendroglial cells (OL cells). • This study is the first to reveal the host proteomic and histone Kac profiles in BDV-infected OL cells. • BDV infection affected the expression of many transcription factors and several HATs and HDACs.« less

Cell death proteomics database: consolidating proteomics data on cell death.

PubMed

Arntzen, Magnus Ø; Bull, Vibeke H; Thiede, Bernd

2013-05-03

Programmed cell death is a ubiquitous process of utmost importance for the development and maintenance of multicellular organisms. More than 10 different types of programmed cell death forms have been discovered. Several proteomics analyses have been performed to gain insight in proteins involved in the different forms of programmed cell death. To consolidate these studies, we have developed the cell death proteomics (CDP) database, which comprehends data from apoptosis, autophagy, cytotoxic granule-mediated cell death, excitotoxicity, mitotic catastrophe, paraptosis, pyroptosis, and Wallerian degeneration. The CDP database is available as a web-based database to compare protein identifications and quantitative information across different experimental setups. The proteomics data of 73 publications were integrated and unified with protein annotations from UniProt-KB and gene ontology (GO). Currently, more than 6,500 records of more than 3,700 proteins are included in the CDP. Comparing apoptosis and autophagy using overrepresentation analysis of GO terms, the majority of enriched processes were found in both, but also some clear differences were perceived. Furthermore, the analysis revealed differences and similarities of the proteome between autophagosomal and overall autophagy. The CDP database represents a useful tool to consolidate data from proteome analyses of programmed cell death and is available at http://celldeathproteomics.uio.no.

Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project.

PubMed

Omenn, Gilbert S; Lane, Lydie; Lundberg, Emma K; Overall, Christopher M; Deutsch, Eric W

2017-12-01

The Human Proteome Organization (HUPO) Human Proteome Project (HPP) continues to make progress on its two overall goals: (1) completing the protein parts list, with an annual update of the HUPO draft human proteome, and (2) making proteomics an integrated complement to genomics and transcriptomics throughout biomedical and life sciences research. neXtProt version 2017-01-23 has 17 008 confident protein identifications (Protein Existence [PE] level 1) that are compliant with the HPP Guidelines v2.1 ( https://hupo.org/Guidelines ), up from 13 664 in 2012-12 and 16 518 in 2016-04. Remaining to be found by mass spectrometry and other methods are 2579 "missing proteins" (PE2+3+4), down from 2949 in 2016. PeptideAtlas 2017-01 has 15 173 canonical proteins, accounting for nearly all of the 15 290 PE1 proteins based on MS data. These resources have extensive data on PTMs, single amino acid variants, and splice isoforms. The Human Protein Atlas v16 has 10 492 highly curated protein entries with tissue and subcellular spatial localization of proteins and transcript expression. Organ-specific popular protein lists have been generated for broad use in quantitative targeted proteomics using SRM-MS or DIA-SWATH-MS studies of biology and disease.

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.

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

PubMed Central

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

2011-01-01

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets. PMID:21876204

A Bayesian Active Learning Experimental Design for Inferring Signaling Networks.

PubMed

Ness, Robert O; Sachs, Karen; Mallick, Parag; Vitek, Olga

2018-06-21

Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity. We describe an active learning strategy for selecting optimal interventions. Our approach takes as inputs pathway databases and historic data sets, expresses them in form of prior probability distributions on network structures, and selects interventions that maximize their expected contribution to structure learning. Evaluations on simulated and real data show that the strategy reduces the detection error of validated edges as compared with an unguided choice of interventions and avoids redundant interventions, thereby increasing the effectiveness of the experiment.

Factors Affecting Cis-Dichloroethene and Vinyl Chloride Biological Transformation Under Anaerobic Conditions

DTIC Science & Technology

2006-05-01

410. 3. Baek, J-M, and C. M. Kenerley. 1998. Detection and enumeration of a genetically modified fungus in soil environments by quantitative...deduced proteome of D. ethenogenes using the complete sequence of the alcohol dehydrogenase with the most similar N-terminus (accession number ZP_00128696...chlorophenol respiration (3 1). Four orfs similru· to VcrC were also found in the deduced proteome of D. ethenogenes (38 - 47 % identity). Two of those are

Quantitative Phospho-proteomic Analysis of TNFα/NFκB Signaling Reveals a Role for RIPK1 Phosphorylation in Suppressing Necrotic Cell Death.

PubMed

Mohideen, Firaz; Paulo, Joao A; Ordureau, Alban; Gygi, Steve P; Harper, J Wade

2017-07-01

TNFα is a potent inducer of inflammation due to its ability to promote gene expression, in part via the NFκB pathway. Moreover, in some contexts, TNFα promotes Caspase-dependent apoptosis or RIPK1/RIPK3/MLKL-dependent necrosis. Engagement of the TNF Receptor Signaling Complex (TNF-RSC), which contains multiple kinase activities, promotes phosphorylation of several downstream components, including TAK1, IKKα/IKKβ, IκBα, and NFκB. However, immediate downstream phosphorylation events occurring in response to TNFα signaling are poorly understood at a proteome-wide level. Here we use Tandem Mass Tagging-based proteomics to quantitatively characterize acute TNFα-mediated alterations in the proteome and phosphoproteome with or without inhibition of the cIAP-dependent survival arm of the pathway with a SMAC mimetic. We identify and quantify over 8,000 phosphorylated peptides, among which are numerous known sites in the TNF-RSC, NFκB, and MAP kinase signaling systems, as well as numerous previously unrecognized phosphorylation events. Functional analysis of S320 phosphorylation in RIPK1 demonstrates a role for this event in suppressing its kinase activity, association with CASPASE-8 and FADD proteins, and subsequent necrotic cell death during inflammatory TNFα stimulation. This study provides a resource for further elucidation of TNFα-dependent signaling pathways. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantitative proteomics reveals the mechanism and consequence of gliotoxin-mediated dysregulation of the methionine cycle in Aspergillus niger.

PubMed

Manzanares-Miralles, Lara; Sarikaya-Bayram, Özlem; Smith, Elizabeth B; Dolan, Stephen K; Bayram, Özgür; Jones, Gary W; Doyle, Sean

2016-01-10

Gliotoxin (GT) is a redox-active metabolite, produced by Aspergillus fumigatus, which inhibits the growth of other fungi. Here we demonstrate how Aspergillus niger responds to GT exposure. Quantitative proteomics revealed that GT dysregulated the abundance of 378 proteins including those involved in methionine metabolism and induced de novo abundance of two S-adenosylmethionine (SAM)-dependent methyltransferases. Increased abundance of enzymes S-adenosylhomocysteinase (p=0.0018) required for homocysteine generation from S-adenosylhomocysteine (SAH), and spermidine synthase (p=0.0068), involved in the recycling of Met, was observed. Analysis of Met-related metabolites revealed significant increases in the levels of Met and adenosine, in correlation with proteomic data. Methyltransferase MT-II is responsible for bisthiobis(methylthio)gliotoxin (BmGT) formation, deletion of MT-II abolished BmGT formation and led to increased GT sensitivity in A. niger. Proteomic analysis also revealed that GT exposure also significantly (p<0.05) increased hydrolytic enzyme abundance, including glycoside hydrolases (n=22) and peptidases (n=16). We reveal that in an attempt to protect against the detrimental affects of GT, methyltransferase-mediated GT thiomethylation alters cellular pathways involving Met and SAM, with consequential dysregulation of hydrolytic enzyme abundance in A. niger. Thus, it provides new opportunities to exploit the response of GT-naïve fungi to GT. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry

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

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.

Current proteomics approaches are comprised of both broad discovery measurements as well as more quantitative targeted measurements. These two different measurement types are used to initially identify potentially important proteins (e.g., candidate biomarkers) and then enable improved quantification for a limited number of selected proteins. However, both approaches suffer from limitations, particularly the lower sensitivity, accuracy, and quantitation precision for discovery approaches compared to targeted approaches, and the limited proteome coverage provided by targeted approaches. Herein, we describe a new proteomics approach that allows both discovery and targeted monitoring (DTM) in a single analysis using liquid chromatography, ion mobility spectrometrymore » and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled peptides for target ions are spiked into tryptic digests and both the labeled and unlabeled peptides are broadly detected using LC-IMS-MS instrumentation, allowing the benefits of discovery and targeted approaches. To understand the possible improvement of the DTM approach, it was compared to LC-MS broad measurements using an accurate mass and time tag database and selected reaction monitoring (SRM) targeted measurements. The DTM results yielded greater peptide/protein coverage and a significant improvement in the detection of lower abundance species compared to LC-MS discovery measurements. DTM was also observed to have similar detection limits as SRM for the targeted measurements indicating its potential for combining the discovery and targeted approaches.« less

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.

Quantitative Proteomics Uncovers Novel Factors Involved in Developmental Differentiation of Trypanosoma brucei

PubMed Central

Dejung, Mario; Subota, Ines; Bucerius, Ferdinand; Dindar, Gülcin; Freiwald, Anja; Engstler, Markus; Boshart, Michael; Butter, Falk; Janzen, Christian J.

2016-01-01

Developmental differentiation is a universal biological process that allows cells to adapt to different environments to perform specific functions. African trypanosomes progress through a tightly regulated life cycle in order to survive in different host environments when they shuttle between an insect vector and a vertebrate host. Transcriptomics has been useful to gain insight into RNA changes during stage transitions; however, RNA levels are only a moderate proxy for protein abundance in trypanosomes. We quantified 4270 protein groups during stage differentiation from the mammalian-infective to the insect form and provide classification for their expression profiles during development. Our label-free quantitative proteomics study revealed previously unknown components of the differentiation machinery that are involved in essential biological processes such as signaling, posttranslational protein modifications, trafficking and nuclear transport. Furthermore, guided by our proteomic survey, we identified the cause of the previously observed differentiation impairment in the histone methyltransferase DOT1B knock-out strain as it is required for accurate karyokinesis in the first cell division during differentiation. This epigenetic regulator is likely involved in essential chromatin restructuring during developmental differentiation, which might also be important for differentiation in higher eukaryotic cells. Our proteome dataset will serve as a resource for detailed investigations of cell differentiation to shed more light on the molecular mechanisms of this process in trypanosomes and other eukaryotes. PMID:26910529

Proteome Analysis Using Isobaric Tags for Relative and Absolute Analysis Quantitation (iTRAQ) Reveals Alterations in Stress-Induced Dysfunctional Chicken Muscle.

PubMed

Xing, Tong; Wang, Chong; Zhao, Xue; Dai, Chen; Zhou, Guanghong; Xu, Xinglian

2017-04-05

The current study was designed to investigate changes in the protein profiles of pale, soft, and exudative (PSE)-like muscles of broilers subjected to transportation under high-temperature conditions, using isobaric tags for relative and absolute analysis quantitation (iTRAQ). Arbor Acres chickens (n = 112) were randomly divided into two treatments: unstressed control (CON) and 0.5 h of transport (T). Birds were transported according to a designed protocol. Pectoralis major (PM) muscle samples in the T group were collected and classified as normal (T-NOR) or PSE-like (T-PSE). Plasma activities of stress indicators, muscle microstructure, and proteome were measured. Results indicated that broilers in the T-PSE group exhibited higher activities of plasma stress indicators. The microstructure of T-PSE group showed a looser network and larger intercellular spaces in comparison to the other groups. Proteomic analysis, based on iTRAQ, revealed 29 differentially expressed proteins in the T-NOR and T-PSE groups that were involved in protein turnover, signal transduction, stress and defense, calcium handling, cell structure, and metabolism. In particular, proteins relating to the glycolysis pathway, calcium signaling, and molecular chaperones exhibited significant differences that may contribute to the inferior post-mortem meat quality. Overall, the proteomic results provide a further understanding of the mechanism of meat quality changes in response to stress.

A Skyline Plugin for Pathway-Centric Data Browsing

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

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach SRM assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). Themore » same plugin can be used for hypothesis-drive DIA data analysis, again utilizing the pathway view to help narrow down the set of proteins which will be investigated. The plugin is backed by the PNNL Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.« less

A Skyline Plugin for Pathway-Centric Data Browsing

NASA Astrophysics Data System (ADS)

Degan, Michael G.; Ryadinskiy, Lillian; Fujimoto, Grant M.; Wilkins, Christopher S.; Lichti, Cheryl F.; Payne, Samuel H.

2016-11-01

For targeted proteomics to be broadly adopted in biological laboratories as a routine experimental protocol, wet-bench biologists must be able to approach selected reaction monitoring (SRM) and parallel reaction monitoring (PRM) assay design in the same way they approach biological experimental design. Most often, biological hypotheses are envisioned in a set of protein interactions, networks, and pathways. We present a plugin for the popular Skyline tool that presents public mass spectrometry data in a pathway-centric view to assist users in browsing available data and determining how to design quantitative experiments. Selected proteins and their underlying mass spectra are imported to Skyline for further assay design (transition selection). The same plugin can be used for hypothesis-driven data-independent acquisition (DIA) data analysis, again utilizing the pathway view to help narrow down the set of proteins that will be investigated. The plugin is backed by the Pacific Northwest National Laboratory (PNNL) Biodiversity Library, a corpus of 3 million peptides from >100 organisms, and the draft human proteome. Users can upload personal data to the plugin to use the pathway navigation prior to importing their own data into Skyline.

iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress

PubMed Central

Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

2016-01-01

Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance. PMID:27902743

Quantitative and temporal proteome analysis of butyrate-treated colorectal cancer cells.

PubMed

Tan, Hwee Tong; Tan, Sandra; Lin, Qingsong; Lim, Teck Kwang; Hew, Choy Leong; Chung, Maxey C M

2008-06-01

Colorectal cancer is one of the most common cancers in developed countries, and its incidence is negatively associated with high dietary fiber intake. Butyrate, a short-chain fatty acid fermentation by-product of fiber induces cell maturation with the promotion of growth arrest, differentiation, and/or apoptosis of cancer cells. The stimulation of cell maturation by butyrate in colonic cancer cells follows a temporal progression from the early phase of growth arrest to the activation of apoptotic cascades. Previously we performed two-dimensional DIGE to identify differentially expressed proteins induced by 24-h butyrate treatment of HCT-116 colorectal cancer cells. Herein we used quantitative proteomics approaches using iTRAQ (isobaric tags for relative and absolute quantitation), a stable isotope labeling methodology that enables multiplexing of four samples, for a temporal study of HCT-116 cells treated with butyrate. In addition, cleavable ICAT, which selectively tags cysteine-containing proteins, was also used, and the results complemented those obtained from the iTRAQ strategy. Selected protein targets were validated by real time PCR and Western blotting. A model is proposed to illustrate our findings from this temporal analysis of the butyrate-responsive proteome that uncovered several integrated cellular processes and pathways involved in growth arrest, apoptosis, and metastasis. These signature clusters of butyrate-regulated pathways are potential targets for novel chemopreventive and therapeutic drugs for treatment of colorectal cancer.

Quantitative proteomics and terminomics to elucidate the role of ubiquitination and proteolysis in adaptive immunity.

PubMed

Klein, Theo; Viner, Rosa I; Overall, Christopher M

2016-10-28

Adaptive immunity is the specialized defence mechanism in vertebrates that evolved to eliminate pathogens. Specialized lymphocytes recognize specific protein epitopes through antigen receptors to mount potent immune responses, many of which are initiated by nuclear factor-kappa B activation and gene transcription. Most, if not all, pathways in adaptive immunity are further regulated by post-translational modification (PTM) of signalling proteins, e.g. phosphorylation, citrullination, ubiquitination and proteolytic processing. The importance of PTMs is reflected by genetic or acquired defects in these pathways that lead to a dysfunctional immune response. Here we discuss the state of the art in targeted proteomics and systems biology approaches to dissect the PTM landscape specifically regarding ubiquitination and proteolysis in B- and T-cell activation. Recent advances have occurred in methods for specific enrichment and targeted quantitation. Together with improved instrument sensitivity, these advances enable the accurate analysis of often rare PTM events that are opaque to conventional proteomics approaches, now rendering in-depth analysis and pathway dissection possible. We discuss published approaches, including as a case study the profiling of the N-terminome of lymphocytes of a rare patient with a genetic defect in the paracaspase protease MALT1, a key regulator protease in antigen-driven signalling, which was manifested by elevated linear ubiquitination.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Authors.

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

PubMed

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

2017-02-22

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

iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress.

PubMed

Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

2016-01-01

Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance.

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

PubMed

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

2013-07-25

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

Comparative and quantitative proteomic analysis of normal and degenerated human annulus fibrosus cells.

PubMed

Ye, Dongping; Liang, Weiguo; Dai, Libing; Zhou, Longqiang; Yao, Yicun; Zhong, Xin; Chen, Honghui; Xu, Jiake

2015-05-01

Degeneration of the intervertebral disc (IVD) is a major chronic medical condition associated with back pain. To better understand the pathogenesis of IVD degeneration, we performed comparative and quantitative proteomic analyses of normal and degenerated human annulus fibrosus (AF) cells and identified proteins that are differentially expressed between them. Annulus fibrosus cells were isolated and cultured from patients with lumbar disc herniation (the experimental group, degenerated AF cells) and scoliosis patients who underwent orthopaedic surgery (the control group, normal AF cells). Comparative proteomic analyses of normal and degenerated cultured AF cells were carried out using 2-D electrophoresis, mass spectrometric analyses, and database searching. Quantitative analyses of silver-stained 2-D electrophoresis gels of normal and degenerated cultured AF cells identified 10 protein spots that showed the most altered differential expression levels between the two groups. Among these, three proteins were decreased, including heat shock cognate 71-kDa protein, glucose-6-phosphate 1-dehydrogenase, and protocadherin-23, whereas seven proteins were increased, including guanine nucleotide-binding protein G(i) subunit α-2, superoxide dismutase, transmembrane protein 51, adenosine receptor A3, 26S protease regulatory subunit 8, lipid phosphate phosphatase-related protein, and fatty acyl-crotonic acid reductase 1. These differentially expressed proteins might be involved in the pathophysiological process of IVD degeneration and have potential values as biomarkers of the degeneration of IVD. © 2015 Wiley Publishing Asia Pty Ltd.

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

PubMed

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

2017-05-20

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

Global analysis of the rat and human platelet proteome – the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

PubMed Central

Yu, Yanbao; Leng, Taohua; Yun, Dong; Liu, Na; Yao, Jun; Dai, Ying; Yang, Pengyuan; Chen, Xian

2013-01-01

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome. PMID:20443191

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

PubMed

Du, Chao; van Wezel, Gilles P

2018-04-30

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

Proteomic Analysis of the Human Skin Proteome after In Vivo Treatment with Sodium Dodecyl Sulphate

PubMed Central

Parkinson, Erika; Skipp, Paul; Aleksic, Maja; Garrow, Andrew; Dadd, Tony; Hughes, Michael; Clough, Geraldine; O′Connor, C. David

2014-01-01

Background Skin has a variety of functions that are incompletely understood at the molecular level. As the most accessible tissue in the body it often reveals the first signs of inflammation or infection and also represents a potentially valuable source of biomarkers for several diseases. In this study we surveyed the skin proteome qualitatively using gel electrophoresis, liquid chromatography tandem mass spectrometry (GeLC-MS/MS) and quantitatively using an isobaric tagging strategy (iTRAQ) to characterise the response of human skin following exposure to sodium dodecyl sulphate (SDS). Results A total of 653 skin proteins were assigned, 159 of which were identified using GeLC-MS/MS and 616 using iTRAQ, representing the most comprehensive proteomic study in human skin tissue. Statistical analysis of the available iTRAQ data did not reveal any significant differences in the measured skin proteome after 4 hours exposure to the model irritant SDS. Conclusions This study represents the first step in defining the critical response to an irritant at the level of the proteome and provides a valuable resource for further studies at the later stages of irritant exposure. PMID:24849295

What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Global profiling of lysine reactivity and ligandability in the human proteome

NASA Astrophysics Data System (ADS)

Hacker, Stephan M.; Backus, Keriann M.; Lazear, Michael R.; Forli, Stefano; Correia, Bruno E.; Cravatt, Benjamin F.

2017-12-01

Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.

From the genome sequence to the protein inventory of Bacillus subtilis.

PubMed

Becher, Dörte; Büttner, Knut; Moche, Martin; Hessling, Bernd; Hecker, Michael

2011-08-01

Owing to the low number of proteins necessary to render a bacterial cell viable, bacteria are extremely attractive model systems to understand how the genome sequence is translated into actual life processes. One of the most intensively investigated model organisms is Bacillus subtilis. It has attracted world-wide research interest, addressing cell differentiation and adaptation on a molecular scale as well as biotechnological production processes. Meanwhile, we are looking back on more than 25 years of B. subtilis proteomics. A wide range of methods have been developed during this period for the large-scale qualitative and quantitative proteome analysis. Currently, it is possible to identify and quantify more than 50% of the predicted proteome in different cellular subfractions. In this review, we summarize the development of B. subtilis proteomics during the past 25 years. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

Global profiling of lysine reactivity and ligandability in the human proteome.

PubMed

Hacker, Stephan M; Backus, Keriann M; Lazear, Michael R; Forli, Stefano; Correia, Bruno E; Cravatt, Benjamin F

2017-12-01

Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.

Quantitative Proteomic Analysis of Optimal Cutting Temperature (OCT) Embedded Core-Needle Biopsy of Lung Cancer

NASA Astrophysics Data System (ADS)

Zhao, Xiaozheng; Huffman, Kenneth E.; Fujimoto, Junya; Canales, Jamie Rodriguez; Girard, Luc; Nie, Guangjun; Heymach, John V.; Wistuba, Igacio I.; Minna, John D.; Yu, Yonghao

2017-10-01

With recent advances in understanding the genomic underpinnings and oncogenic drivers of pathogenesis in different subtypes, it is increasingly clear that proper pretreatment diagnostics are essential for the choice of appropriate treatment options for non-small cell lung cancer (NSCLC). Tumor tissue preservation in optimal cutting temperature (OCT) compound is commonly used in the surgical suite. However, proteins recovered from OCT-embedded specimens pose a challenge for LC-MS/MS experiments, due to the large amounts of polymers present in OCT. Here we present a simple workflow for whole proteome analysis of OCT-embedded NSCLC tissue samples, which involves a simple trichloroacetic acid precipitation step. Comparisons of protein recovery between frozen versus OCT-embedded tissue showed excellent consistency with more than 9200 proteins identified. Using an isobaric labeling strategy, we quantified more than 5400 proteins in tumor versus normal OCT-embedded core needle biopsy samples. Gene ontology analysis indicated that a number of proliferative as well as squamous cell carcinoma (SqCC) marker proteins were overexpressed in the tumor, consistent with the patient's pathology based diagnosis of "poorly differentiated SqCC". Among the most downregulated proteins in the tumor sample, we noted a number of proteins with potential immunomodulatory functions. Finally, interrogation of the aberrantly expressed proteins using a candidate approach and cross-referencing with publicly available databases led to the identification of potential druggable targets in DNA replication and DNA damage repair pathways. We conclude that our approach allows LC-MS/MS proteomic analyses on OCT-embedded lung cancer specimens, opening the way to bring powerful proteomics into the clinic. [Figure not available: see fulltext.

The Utility, Limitations, and Promise of Proteomics in Animal Science

USDA-ARS?s Scientific Manuscript database

Proteomics experiments have the ability to simultaneously identify and quantify potentially thousands of proteins in one experiment. The use of this technology in animal science is still in its infancy, yet it holds significant promise as a method for advancing animal science research. Examples of...

Utility, Limitations, and Promise of Proteomics in Animal Science

USDA-ARS?s Scientific Manuscript database

Proteomics experiments have the ability to simultaneously identify and quantify thousands of proteins in one experiment. The use of this technology in veterinary/animal science is still in its infancy, yet it holds significant promise as a method for advancing veterinary/animal science research. E...

A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification.

PubMed

Tu, Chengjian; Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2017-01-30

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches. We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins. Published by Elsevier B.V.

Perturbations in the Urinary Exosome in Transplant Rejection

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

Sigdel, Tara K.; NG, Yolanda; Lee, Sangho

Background: Urine exosomes, vesicles exocytosed into urine by all renal epithelial cell types, occur under normal physiologic and disease states. Exosome contents may mirror disease-specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed and for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery. Methods: Urine exosomes were isolated by centrifugal filtration from mid-stream, second morning void, urine samples collected from kidney transplant recipients with and without biopsy matched acute rejection. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Uexo) underwent mass spectrometry-based quantitative proteomics analysis. Themore » proteome data were analyzed for significant differential protein abundances in acute rejection (AR). Results: Identifications of 1018 and 349 proteins, Uw and Uexo fractions, respectively, demonstrated a 279 protein overlap between the two urinary compartments with 25%(70) of overlapping proteins unique to Uexoand represented membrane bound proteins (p=9.31e-7). Of 349 urine exosomal proteins identified in transplant patients 220 were not previously identified in the normal urine exosomal fraction. Uexo proteins (11), functioning in the inflammatory / stress response, were more abundant in patients with biopsy-confirmed acute rejection, 3 of which were exclusive to Uexo. Uexo AR-specific biomarkers (8) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw. Conclusions: A rapid urinary exosome isolation method and quantitative measurement of enriched Uexo proteins was applied. Urine proteins specific to the exosomal fraction were detected either in unfractionated urine (at low abundances) or by Uexo fraction analysis. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Uexo fraction from normal healthy subjects. Uexo specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring for acute transplant rejection.« less

The Proteome of Native Adult Müller Glial Cells From Murine Retina*

PubMed Central

Hauser, Alexandra; Lepper, Marlen Franziska; Mayo, Rebecca

2016-01-01

To date, the proteomic profiling of Müller cells, the dominant macroglia of the retina, has been hampered because of the absence of suitable enrichment methods. We established a novel protocol to isolate native, intact Müller cells from adult murine retinae at excellent purity which retain in situ morphology and are well suited for proteomic analyses. Two different strategies of sample preparation - an in StageTips (iST) and a subcellular fractionation approach including cell surface protein profiling were used for quantitative liquid chromatography-mass spectrometry (LC-MSMS) comparing Müller cell-enriched to depleted neuronal fractions. Pathway enrichment analyses on both data sets enabled us to identify Müller cell-specific functions which included focal adhesion kinase signaling, signal transduction mediated by calcium as second messenger, transmembrane neurotransmitter transport and antioxidant activity. Pathways associated with RNA processing, cellular respiration and phototransduction were enriched in the neuronal subpopulation. Proteomic results were validated for selected Müller cell genes by quantitative real time PCR, confirming the high expression levels of numerous members of the angiogenic and anti-inflammatory annexins and antioxidant enzymes (e.g. paraoxonase 2, peroxiredoxin 1, 4 and 6). Finally, the significant enrichment of antioxidant proteins in Müller cells was confirmed by measurements on vital retinal cells using the oxidative stress indicator CM-H2DCFDA. In contrast to photoreceptors or bipolar cells, Müller cells were most efficiently protected against H2O2-induced reactive oxygen species formation, which is in line with the protein repertoire identified in the proteomic profiling. Our novel approach to isolate intact glial cells from adult retina in combination with proteomic profiling enabled the identification of novel Müller glia specific proteins, which were validated as markers and for their functional impact in glial physiology. This provides the basis to allow the discovery of novel glial specializations and will enable us to elucidate the role of Müller cells in retinal pathologies — a topic still controversially discussed. PMID:26324419

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

PubMed Central

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

2016-01-01

Cells of the vascular system release spherical vesicles, called microparticles, in the size range of 0.1–1 μm induced by a variety of stress factors resulting in variable concentrations between health and disease. Furthermore, microparticles have intercellular communication/signaling properties and interfere with inflammation and coagulation pathways. Today's most used analytical technology for microparticle characterization, flow cytometry, is lacking sensitivity and specificity, which might have led to the publication of contradicting results in the past. We propose the use of nano-liquid chromatography two-stage mass spectrometry as a nonbiased tool for quantitative MP proteome analysis. For this, we developed an improved microparticle isolation protocol and quantified the microparticle protein composition of twelve healthy volunteers with a label-free, data-dependent and independent proteomics approach on a quadrupole orbitrap instrument. Using aliquots of 250 μl platelet-free plasma from one individual donor, we achieved excellent reproducibility with an interassay coefficient of variation of 2.7 ± 1.7% (mean ± 1 standard deviation) on individual peptide intensities across 27 acquisitions performed over a period of 3.5 months. We show that the microparticle proteome between twelve healthy volunteers were remarkably similar, and that it is clearly distinguishable from whole cell and platelet lysates. We propose the use of the proteome profile shown in this work as a quality criterion for microparticle purity in proteomics studies. Furthermore, one freeze thaw cycle damaged the microparticle integrity, articulated by a loss of cytoplasm proteins, encompassing a specific set of proteins involved in regulating dynamic structures of the cytoskeleton, and thrombin activation leading to MP clotting. On the other hand, plasma membrane protein composition was unaffected. Finally, we show that multiplexed data-independent acquisition can be used for relative quantification of target proteins using Skyline software. Mass spectrometry data are available via ProteomeXchange (identifier PXD003935) and panoramaweb.org (https://panoramaweb.org/labkey/N1OHMk.url). PMID:27738094

Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics

PubMed Central

Bennett, Eric J.; Rush, John; Gygi, Steven P.; Harper, J. Wade

2010-01-01

Dynamic reorganization of signaling systems frequently accompany pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex Absolute Quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules while only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. PMID:21145461

Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics.

PubMed

Bennett, Eric J; Rush, John; Gygi, Steven P; Harper, J Wade

2010-12-10

Dynamic reorganization of signaling systems frequently accompanies pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex absolute quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules, whereas only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. Copyright © 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

2006-08-01

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

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.

Global, quantitative and dynamic mapping of protein subcellular localization

PubMed Central

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg HH

2016-01-01

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology. DOI: http://dx.doi.org/10.7554/eLife.16950.001 PMID:27278775

Comparative analysis of Staphylococcus epidermidis strains utilizing quantitative and cell surface shaving proteomics.

PubMed

Solis, Nestor; Cain, Joel A; Cordwell, Stuart J

2016-01-01

Staphylococcus epidermidis is an opportunistic pathogen that is an emerging risk factor in hospitals worldwide and is often difficult to eradicate as virulent strains produce a protective biofilm matrix. We utilized cell shaving proteomics to profile surface-exposed proteins from two fully genome sequenced S. epidermidis strains: the avirulent, non-biofilm forming ATCC12228 and the virulent, strongly adherent biofilm forming ATCC35984 (RP62A). A false positive control strategy was employed to calculate the probabilities of proteins being truly surface-exposed. A total of 78 surface-exposed proteins were identified, of which only 19 proteins were common to ATCC12228 and RP62A, and which thus represents the core surfaceome. S. epidermidis RP62A displayed additional proteins involved in biofilm formation (cell wall-associated Bhp and intercellular adhesion protein IcaB), surface antigenicity, peptidoglycan biosynthesis and antibiotic resistance. We concurrently profiled whole cell proteomes of the two strains using iTRAQ quantitation and LC-MS/MS. A total of 1610 proteins were confidently identified (representing 64% of the theoretical S. epidermidis proteome). One hundred and ninety one proteins were differentially abundant between strains. Proteins associated with RP62A were clustered into functions including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-mediated defense, sulfate assimilation, antibiotic resistance and biofilm formation. Validation of the sulfate assimilation and cysteine/methionine biosynthesis pathways showed RP62A contained elevated levels (~25% increase) of methionine that are likely linked to biofilm formation. Cell shaving and quantitative proteomics identified proteins associated with a biofilm-forming, virulent strain of S. epidermidis (RP62A). These proteins show RP62A maintains an active CRISPR-mediated defense, as well as heightened antibiotic resistance in comparison to a non-virulent, non-biofilm forming strain. Increased abundances of sulfate assimilation proteins lead to elevated intracellular methionine. Proteins and their exposed peptides identified on the surface of S. epidermidis RP62A may be useful vaccine antigens in clinical settings if administered in at-risk patients prior to surgical implantations. Copyright © 2015 Elsevier B.V. All rights reserved.

Systems proteomic analysis reveals that clusterin and tissue inhibitor of metalloproteinases 3 increase in leptomeningeal arteries affected by cerebral amyloid angiopathy.

PubMed

Manousopoulou, A; Gatherer, M; Smith, C; Nicoll, J A R; Woelk, C H; Johnson, M; Kalaria, R; Attems, J; Garbis, S D; Carare, R O

2017-10-01

Amyloid beta (Aβ) accumulation in the walls of leptomeningeal arteries as cerebral amyloid angiopathy (CAA) is a major feature of Alzheimer's disease. In this study, we used global quantitative proteomic analysis to examine the hypothesis that the leptomeningeal arteries derived from patients with CAA have a distinct endophenotypic profile compared to those from young and elderly controls. Freshly dissected leptomeningeal arteries from the Newcastle Brain Tissue Resource and Edinburgh Sudden Death Brain Bank from seven elderly (82.9 ± 7.5 years) females with severe capillary and arterial CAA, as well as seven elderly (88.3 ± 8.6 years) and five young (45.4 ± 3.9 years) females without CAA were used in this study. Arteries from four patients with CAA, two young and two elderly controls were individually analysed using quantitative proteomics. Key proteomic findings were then validated using immunohistochemistry. Bioinformatics interpretation of the results showed a significant enrichment of the immune response/classical complement and extracellular matrix remodelling pathways (P < 0.05) in arteries affected by CAA vs. those from young and elderly controls. Clusterin (apolipoprotein J) and tissue inhibitor of metalloproteinases-3 (TIMP3), validated using immunohistochemistry, were shown to co-localize with Aβ and to be up-regulated in leptomeningeal arteries from CAA patients compared to young and elderly controls. Global proteomic profiling of brain leptomeningeal arteries revealed that clusterin and TIMP3 increase in leptomeningeal arteries affected by CAA. We propose that clusterin and TIMP3 could facilitate perivascular clearance and may serve as novel candidate therapeutic targets for CAA. © 2016 The Authors. Neuropathology and Applied Neurobiology published by John Wiley & Sons Ltd on behalf of British Neuropathological Society.

Quantitative proteomics and systems analysis of cultured H9C2 cardiomyoblasts during differentiation over time supports a 'function follows form' model of differentiation.

PubMed

Kankeu, Cynthia; Clarke, Kylie; Van Haver, Delphi; Gevaert, Kris; Impens, Francis; Dittrich, Anna; Roderick, H Llewelyn; Passante, Egle; Huber, Heinrich J

2018-05-17

The rat cardiomyoblast cell line H9C2 has emerged as a valuable tool for studying cardiac development, mechanisms of disease and toxicology. We present here a rigorous proteomic analysis that monitored the changes in protein expression during differentiation of H9C2 cells into cardiomyocyte-like cells over time. Quantitative mass spectrometry followed by gene ontology (GO) enrichment analysis revealed that early changes in H9C2 differentiation are related to protein pathways of cardiac muscle morphogenesis and sphingolipid synthesis. These changes in the proteome were followed later in the differentiation time-course by alterations in the expression of proteins involved in cation transport and beta-oxidation. Studying the temporal profile of the H9C2 proteome during differentiation in further detail revealed eight clusters of co-regulated proteins that can be associated with early, late, continuous and transient up- and downregulation. Subsequent reactome pathway analysis based on these eight clusters further corroborated and detailed the results of the GO analysis. Specifically, this analysis confirmed that proteins related to pathways in muscle contraction are upregulated early and transiently, and proteins relevant to extracellular matrix organization are downregulated early. In contrast, upregulation of proteins related to cardiac metabolism occurs at later time points. Finally, independent validation of the proteomics results by immunoblotting confirmed hereto unknown regulators of cardiac structure and ionic metabolism. Our results are consistent with a 'function follows form' model of differentiation, whereby early and transient alterations of structural proteins enable subsequent changes that are relevant to the characteristic physiology of cardiomyocytes.

Guaifenesin stone matrix proteomics: a protocol for identifying proteins critical to stone formation.

PubMed

Kolbach-Mandel, A M; Mandel, N S; Cohen, S R; Kleinman, J G; Ahmed, F; Mandel, I C; Wesson, J A

2017-04-01

Drug-related kidney stones are a diagnostic problem, since they contain a large matrix (protein) fraction and are frequently incorrectly identified as matrix stones. A urine proteomics study patient produced a guaifenesin stone during her participation, allowing us to both correctly diagnose her disease and identify proteins critical to this drug stone-forming process. The patient provided three random midday urine samples for proteomics studies; one of which contained stone-like sediment with two distinct fractions. These solids were characterized with optical microscopy and Fourier transform infrared spectroscopy. Immunoblotting and quantitative mass spectrometry were used to quantitatively identify the proteins in urine and stone matrix. Infrared spectroscopy showed that the sediment was 60 % protein and 40 % guaifenesin and its metabolite guaiacol. Of the 156 distinct proteins identified in the proteomic studies, 49 were identified in the two stone-components with approximately 50 % of those proteins also found in this patient's urine. Many proteins observed in this drug-related stone have also been reported in proteomic matrix studies of uric acid and calcium containing stones. More importantly, nine proteins were highly enriched and highly abundant in the stone matrix and 8 were reciprocally depleted in urine, suggesting a critical role for these proteins in guaifenesin stone formation. Accurate stone analysis is critical to proper diagnosis and treatment of kidney stones. Many matrix proteins were common to all stone types, but likely not related to disease mechanism. This protocol defined a small set of proteins that were likely critical to guaifenesin stone formation based on their high enrichment and high abundance in stone matrix, and it should be applied to all stone types.

Comparative membrane proteomics analyses of breast cancer cell lines to understand the molecular mechanism of breast cancer brain metastasis.

PubMed

Peng, Wenjing; Zhang, Yu; Zhu, Rui; Mechref, Yehia

2017-09-01

Breast cancer is the leading type of cancer in women. Breast cancer brain metastasis is currently considered an issue of concern among breast cancer patients. Membrane proteins play important roles in breast cancer brain metastasis, involving cell adhesion and penetration of blood-brain barrier. To understand the mechanism of breast cancer brain metastasis, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed in conjunction with enrichment of membrane proteins to analyze the proteomes from five different breast cancer and a brain cancer cell lines. Quantitative proteomic data of all cell lines were compared with MDA-MB-231BR which is a brain seeking breast cancer cell line, thus representing brain metastasis characteristics. Label-free proteomics of the six cell lines facilitates the identification of 1238 proteins and the quantification of 899 proteins of which more than 70% were membrane proteins. Unsupervised principal component analysis (PCA) of the label-free proteomics data resulted in a distinct clustering of cell lines, suggesting quantitative differences in the expression of several proteins among the different cell lines. Unique protein expressions in 231BR were observed for 28 proteins. The up-regulation of STAU1, AT1B3, NPM1, hnRNP Q, and hnRNP K and the down-regulation of TUBB4B and TUBB5 were noted in 231BR relative to 231 (precursor cell lines from which 231BR is derived). These proteins might contribute to the breast cancer brain metastasis. Ingenuity pathway analysis (IPA) supported the great brain metastatic propensity of 231BR and suggested the importance of the up-regulation of integrin proteins and down-regulation of EPHA2 in brain metastasis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Proteomic Profiling of Prostate Cancer Reveals a Role for miR-128 in Prostate Cancer*

PubMed Central

Khan, Amjad P.; Poisson, Laila M.; Bhat, Vadiraja B.; Fermin, Damian; Zhao, Rong; Kalyana-Sundaram, Shanker; Michailidis, George; Nesvizhskii, Alexey I.; Omenn, Gilbert S.; Chinnaiyan, Arul M.; Sreekumar, Arun

2010-01-01

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of biomarkers of cancer invasion and disease aggressiveness. Although alterations in gene expression have been extensively quantified during neoplastic progression, complementary analyses of proteomic changes have been limited. Here we interrogate the proteomic alterations in a cohort of 15 prostate-derived tissues that included five each from adjacent benign prostate, clinically localized prostate cancer, and metastatic disease from distant sites. The experimental strategy couples isobaric tags for relative and absolute quantitation with multidimensional liquid phase peptide fractionation followed by tandem mass spectrometry. Over 1000 proteins were quantified across the specimens and delineated into clinically localized and metastatic prostate cancer-specific signatures. Included in these class-specific profiles were both proteins that were known to be dysregulated during prostate cancer progression and new ones defined by this study. Enrichment analysis of the prostate cancer-specific proteomic signature, to gain insight into the functional consequences of these alterations, revealed involvement of miR-128-a/b regulation during prostate cancer progression. This finding was validated using real time PCR analysis for microRNA transcript levels in an independent set of 15 clinical specimens. miR-128 levels were elevated in benign prostate epithelial cell lines compared with invasive prostate cancer cells. Knockdown of miR-128 induced invasion in benign prostate epithelial cells, whereas its overexpression attenuated invasion in prostate cancer cells. Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion. PMID:19955085

Comparative iTRAQ-Based Quantitative Proteomic Analysis of Pelteobagrus vachelli Liver under Acute Hypoxia: Implications in Metabolic Responses.

PubMed

Zhang, Guosong; Zhang, Jiajia; Wen, Xin; Zhao, Cheng; Zhang, Hongye; Li, Xinru; Yin, Shaowu

2017-09-01

More and more frequently these days, aquatic ecosystems are being stressed by nutrient enrichment, pollutants, and global warming, leading to a serious depletion in oxygen concentrations. Although a sudden, significant lack of oxygen will result in mortality, fishes can have an acute behavior (e.g., an increase in breathing rate, reduction in swimming frequency) and physiology responses (e.g., increase in oxygen delivery, and reduction in oxygen consumption) to hypoxia, which allows them to maintain normal physical activity. Therefore, in order to shed further light on the molecular mechanisms of hypoxia adaptation in fishes, the authors conduct comparative quantitative proteomics on Pelteobagrus vachelli livers using iTRAQ. The research identifies 511 acute hypoxia-responsive proteins in P. vachelli. Furthermore, comparison of several of the diverse key pathways studied (e.g., peroxisome pathway, PPAR signaling pathway, lipid metabolism, glycolysis/gluco-neogenesis, and amino acid metabolism) help to articulate the different mechanisms involved in the hypoxia response of P. vachelli. Data from proteome analysis shows that P. vachelli can have an acute reaction to hypoxia, including detoxification of metabolic by-products and oxidative stress in light of continued metabolic activity (e.g., peroxisomes), an activation in the capacity of catabolism to get more energy (e.g., lipolysis and amino acid catabolism), a depression in the capacity of biosynthesis to reduce energy consumption (e.g., biosynthesis of amino acids and lipids), and a shift in the aerobic and anaerobic contributions to total metabolism. The observed hypoxia-related changes in the liver proteome of the fish can help to understand or can be related to the hypoxia-related response that takes place in similar conditions in the liver or other proteomes of mammals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2012-12-01

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

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression.

PubMed

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-02-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression*

PubMed Central

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B.; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-01-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. PMID:29208753

Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics

PubMed Central

Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang

2013-01-01

Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026

The speciation of the proteome

PubMed Central

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

2008-01-01

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

Recent advances in proteomic applications for schistosomiasis research: potential clinical impact.

PubMed

Sotillo, Javier; Doolan, Denise; Loukas, Alex

2017-02-01

Schistosomiasis is a neglected tropical disease affecting hundreds of millions of people worldwide. Recent advances in the field of proteomics and the development of new and highly sensitive mass spectrometers and quantitative techniques have provided new tools for advancing the molecular biology, cell biology, diagnosis and vaccine development for public health threats such as schistosomiasis. Areas covered: In this review we describe the latest advances in research that utilizes proteomics-based tools to address some of the key challenges to developing effective interventions against schistosomiasis. We also provide information about the potential of extracellular vesicles to advance the fight against this devastating disease. Expert commentary: Different proteins are already being tested as vaccines against schistosomiasis with promising results. The re-analysis of the Schistosoma spp. proteomes using new and more sensitive mass spectrometers as well as better separation approaches will help identify more vaccine targets in a rational and informed manner. In addition, the recent development of new proteome microarrays will facilitate characterisation of novel markers of infection as well as new vaccine and diagnostic candidate antigens.

A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics

PubMed Central

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

2015-01-01

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

Proteomics identifies the composition and manufacturing recipe of the 2500-year old sourdough bread from Subeixi cemetery in China.

PubMed

Shevchenko, Anna; Yang, Yimin; Knaust, Andrea; Thomas, Henrik; Jiang, Hongen; Lu, Enguo; Wang, Changsui; Shevchenko, Andrej

2014-06-13

We report on the geLC-MS/MS proteomics analysis of cereals and cereal food excavated in Subeixi cemetery (500-300BC) in Xinjiang, China. Proteomics provided direct evidence that at the Subexi sourdough bread was made from barley and broomcorn millet by leavening with a renewable starter comprising baker's yeast and lactic acid bacteria. The baking recipe and flour composition indicated that barley and millet bread belonged to the staple food already in the first millennium BC and suggested the role of Turpan basin as a major route for cultural communication between Western and Eastern Eurasia in antiquity. This article is part of a Special Issue entitled: Proteomics of non-model organisms. We demonstrate that organic residues of thousand year old foods unearthed by archeological excavations can be analyzed by geLC-MS/MS proteomics with good representation of protein source organisms and coverage of sequences of identified proteins. In-depth look into the foods proteome identifies the food type and its individual ingredients, reveals ancient food processing technologies, projects their social and economic impact and provides evidence of intercultural communication between ancient populations. Proteomics analysis of ancient organic residues is direct, quantitative and informative and therefore has the potential to develop into a valuable, generally applicable tool in archaeometry. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2013. Published by Elsevier B.V.

Controlled vocabularies and ontologies in proteomics: Overview, principles and practice☆

PubMed Central

Mayer, Gerhard; Jones, Andrew R.; Binz, Pierre-Alain; Deutsch, Eric W.; Orchard, Sandra; Montecchi-Palazzi, Luisa; Vizcaíno, Juan Antonio; Hermjakob, Henning; Oveillero, David; Julian, Randall; Stephan, Christian; Meyer, Helmut E.; Eisenacher, Martin

2014-01-01

This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the “mapping files” used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23429179

Low Mass Blood Peptides Discriminative of Inflammatory Bowel Disease (IBD) Severity: A Quantitative Proteomic Perspective*

PubMed Central

Yau, Yunki; Duo, Xizi; Zeng, Ming; Campbell, Beth; Shin, Sean; Luber, Raphael; Redmond, Diane; Leong, Rupert W. L.

2016-01-01

Breakdown of the protective gut barrier releases effector molecules and degradation products into the blood stream making serum and plasma ideal as a diagnostic medium. The enriched low mass proteome is unexplored as a source of differentiators for diagnosing and monitoring inflammatory bowel disease (IBD) activity, that is less invasive than colonoscopy. Differences in the enriched low mass plasma proteome (<25 kDa) were assessed by label-free quantitative mass-spectrometry. A panel of marker candidates were progressed to validation phase and “Tier-2” FDA-level validated quantitative assay. Proteins important in maintaining gut barrier function and homeostasis at the epithelial interface have been quantitated by multiple reaction monitoring in plasma and serum including both inflammatory; rheumatoid arthritis controls, and non-inflammatory healthy controls; ulcerative colitis (UC), and Crohn's disease (CD) patients. Detection by immunoblot confirmed presence at the protein level in plasma. Correlation analysis and receiver operator characteristics were used to report the sensitivity and specificity. Peptides differentiating controls from IBD originate from secreted phosphoprotein 24 (SPP24, p = 0.000086, 0.009); whereas those in remission and healthy can be differentiated in UC by SPP24 (p = 0.00023, 0.001), α-1-microglobulin (AMBP, p = 0.006) and CD by SPP24 (p = 0.019, 0.05). UC and CD can be differentiated by Guanylin (GUC2A, p = 0.001), and Secretogranin-1 (CHGB p = 0.035). Active and quiescent disease can also be differentiated in UC and CD by CHGB (p ≤ 0.023) SPP24 (p ≤ 0.023) and AMBP (UC p = 0.046). Five peptides discriminating IBD activity and severity had very little-to-no correlation to erythrocyte sedimentation rate, C-reactive protein, white cell or platelet counts. Three of these peptides were found to be binding partners to SPP24 protein alongside other known matrix proteins. These proteins have the potential to improve diagnosis and evaluate IBD activity, reducing the need for more invasive techniques. Data are available via ProteomeXchange with identifier PXD002821. PMID:26530476

iTRAQ-based quantitative proteomics analysis of molecular mechanisms associated with Bombyx mori (Lepidoptera) larval midgut response to BmNPV in susceptible and near-isogenic strains.

PubMed

Yu, Haizhong; Wang, Xueyang; Xu, Jiaping; Ma, Yan; Zhang, Shangzhi; Yu, Dong; Fei, Dongqiong; Muhammad, Azharuddin

2017-08-08

Bombyx mori nucleopolyhedrovirus (BmNPV) has been identified as a major pathogen responsible for severe economic loss. Most silkworm strains are susceptible to BmNPV, with only a few highly resistant strains thus far identified. Here we investigated the molecular basis of silkworm resistance to BmNPV using susceptible (the recurrent parent P50) and resistant (near-isogenic line BC9) strains and a combination of iTRAQ-based quantitative proteomics, reverse-transcription quantitative PCR and Western blotting. By comparing the proteomes of infected and non-infected P50 and BC9 silkworms, we identified 793 differentially expressed proteins (DEPs). By gene ontology and KEGG enrichment analyses, we found that these DEPs are preferentially involved in metabolism, catalytic activity, amino sugar and nucleotide sugar metabolism and carbon metabolism. 114 (14.38%) DEPs were associated with the cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. After removing the genetic background and individual immune stress response proteins, we identified 84 DEPs were found that are potentially involved in resistance to BmNPV. Further studies showed that a serine protease was down-regulated in P50 and up-regulated in BC9 after BmNPV infection. Taken together, these results provide insights into the molecular mechanism of silkworm response to BmNPV. Bombyx mori nucleopolyhedrovirus (BmNPV) is highly pathogenic, causing serious losses in sericulture every year. However, the molecular mechanisms of BmNPV infection and host defence remain unclear. Here we combined quantitative proteomic, bioinformatics, RT-qPCR and Western blotting analyses and found that BmNPV invasion causes complex protein alterations in the larval midgut, and that these changes are related to cytoskeleton, immune response, apoptosis, ubiquitination, translation, ion transport, endocytosis and endopeptidase activity. Five important differentially expression proteins were validation by independent approaches. These finding will help address the molecular mechanisms of silkworm resistance to BmNPV and provide a molecular target for resisting BmNPV. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-01-01

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

Absolute quantitation of isoforms of post-translationally modified proteins in transgenic organism.

PubMed

Li, Yaojun; Shu, Yiwei; Peng, Changchao; Zhu, Lin; Guo, Guangyu; Li, Ning

2012-08-01

Post-translational modification isoforms of a protein are known to play versatile biological functions in diverse cellular processes. To measure the molar amount of each post-translational modification isoform (P(isf)) of a target protein present in the total protein extract using mass spectrometry, a quantitative proteomic protocol, absolute quantitation of isoforms of post-translationally modified proteins (AQUIP), was developed. A recombinant ERF110 gene overexpression transgenic Arabidopsis plant was used as the model organism for demonstration of the proof of concept. Both Ser-62-independent (14)N-coded synthetic peptide standards and (15)N-coded ERF110 protein standard isolated from the heavy nitrogen-labeled transgenic plants were employed simultaneously to determine the concentration of all isoforms (T(isf)) of ERF110 in the whole plant cell lysate, whereas a pair of Ser-62-dependent synthetic peptide standards were used to quantitate the Ser-62 phosphosite occupancy (R(aqu)). The P(isf) was finally determined by integrating the two empirically measured variables using the following equation: P(isf) = T(isf) · R(aqu). The absolute amount of Ser-62-phosphorylated isoform of ERF110 determined using AQUIP was substantiated with a stable isotope labeling in Arabidopsis-based relative and accurate quantitative proteomic approach. The biological role of the Ser-62-phosphorylated isoform was demonstrated in transgenic plants.

High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

PubMed Central

2015-01-01

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer. PMID:25405479

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach.

PubMed

Guruceaga, Elizabeth; Garin-Muga, Alba; Prieto, Gorka; Bejarano, Bartolomé; Marcilla, Miguel; Marín-Vicente, Consuelo; Perez-Riverol, Yasset; Casal, J Ignacio; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2017-12-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach

PubMed Central

2017-01-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations. PMID:28960077

Unifying expression scale for peptide hydrophobicity in proteomic reversed phase high-pressure liquid chromatography experiments.

PubMed

Grigoryan, Marine; Shamshurin, Dmitry; Spicer, Victor; Krokhin, Oleg V

2013-11-19

As an initial step in our efforts to unify the expression of peptide retention times in proteomic liquid chromatography-mass spectrometry (LC-MS) experiments, we aligned the chromatographic properties of a number of peptide retention standards against a collection of peptides commonly observed in proteomic experiments. The standard peptide mixtures and tryptic digests of samples of different origins were separated under the identical chromatographic condition most commonly employed in proteomics: 100 Å C18 sorbent with 0.1% formic acid as an ion-pairing modifier. Following our original approach (Krokhin, O. V.; Spicer, V. Anal. Chem. 2009, 81, 9522-9530) the retention characteristics of these standards and collection of tryptic peptides were mapped into hydrophobicity index (HI) or acetonitrile percentage units. This scale allows for direct visualization of the chromatographic outcome of LC-MS acquisitions, monitors the performance of the gradient LC system, and simplifies method development and interlaboratory data alignment. Wide adoption of this approach would significantly aid understanding the basic principles of gradient peptide RP-HPLC and solidify our collective efforts in acquiring confident peptide retention libraries, a key component in the development of targeted proteomic approaches.

Analyzing large-scale proteomics projects with latent semantic indexing.

PubMed

Klie, Sebastian; Martens, Lennart; Vizcaíno, Juan Antonio; Côté, Richard; Jones, Phil; Apweiler, Rolf; Hinneburg, Alexander; Hermjakob, Henning

2008-01-01

Since the advent of public data repositories for proteomics data, readily accessible results from high-throughput experiments have been accumulating steadily. Several large-scale projects in particular have contributed substantially to the amount of identifications available to the community. Despite the considerable body of information amassed, very few successful analyses have been performed and published on this data, leveling off the ultimate value of these projects far below their potential. A prominent reason published proteomics data is seldom reanalyzed lies in the heterogeneous nature of the original sample collection and the subsequent data recording and processing. To illustrate that at least part of this heterogeneity can be compensated for, we here apply a latent semantic analysis to the data contributed by the Human Proteome Organization's Plasma Proteome Project (HUPO PPP). Interestingly, despite the broad spectrum of instruments and methodologies applied in the HUPO PPP, our analysis reveals several obvious patterns that can be used to formulate concrete recommendations for optimizing proteomics project planning as well as the choice of technologies used in future experiments. It is clear from these results that the analysis of large bodies of publicly available proteomics data by noise-tolerant algorithms such as the latent semantic analysis holds great promise and is currently underexploited.

Quantitative proteomics of bronchoalveolar lavage fluid in lung adenocarcinoma.

PubMed

Almatroodi, Saleh A; McDonald, Christine F; Collins, Allison L; Darby, Ian A; Pouniotis, Dodie S

2015-01-01

The most commonly reported primary lung cancer subtype is adenocarcinoma, which is associated with a poor prognosis and short survival. Proteomic studies on human body fluids such as bronchoalveolar lavage fluid (BALF) have become essential methods for biomarker discovery, examination of tumor pathways and investigation of potential treatments. This study used quantitative proteomics to investigate the up-regulation of novel proteins in BALF from patients with primary lung adenocarcinoma in order to identify potential biomarkers. BALF samples from individuals with and without primary lung adenocarcinoma were analyzed using liquid chromatography-mass spectrometry. One thousand and one hundred proteins were identified, 33 of which were found to be consistently overexpressed in all lung adenocarcinoma samples compared to non-cancer controls. A number of overexpressed proteins have been previously shown to be related to lung cancer progression including S100-A8, annexin A1, annexin A2, thymidine phosphorylase and transglutaminase 2. The overexpression of a number of specific proteins in BALF from patients with primary lung adenocarcinoma may be used as a potential biomarker for lung adenocarcinoma. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

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

PubMed

Chahrour, Osama; Cobice, Diego; Malone, John

2015-09-10

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

Quantitative proteomic analysis of whey proteins in the colostrum and mature milk of yak (Bos grunniens).

PubMed

Yang, Yongxin; Zhao, Xiaowei; Yu, Shumin; Cao, Suizhong

2015-02-01

Yak (Bos grunniens) is an important natural resource in mountainous regions. To date, few studies have addressed the differences in the protein profiles of yak colostrum and milk. We used quantitative proteomics to compare the protein profiles of whey from yak colostrum and milk. Milk samples were collected from 21 yaks after calving (1 and 28 d). Whey protein profiles were generated through isobaric tag for relative and absolute quantification (iTRAQ)-labelled proteomics. We identified 183 proteins in milk whey; of these, the expression levels of 86 proteins differed significantly between the whey from colostrum and milk. Haemoglobin expression showed the greatest change; its levels were significantly higher in the whey from colostrum than in mature milk whey. Functional analysis revealed that many of the differentially expressed proteins were associated with biological regulation and response to stimuli. Further, eight differentially expressed proteins involved in the complement and coagulation cascade pathway were enriched in milk whey. These findings add to the general understanding of the protein composition of yak milk, suggest potential functions of the differentially expressed proteins, and provide novel information on the role of colostral components in calf survival. © 2014 Society of Chemical Industry.

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

PubMed

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

2009-12-01

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

Quantitative proteomic analyses of the microbial degradation of estrone under various background nitrogen and carbon conditions.

PubMed

Du, Zhe; Chen, Yinguang; Li, Xu

2017-10-15

Microbial degradation of estrogenic compounds can be affected by the nitrogen source and background carbon in the environment. However, the underlying mechanisms are not well understood. The objective of this study was to elucidate the molecular mechanisms of estrone (E1) biodegradation at the protein level under various background nitrogen (nitrate or ammonium) and carbon conditions (no background carbon, acetic acid, or humic acid as background carbon) by a newly isolated bacterial strain. The E1 degrading bacterial strain, Hydrogenophaga atypica ZD1, was isolated from river sediments and its proteome was characterized under various experimental conditions using quantitative proteomics. Results show that the E1 degradation rate was faster when ammonium was used as the nitrogen source than with nitrate. The degradation rate was also faster when either acetic acid or humic acid was present in the background. Proteomics analyses suggested that the E1 biodegradation products enter the tyrosine metabolism pathway. Compared to nitrate, ammonium likely promoted E1 degradation by increasing the activities of the branched-chain-amino-acid aminotransferase (IlvE) and enzymes involved in the glutamine synthetase-glutamine oxoglutarate aminotransferase (GS-GOGAT) pathway. The increased E1 degradation rate with acetic acid or humic acid in the background can also be attributed to the up-regulation of IlvE. Results from this study can help predict and explain E1 biodegradation kinetics under various environmental conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

PubMed

Qi, Da; Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R

2015-09-01

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative analysis of oyster larval proteome provides new insights into the effects of multiple climate change stressors.

PubMed

Dineshram, Ramadoss; Chandramouli, Kondethimmanahalli; Ko, Ginger Wai Kuen; Zhang, Huoming; Qian, Pei-Yuan; Ravasi, Timothy; Thiyagarajan, Vengatesen

2016-06-01

The metamorphosis of planktonic larvae of the Pacific oyster (Crassostrea gigas) underpins their complex life-history strategy by switching on the molecular machinery required for sessile life and building calcite shells. Metamorphosis becomes a survival bottleneck, which will be pressured by different anthropogenically induced climate change-related variables. Therefore, it is important to understand how metamorphosing larvae interact with emerging climate change stressors. To predict how larvae might be affected in a future ocean, we examined changes in the proteome of metamorphosing larvae under multiple stressors: decreased pH (pH 7.4), increased temperature (30 °C), and reduced salinity (15 psu). Quantitative protein expression profiling using iTRAQ-LC-MS/MS identified more than 1300 proteins. Decreased pH had a negative effect on metamorphosis by down-regulating several proteins involved in energy production, metabolism, and protein synthesis. However, warming switched on these down-regulated pathways at pH 7.4. Under multiple stressors, cell signaling, energy production, growth, and developmental pathways were up-regulated, although metamorphosis was still reduced. Despite the lack of lethal effects, significant physiological responses to both individual and interacting climate change related stressors were observed at proteome level. The metamorphosing larvae of the C. gigas population in the Yellow Sea appear to have adequate phenotypic plasticity at the proteome level to survive in future coastal oceans, but with developmental and physiological costs. © 2016 John Wiley & Sons Ltd.

New insights into the mechanisms of acetic acid resistance in Acetobacter pasteurianus using iTRAQ-dependent quantitative proteomic analysis.

PubMed

Xia, Kai; Zang, Ning; Zhang, Junmei; Zhang, Hong; Li, Yudong; Liu, Ye; Feng, Wei; Liang, Xinle

2016-12-05

Acetobacter pasteurianus is the main starter in rice vinegar manufacturing due to its remarkable abilities to resist and produce acetic acid. Although several mechanisms of acetic acid resistance have been proposed and only a few effector proteins have been identified, a comprehensive depiction of the biological processes involved in acetic acid resistance is needed. In this study, iTRAQ-based quantitative proteomic analysis was adopted to investigate the whole proteome of different acidic titers (3.6, 7.1 and 9.3%, w/v) of Acetobacter pasteurianus Ab3 during the vinegar fermentation process. Consequently, 1386 proteins, including 318 differentially expressed proteins (p<0.05), were identified. Compared to that in the low titer circumstance, cells conducted distinct biological processes under high acetic acid stress, where >150 proteins were differentially expressed. Specifically, proteins involved in amino acid metabolic processes and fatty acid biosynthesis were differentially expressed, which may contribute to the acetic acid resistance of Acetobacter. Transcription factors, two component systems and toxin-antitoxin systems were implicated in the modulatory network at multiple levels. In addition, the identification of proteins involved in redox homeostasis, protein metabolism, and the cell envelope suggested that the whole cellular system is mobilized in response to acid stress. These findings provide a differential proteomic profile of acetic acid resistance in Acetobacter pasteurianus and have potential application to highly acidic rice vinegar manufacturing. Copyright © 2016 Elsevier B.V. All rights reserved.

Chronic intermittent ethanol exposure and withdrawal leads to adaptations in nucleus accumbens core postsynaptic density proteome and dendritic spines.

PubMed

Uys, Joachim D; McGuier, Natalie S; Gass, Justin T; Griffin, William C; Ball, Lauren E; Mulholland, Patrick J

2016-05-01

Alcohol use disorder is a chronic relapsing brain disease characterized by the loss of ability to control alcohol (ethanol) intake despite knowledge of detrimental health or personal consequences. Clinical and pre-clinical models provide strong evidence for chronic ethanol-associated alterations in glutamatergic signaling and impaired synaptic plasticity in the nucleus accumbens (NAc). However, the neural mechanisms that contribute to aberrant glutamatergic signaling in ethanol-dependent individuals in this critical brain structure remain unknown. Using an unbiased proteomic approach, we investigated the effects of chronic intermittent ethanol (CIE) exposure on neuroadaptations in postsynaptic density (PSD)-enriched proteins in the NAc of ethanol-dependent mice. Compared with controls, CIE exposure significantly changed expression levels of 50 proteins in the PSD-enriched fraction. Systems biology and functional annotation analyses demonstrated that the dysregulated proteins are expressed at tetrapartite synapses and critically regulate cellular morphology. To confirm this latter finding, the density and morphology of dendritic spines were examined in the NAc core of ethanol-dependent mice. We found that CIE exposure and withdrawal differentially altered dendrite diameter and dendritic spine density and morphology. Through the use of quantitative proteomics and functional annotation, these series of experiments demonstrate that ethanol dependence produces neuroadaptations in proteins that modify dendritic spine morphology. In addition, these studies identified novel PSD-related proteins that contribute to the neurobiological mechanisms of ethanol dependence that drive maladaptive structural plasticity of NAc neurons. © 2015 Society for the Study of Addiction.