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1.  The State of the Human Proteome in 2013 as viewed through PeptideAtlas: Comparing the Kidney, Urine, and Plasma Proteomes for the Biology and Disease-driven Human Proteome Project 
Journal of proteome research  2013;13(1):60-75.
The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics datasets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively—for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ~14,000 Swiss-Prot entries, an increase over 2012 of ~7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue.
doi:10.1021/pr4010037
PMCID: PMC3951210  PMID: 24261998
Human Proteome Project; PeptideAtlas; LC-MS/MS; database; kidney; plasma; urine; proteome comparison
2.  Community-integrated omics links dominance of a microbial generalist to fine-tuned resource usage 
Nature Communications  2014;5:5603.
Microbial communities are complex and dynamic systems that are primarily structured according to their members’ ecological niches. To investigate how niche breadth (generalist versus specialist lifestyle strategies) relates to ecological success, we develop and apply an integrative workflow for the multi-omic analysis of oleaginous mixed microbial communities from a biological wastewater treatment plant. Time- and space-resolved coupled metabolomic and taxonomic analyses demonstrate that the community-wide lipid accumulation phenotype is associated with the dominance of the generalist bacterium Candidatus Microthrix spp. By integrating population-level genomic reconstructions (reflecting fundamental niches) with transcriptomic and proteomic data (realised niches), we identify finely tuned gene expression governing resource usage by Candidatus Microthrix parvicella over time. Moreover, our results indicate that the fluctuating environmental conditions constrain the accumulation of genetic variation in Candidatus Microthrix parvicella likely due to fitness trade-offs. Based on our observations, niche breadth has to be considered as an important factor for understanding the evolutionary processes governing (microbial) population sizes and structures in situ.
Within microbial communities, microorganisms adopt different lifestyle strategies to use the available resources. Here, the authors use an integrated ‘multi-omic’ approach to study niche breadth (generalist versus specialist lifestyles) in oleaginous microbial assemblages from an anoxic wastewater treatment tank.
doi:10.1038/ncomms6603
PMCID: PMC4263124  PMID: 25424998
3.  Mass fingerprinting of complex mixtures: protein inference from high-resolution peptide masses and predicted retention times 
Journal of proteome research  2013;12(12):10.1021/pr400705q.
In typical shotgun experiments, the mass spectrometer records the masses of a large set of ionized analytes, but fragments only a fraction of them. In the subsequent analyses, only the fragmented ions are used to compile a set of peptide identifications, while the unfragmented ones are disregarded. In this work we show how the unfragmented ions, here denoted MS1-features, can be used to increase the confidence of the proteins identified in shotgun experiments. Specifically, we propose the usage of in silico tags, where the observed MS1-features are matched against de novo predicted masses and retention times for all the peptides derived from a sequence database. We present a statistical model to assign protein-level probabilities based on the MS1-features, and combine this data with the fragmentation spectra. Our approach was evaluated for two triplicate datasets from yeast and human, respectively, leading to up to 7% more protein identifications at a fixed protein-level false discovery rate of 1%. The additional protein identifications were validated both in the context of the mass spectrometry data, and by examining their estimated transcript levels generated using RNA-Seq. The proposed method is reproducible, straightforward to apply, and can even be used to re-analyze and increase the yield of existing datasets.
Principle contribution
A statistical framework that uses the unfragmented MS1-features to increase the confidence of the proteins identified in shotgun experiments.
doi:10.1021/pr400705q
PMCID: PMC3860378  PMID: 24074221
4.  Current algorithmic solutions for peptide-based proteomics data generation and identification 
Current opinion in biotechnology  2012;24(1):10.1016/j.copbio.2012.10.013.
Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics.
doi:10.1016/j.copbio.2012.10.013
PMCID: PMC3857305  PMID: 23142544
5.  An Assessment of Current Bioinformatic Solutions for Analyzing LC-MS data Acquired by Selected Reaction Monitoring Technology 
Proteomics  2012;12(8):10.1002/pmic.201100571.
Selected reaction monitoring (SRM) is an accurate quantitative technique, typically used for small-molecule mass spectrometry (MS). SRM has emerged as an important technique for targeted and hypothesis-driven proteomic research, and is becoming the reference method for protein quantification in complex biological samples. SRM offers high selectivity, a lower limit of detection and improved reproducibility, compared to conventional shot-gun based tandem MS (LC-MS/MS) methods. Unlike LC-MS/MS, which requires computationally intensive informatic post-analysis, SRM requires pre-acquisition bioinformatic analysis to determine proteotypic peptides and optimal transitions to uniquely identify and to accurately quantitate proteins of interest. Extensive arrays of bioinformatics software tools, both web-based and stand-alone, have been published to assist researchers to determine optimal peptides and transition sets. The transitions are oftentimes selected based on preferred precursor charge state, peptide molecular weight, hydrophobicity, fragmentation pattern at a given collision energy (CE), and instrumentation chosen. Validation of the selected transitions for each peptide is critical since peptide performance varies depending on the mass spectrometer used. In this review, we provide an overview of open source and commercial bioinformatic tools for analyzing LC-MS data acquired by SRM.
doi:10.1002/pmic.201100571
PMCID: PMC3857306  PMID: 22577019
Bioinformatics; Mass Spectrometry; Selected Reaction Monitoring; Transition
6.  Comparative proteome analysis reveals conserved and specific adaptation patterns of Staphylococcus aureus after internalization by different types of human non-professional phagocytic host cells 
Staphylococcus aureus is a human pathogen that can cause a wide range of diseases. Although formerly regarded as extracellular pathogen, it has been shown that S. aureus can also be internalized by host cells and persist within these cells. In the present study, we comparatively analyzed survival and physiological adaptation of S. aureus HG001 after internalization by two human lung epithelial cell lines (S9 and A549), and human embryonic kidney cells (HEK 293). Combining enrichment of bacteria from host-pathogen assays by cell sorting and quantitation of the pathogen's proteome by mass spectrometry we characterized S. aureus adaptation during the initial phase between 2.5 h and 6.5 h post-infection. Starting with about 2 × 106 bacteria, roughly 1450 S. aureus proteins, including virulence factors and metabolic enzymes were identified by spectral comparison and classical database searches. Most of the bacterial adaptation reactions, such as decreased levels of ribosomal proteins and metabolic enzymes or increased amounts of proteins involved in arginine and lysine biosynthesis, enzymes coding for terminal oxidases and stress responsive proteins or activation of the sigma factor SigB were observed after internalization into any of the three cell lines studied. However, differences were noted in central carbon metabolism including regulation of fermentation and threonine degradation. Since these differences coincided with different intracellular growth behavior, complementary profiling of the metabolome of the different non-infected host cell types was performed. This revealed similar levels of intracellular glucose but host cell specific differences in the amounts of amino acids such as glycine, threonine or glutamate. With this comparative study we provide an impression of the common and specific features of the adaptation of S. aureus HG001 to specific host cell environments as a starting point for follow-up studies with different strain isolates and regulatory mutants.
doi:10.3389/fmicb.2014.00392
PMCID: PMC4117987  PMID: 25136337
Staphylococcus aureus; human cell lines; host-pathogen interaction; proteomics; label-free quantitation
7.  The Mtb Proteome Library: A Resource of Assays to Quantify the Complete Proteome of Mycobacterium tuberculosis 
Cell host & microbe  2013;13(5):602-612.
SUMMARY
Research advancing our understanding of Mycobacterium tuberculosis (Mtb) biology and complex host-Mtb interactions requires consistent and precise quantitative measurements of Mtb proteins. We describe the generation and validation of a compendium of assays to quantify 97% of the 4,012 annotated Mtb proteins by the targeted mass spectrometric method selected reaction monitoring (SRM). Furthermore, we estimate the absolute abundance for 55% of all Mtb proteins, revealing a dynamic range within the Mtb proteome of over four orders of magnitude, and identify previously un-annotated proteins. As an example of the assay library utility, we monitored the entire Mtb dormancy survival regulon (DosR), which is linked to anaerobic survival and Mtb persistence, and show its dynamic protein-level regulation during hypoxia. In conclusion, we present a publicly available research resource that supports the sensitive, precise, and reproducible quantification of virtually any Mtb protein by a robust and widely accessible mass spectrometric method.
doi:10.1016/j.chom.2013.04.008
PMCID: PMC3766585  PMID: 23684311
8.  New and improved proteomics technologies for understanding complex biological systems: Addressing a grand challenge in the life sciences 
Proteomics  2012;12(18):2773-2783.
This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14–15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development.
doi:10.1002/pmic.201270086
PMCID: PMC4005326  PMID: 22807061
Complex systems; Democratization of proteomics; Economic growth; Grand challenges; Integration; Systems biology
9.  The state of the human proteome in 2012 as viewed through PeptideAtlas 
Journal of proteome research  2012;12(1):162-171.
The Human Proteome Project was launched in September 2010 with the goal of characterizing at least one protein product from each protein-coding gene. Here we assess how much of the proteome has been detected to date via tandem mass spectrometry by analyzing PeptideAtlas, a compendium of human derived LC-MS/MS proteomics data from many laboratories around the world. All datasets are processed with a consistent set of parameters using the Trans-Proteomic Pipeline and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas. Therefore, PeptideAtlas contains only high confidence protein identifications. To increase proteome coverage, we explored new comprehensive public data sources for data likely to add new proteins to the Human PeptideAtlas. We then folded these data into a Human PeptideAtlas 2012 build and mapped it to Swiss-Prot, a protein sequence database curated to contain one entry per human protein coding gene. We find that this latest PeptideAtlas build includes at least one peptide for each of ~12,500 Swiss-Prot entries, leaving ~7500 gene products yet to be confidently cataloged. We characterize these “PA-unseen” proteins in terms of tissue localization, transcript abundance, and Gene Ontology enrichment, and propose reasons for their absence from PeptideAtlas and strategies for detecting them in the future.
doi:10.1021/pr301012j
PMCID: PMC3928036  PMID: 23215161
Human Proteome Project; PeptideAtlas; LC-MS/MS; database; protein inference
10.  Identification of peptide features in precursor spectra using Hardklör and Krönik 
Hardklör and Krönik are software tools for feature detection and data reduction of high resolution mass spectra. Hardklör is used to reduce peptide isotope distributions to a single monoisotopic mass and charge state, and can deconvolve overlapping peptide isotope distributions. Krönik filters, validates, and summarizes peptide features identified with Hardklör from data obtained during liquid chromatography mass spectrometry (LC-MS). Both software tools contain a simple user interface and can be run from nearly any desktop computer. These tools are freely available from http://proteome.gs.washington.edu/software/hardklor.
doi:10.1002/0471250953.bi1318s37
PMCID: PMC3891918  PMID: 22389013
proteomics; mass spectrometry; liquid chromatography; high resolution; feature detection; deisotoping; peptide isotope distribution
11.  PASSEL: The PeptideAtlas SRM Experiment Library 
Proteomics  2012;12(8):10.1002/pmic.201100515.
Public repositories for proteomics data have accelerated proteomics research by enabling more efficient cross-analyses of datasets, supporting the creation of protein and peptide compendia of experimental results, supporting the development and testing of new software tools, and facilitating the manuscript review process. The repositories available to date have been designed to accommodate either shotgun experiments or generic proteomic data files. Here, we describe a new kind of proteomic data repository for the collection and representation of data from selected reaction monitoring (SRM) measurements. The PeptideAtlas SRM Experiment Library (PASSEL) allows researchers to easily submit proteomic data sets generated by SRM. The raw data are automatically processed in a uniform manner and the results are stored in a database, where they may be downloaded or browsed via a web interface that includes a chromatogram viewer. PASSEL enables cross-analysis of SRM data, supports optimization of SRM data collection, and facilitates the review process of SRM data. Further, PASSEL will help in the assessment of proteotypic peptide performance in a wide array of samples containing the same peptide, as well as across multiple experimental protocols.
doi:10.1002/pmic.201100515
PMCID: PMC3832291  PMID: 22318887
data repository; MRM; software; SRM; targeted proteomics
13.  The Microvesicle Component of HIV-1 Inocula Modulates Dendritic Cell Infection and Maturation and Enhances Adhesion to and Activation of T Lymphocytes 
PLoS Pathogens  2013;9(10):e1003700.
HIV-1 is taken up by immature monocyte derived dendritic cells (iMDDCs) into tetraspanin rich caves from which the virus can either be transferred to T lymphocytes or enter into endosomes resulting in degradation. HIV-1 binding and fusion with the DC membrane results in low level de novo infection that can also be transferred to T lymphocytes at a later stage. We have previously reported that HIV-1 can induce partial maturation of iMDDCs at both stages of trafficking. Here we show that CD45+ microvesicles (MV) which contaminate purified HIV-1 inocula due to similar size and density, affect DC maturation, de novo HIV-1 infection and transfer to T lymphocytes. Comparing iMDDCs infected with CD45-depleted HIV-1BaL or matched non-depleted preparations, the presence of CD45+ MVs was shown to enhance DC maturation and ICAM-1 (CD54) expression, which is involved in DC∶T lymphocyte interactions, while restricting HIV-1 infection of MDDCs. Furthermore, in the DC culture HIV-1 infected (p24+) MDDCs were more mature than bystander cells. Depletion of MVs from the HIV-1 inoculum markedly inhibited DC∶T lymphocyte clustering and the induction of alloproliferation as well as limiting HIV-1 transfer from DCs to T lymphocytes. The effects of MV depletion on these functions were reversed by the re-addition of purified MVs from activated but not non-activated SUPT1.CCR5-CL.30 or primary T cells. Analysis of the protein complement of these MVs and of these HIV-1 inocula before and after MV depletion showed that Heat Shock Proteins (HSPs) and nef were the likely DC maturation candidates. Recombinant HSP90α and β and nef all induced DC maturation and ICAM-1 expression, greater when combined. These results suggest that MVs contaminating HIV-1 released from infected T lymphocytes may be biologically important, especially in enhancing T cell activation, during uptake by DCs in vitro and in vivo, particularly as MVs have been detected in the circulation of HIV-1 infected subjects.
Author Summary
Dendritic cells (DCs) are vital for immune recognition of pathogens as they capture, internalise, degrade and present foreign peptides to T lymphocytes. It is thought that HIV-1 hijacks the DCs functions, such as migration and maturation, to increase contact with the major target cell CD4+ T lymphocytes leading to dissemination throughout the body. Currently there is still some controversy over the ability of HIV-1 to infect and mature DCs, which may be due to differences in the inoculum used. Here we examined the effect of contaminating microvesicles (MVs) identified in HIV-1 preparations on HIV-1 modulation of DC function. We show that when MVs are present with HIV-1, the inoculum induces greater DC maturation and adhesion probably via cellular HSP90α and β and viral nef within the MVs. The functional consequences are reduced de novo replication of HIV-1 but increased clustering with T lymphocytes, resulting in increased T lymphocyte alloproliferation and HIV-1 transfer. As MVs are produced in HIV-1 susceptible cells and would be present in vivo due to HIV-1 induced cell death and hence are physiologically relevant, these results also indicate that MVs present in HIV-1 inocula should be considered when assessing HIV∶DC interactions.
doi:10.1371/journal.ppat.1003700
PMCID: PMC3798598  PMID: 24204260
14.  Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics 
Science translational medicine  2012;4(142):142ra94.
The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers where the lack of accurate, reproducible and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature.
Here, we describe a high throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples, plasma and urine. 182 proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/mL. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow the reproducible quantification of 34 biomarker candidates across 84 patient plasma samples. Through public access to the entire assay library, which will also be expandable in the future, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated reference map of SRM assays for cancer-associated proteins is a valuable resource for accelerating and planning biomarker verification studies.
doi:10.1126/scitranslmed.3003989
PMCID: PMC3766734  PMID: 22786679
15.  SRM Targeted Proteomics in Search for Biomarkers of HCV-Induced Progression of Fibrosis to Cirrhosis in HALT-C Patients 
Proteomics  2012;12(8):1244-1252.
The current gold standard for diagnosis of hepatic fibrosis and cirrhosis is the traditional invasive liver biopsy. It is desirable to assess hepatic fibrosis with noninvasive means. Targeted proteomic techniques allow an unbiased assessment of proteins and might be useful to identify proteins related to hepatic fibrosis. We utilized Selected Reaction Monitoring (SRM) targeted proteomics combined with an organ-specific blood protein strategy to identify and quantify 38 liver-specific proteins. A combination of protein C and retinol binding protein 4 in serum gave promising preliminary results as candidate biomarkers to distinguish patients at different stages of hepatic fibrosis due to chronic infection with hepatitis C virus (HCV). Also, alpha-1-B glycoprotein, complement factor H and insulin-like growth factor binding protein acid labile subunit performed well in distinguishing patients from healthy controls.
doi:10.1002/pmic.201100601
PMCID: PMC3766736  PMID: 22577025
hepatitis C; fibrosis; liver-specific blood biomarkers; quantitation; selected reaction monitoring
16.  The 2012/2013 PRG Study: Assessing Longitudinal Variability in Routine Peptide LC-MS/MS Analysis 
The PRG study for 2012-2013 was intended to catalog critical parameters of variability influencing LC-MS/MS data quality within laboratories over a nine month period between March and November, 2012. This study was intended to determine intra-laboratory reproducibility and inform participants of key areas of variability in routine peptide mass spectrometry analyses. Aliquots of a dried, digested protein mixture was sent to all participants with the expectation that once per month a new vial will be reconstituted and analyzed using routine LC-MS and data-dependent MS/MS acquisition settings. Of key importance in the design of this study is the lack of a standard operating protocol. The goal was to measure the degree of reproducibility within a lab as it applies to their established HPLC and MS settings and QC measures. A survey was conducted with each sample submission to catalog individual laboratory practices, instrument configurations, acquisition settings, and routine and non-routine maintenance procedures. Over 80 participants submitted at least one data set, and 36 participants completed the study with 8 or more submissions over the 9 month period. Survey data revealed the vast majority of laboratories (>90%) perform routine QC to determine system suitability, but there was considerable variability in the type and frequency of QC analysis. Collected raw data was searched using identical parameters by the PRG and analyzed for more than 40 MS and MS/MS metrics using the software QuaMeter. The software tool generates metrics that assess multiple properties of LC-MS/MS, from extracted ion chromatogram peak width to total ion current distribution and MS sampling rates. Both identification-dependent and identification-independent metrics can be generated. The variability within these metrics across time was analyzed for each participant and correlative relationships with survey results will be presented.
PMCID: PMC3635275
17.  [No title available] 
The PRG study for 2012–2013 was intended to catalog critical parameters of variability influencing LC-MS/MS data quality within laboratories over a nine month period between March and November, 2012. This study was intended to determine intra-laboratory reproducibility and inform participants of key areas of variability in routine peptide mass spectrometry analyses. Aliquots of a dried, digested protein mixture were sent to all participants with the expectation that once per month a new vial will be reconstituted and analyzed using routine LC-MS and data-dependent MS/MS acquisition settings. Of key importance in the design of this study is the lack of a standard operating protocol. The goal was to measure the degree of reproducibility within a lab as it applies to their established HPLC and MS settings and QC measures. A survey was conducted with each sample submission to catalog individual laboratory practices, instrument configurations, acquisition settings, and routine and non-routine maintenance procedures. Over 80 participants submitted at least one data set, and 36 participants completed the study with 8 or more submissions over the 9 month period. Survey data revealed the vast majority of laboratories (90%) perform routine QC to determine system suitability, but there was considerable variability in the type and frequency of QC analysis. Collected raw data was searched using identical parameters by the PRG and analyzed for more than 40 MS and MS/MS metrics using the software QuaMeter. The software tool generates metrics that assess multiple properties of LC-MS/MS, from extracted ion chromatogram peak width to total ion current distribution and MS sampling rates. Both identification-dependent and identification-independent metrics can be generated. The variability within these metrics across time was analyzed for each participant and correlative relationships with survey results will be presented.
PMCID: PMC3635300
18.  A Cross-platform Toolkit for Mass Spectrometry and Proteomics 
Nature biotechnology  2012;30(10):918-920.
Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.
doi:10.1038/nbt.2377
PMCID: PMC3471674  PMID: 23051804
19.  Quantotypic properties of QconCAT peptides targeting bovine host response to Streptococcus uberis 
Journal of Proteome Research  2012;11(3):1832-1843.
Mammalian host response to pathogens is associated with fluctuations in high abundant proteins in body fluids as well as in regulation of proteins expressed in relatively low copy numbers like cytokines secreted from immune cells and endothelium. Hence, efficient monitoring of proteins associated with host response to pathogens remains a challenging task. In this paper we present a targeted proteome analysis of a panel of 20 proteins that are widely believed to be key players and indicators of bovine host response to mastitis pathogens. Stable isotope labeled variants of two concordant proteotypic peptides from each of these 20 proteins were obtained through the QconCAT method. We present the quantotypic properties of these 40 proteotypic peptides, and discuss their application to research in host pathogen interactions. Our results clearly demonstrate a robust monitoring of 17 targeted host-response proteins. Twelve of these were readily quantified in a simple extraction of mammary gland tissues, while the expression levels of the remaining proteins were too low for direct and stable quantification; hence their accurate quantification requires further fractionation of mammary gland tissues.
doi:10.1021/pr201064g
PMCID: PMC3342530  PMID: 22256911
SRM; QconCAT assay; quantification; proteomics; quantotypic peptides; mastitis
20.  Recommendations for Mass Spectrometry Data Quality Metrics for Open Access Data (Corollary to the Amsterdam Principles) 
Journal of Proteome Research  2011;11(2):1412-1419.
Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the “International Workshop on Proteomic Data Quality Metrics” in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (1) an evolving list of comprehensive quality metrics and (2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data.
By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.
doi:10.1021/pr201071t
PMCID: PMC3272102  PMID: 22053864
selected reaction monitoring; bioinformatics; data quality; metrics; open access; Amsterdam Principles; standards
21.  Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework 
BMC Bioinformatics  2012;13:324.
Background
For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed.
Results
We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed.
Conclusion
The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.
doi:10.1186/1471-2105-13-324
PMCID: PMC3538679  PMID: 23216909
22.  ATF3 protects against atherosclerosis by suppressing 25-hydroxycholesterol–induced lipid body formation 
The transcription factor ATF3 inhibits lipid body formation in macrophages during atherosclerosis in part by dampening the expression of cholesterol 25-hydroxylase.
Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipid-loaded macrophages in the arterial wall. We demonstrate that macrophage lipid body formation can be induced by modified lipoproteins or by inflammatory Toll-like receptor agonists. We used an unbiased approach to study the overlap in these pathways to identify regulators that control foam cell formation and atherogenesis. An analysis method integrating epigenomic and transcriptomic datasets with a transcription factor (TF) binding site prediction algorithm suggested that the TF ATF3 may regulate macrophage foam cell formation. Indeed, we found that deletion of this TF results in increased lipid body accumulation, and that ATF3 directly regulates transcription of the gene encoding cholesterol 25-hydroxylase. We further showed that production of 25-hydroxycholesterol (25-HC) promotes macrophage foam cell formation. Finally, deletion of ATF3 in Apoe−/− mice led to in vivo increases in foam cell formation, aortic 25-HC levels, and disease progression. These results define a previously unknown role for ATF3 in controlling macrophage lipid metabolism and demonstrate that ATF3 is a key intersection point for lipid metabolic and inflammatory pathways in these cells.
doi:10.1084/jem.20111202
PMCID: PMC3328364  PMID: 22473958
23.  The Protein Information and Property Explorer 2: Gaggle-like exploration of biological proteomic data within one webpage 
Proteomics  2010;11(1):154-158.
The Protein Information and Property Explorer 2 (PIPE2) is an enhanced software program and updated web application that aims at providing the proteomic researcher a simple, intuitive user interface through which to begin inquiry into the biological significance of a list of proteins typically produced by MS/MS proteomic processing software. PIPE2 includes an improved interface, new data visualization options, and new data analysis methods for combining disparate, but related, data sets. In particular, PIPE2 has been enhanced to handle multi-dimensional data like protein abundance, gene expression, and/or interaction data. The current architecture of PIPE2, modeled after that of the Gaggle (a programming infrastructure for interoperability between separately developed software tools), contains independent functional units that can be instantiated and pieced together at the user’s discretion to form a pipelined analysis workflow. Among these functional units is the Network Viewer component, which adds rich network analysis capabilities to the suite of existing proteomic web resources. Additionally, PIPE2 implements a framework within which new analysis procedures can be easily deployed and distributed over the World Wide Web. PIPE2 is available as a web service at http://pipe2.systemsbiology.net/.
doi:10.1002/pmic.201000459
PMCID: PMC3072271  PMID: 21182202
Interaction networks; Biological inference; Gene ontology; Software analysis
24.  The 2012 PRG study: Assessing Longitudinal Variability in Routine Peptide LC-MS/MS Analysis 
The PRG study for 2012 is intended to catalog critical parameters of variability influencing LC-MS/MS data quality within labs over a nine month period between March and November, 2012. This study is intended to inform participant labs of key areas of variability in their routine qualitative and quantitative analyses. A dried digested protein mix is sent to labs in aliquots with the expectation that once per month a new vial will be reconstituted and analyzed using routine LC-MS and data-dependent MS/MS acquisition settings. Participants will return the raw data to a centralized server for analysis. The analysis consists of 42 MS and MS/MS metrics that have been determined through the efforts of the CPTC consortium and implemented in open source software from NIST (“MSQC”) and Vanderbilt University (“QuaMeter”). Of key importance in the design of this study is the lack of a standard operating protocol. The concept is to determine variability within a lab when that lab uses their own routine settings and QC measures. A survey is conducted with each sample submission to catalog changes in operators, acquisition settings, as well as routine and non-routine maintenance procedures. As of date, there were 95 labs in 23 countries requesting sample. Within these labs are 25 different models of mass spectrometers from 6 commercial vendors.
PMCID: PMC3630542
25.  The 2012 PRG Study: Assessing Longitudinal Variability in Routine Peptide LC-MS/MS Analysis 
The PRG study for 2012 is intended to catalog critical parameters of variability influencing LC-MS/MS data quality within labs over a nine month period between March and November, 2012. This study is intended to inform participant labs of key areas of variability in their routine qualitative and quantitative analyses. A dried digested protein mix is sent to labs in aliquots with the expectation that once per month a new vial will be reconstituted and analyzed using routine LC-MS and data-dependent MS/MS acquisition settings. Participants will return the raw data to a centralized server for analysis. The analysis consists of 42 MS and MS/MS metrics that have been determined through the efforts of the CPTC consortium and implemented in open source software from NIST (“MSQC”) and Vanderbilt University (“QuaMeter”). Of key importance in the design of this study is the lack of a standard operating protocol. The concept is to determine variability within a lab when that lab uses their own routine settings and QC measures. A survey is conducted with each sample submission to catalog changes in operators, acquisition settings, as well as routine and non-routine maintenance procedures. As of date, there were 95 labs in 23 countries requesting sample. Within these labs are 25 different models of mass spectrometers from 6 commercial vendors.
PMCID: PMC3630553

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