Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.
ABSTRACT: 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.
Project description:We report a high quality and system-wide proteome catalogue covering 71% (3,542 proteins) of the predicted genes of fission yeast, Schizosaccharomyces pombe, presenting the largest protein dataset to date for this important model organism. We obtained this high proteome and peptide (11.4 peptides/protein) coverage by a combination of extensive sample fractionation, high resolution Orbitrap mass spectrometry, and combined database searching using the iProphet software as part of the Trans-Proteomics Pipeline. All raw and processed data are made accessible in the S. pombe PeptideAtlas. The identified proteins showed no biases in functional properties and allowed global estimation of protein abundances. The high coverage of the PeptideAtlas allowed correlation with transcriptomic data in a system-wide manner indicating that post-transcriptional processes control the levels of at least half of all identified proteins. Interestingly, the correlation was not equally tight for all functional categories ranging from r(s) >0.80 for proteins involved in translation to r(s) <0.45 for signal transduction proteins. Moreover, many proteins involved in DNA damage repair could not be detected in the PeptideAtlas despite their high mRNA levels, strengthening the translation-on-demand hypothesis for members of this protein class. In summary, the extensive and publicly available S. pombe PeptideAtlas together with the generated proteotypic peptide spectral library will be a useful resource for future targeted, in-depth, and quantitative proteomic studies on this microorganism.
Project description: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.
Project description:Tumor-derived mutant KRAS (v-Ki-ras-2 Kirsten rat sarcoma viral oncogene) oncoprotein is a critical driver of cancer phenotypes and a potential biomarker for many epithelial cancers. Targeted mass spectrometry analysis by multiple reaction monitoring (MRM) enables selective detection and quantitation of wild-type and mutant KRAS proteins in complex biological samples. A recently described immunoprecipitation approach (Proc. Nat. Acad. Sci.2011, 108, 2444-2449) can be used to enrich KRAS for MRM analysis, but requires large protein inputs (2-4 mg). Here, we describe sodium dodecyl sulfate-polyacrylamide gel electrophoresis-based enrichment of KRAS in a low molecular weight (20-25 kDa) protein fraction prior to MRM analysis (GeLC-MRM). This approach reduces background proteome complexity, thus, allowing mutant KRAS to be reliably quantified in low protein inputs (5-50 ?g). GeLC-MRM detected KRAS mutant variants (G12D, G13D, G12V, G12S) in a panel of cancer cell lines. GeLC-MRM analysis of wild-type and mutant was linear with respect to protein input and showed low variability across process replicates (CV = 14%). Concomitant analysis of a peptide from the highly similar HRAS and NRAS proteins enabled correction of KRAS-targeted measurements for contributions from these other proteins. KRAS peptides were also quantified in fluid from benign pancreatic cysts and pancreatic cancers at concentrations from 0.08 to 1.1 fmol/?g protein. GeLC-MRM provides a robust, sensitive approach to quantitation of mutant proteins in complex biological samples.
Project description:Prostate specific antigen (PSA) is a well-established tumor marker that is frequently employed as model biomarker in the development and evaluation of emerging quantitative proteomics techniques, partially as a result of wide access to commercialized immunoassays serving as "gold standards." We designed a multiple reaction monitoring (MRM) assay to detect PSA proteoforms in clinical samples (n = 72), utilizing the specificity and sensitivity of the method. We report, for the first time, a PSA proteoform coded by SNP-L132I (rs2003783) that was observed in nine samples in both heterozygous (n = 7) and homozygous (n = 2) expression profiles. Other isoforms of PSA, derived from protein databases, were not identified by four unique proteotypic tryptic peptides. We have also utilized our MRM assay for precise quantitative analysis of PSA concentrations in both seminal and blood plasma samples. The analytical performance was evaluated, and close agreement was noted between quantitations based on three selected peptides (LSEPAELTDAVK, IVGGWECEK, and SVILLGR) and a routinely used commercialized immunoassay. Additionally, we disclose that the peptide IVGGWECEK is shared with kallikrein-related peptidase 2 and therefore is not unique for PSA. Thus, we propose the use of another tryptic sequence (SVILLGR) for accurate MRM quantification of PSA in clinical samples.
Project description:Dried blood spot (DBS) sampling, coupled with multiple reaction monitoring mass spectrometry (MRM-MS), is a well-established approach for quantifying a wide range of small molecule biomarkers and drugs. This sampling procedure is simpler and less-invasive than those required for traditional plasma or serum samples enabling collection by minimally trained personnel. Many analytes are stable in the DBS format without refrigeration, which reduces the cost and logistical challenges of sample collection in remote locations. These advantages make DBS sample collection desirable for advancing personalized medicine through population-wide biomarker screening. Here we expand this technology by demonstrating the first multiplexed method for the quantitation of endogenous proteins in DBS samples. A panel of 60 abundant proteins in human blood was targeted by monitoring proteotypic tryptic peptides and their stable isotope-labeled analogs by MRM. Linear calibration curves were obtained for 40 of the 65 peptide targets demonstrating multiple proteins can be quantitatively extracted from DBS collection cards. The method was also highly reproducible with a coefficient of variation of <15% for all 40 peptides. Overall, this assay quantified 37 proteins spanning a range of more than four orders of magnitude in concentration within a single 25 min LC/MRM-MS analysis. The protein abundances of the 33 proteins quantified in matching DBS and whole blood samples showed an excellent correlation, with a slope of 0.96 and an R(2) value of 0.97. Furthermore, the measured concentrations for 80% of the proteins were stable for at least 10 days when stored at -20 °C, 4 °C and 37 °C. This work represents an important first step in evaluating the integration of DBS sampling with highly-multiplexed MRM for quantitation of endogenous proteins.
Project description:The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list-the draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications (PTMs), and splice isoforms of those proteins; and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data sets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.1 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [ www.thehpp.org/guidelines ]. The Human Proteome presented as neXtProt version 2016-02 has 16,518 confident protein identifications (Protein Existence [PE] Level 1), up from 13,664 at 2012-12, 15,646 at 2013-09, and 16,491 at 2014-10. There are 485 proteins that would have been PE1 under the Guidelines v1.0 from 2012 but now have insufficient evidence due to the agreed-upon more stringent Guidelines v2.0 to reduce false positives. neXtProt and PeptideAtlas now both require two non-nested, uniquely mapping (proteotypic) peptides of at least 9 aa in length. There are 2,949 missing proteins (PE2+3+4) as the baseline for submissions for this fourth annual C-HPP special issue of Journal of Proteome Research. PeptideAtlas has 14,629 canonical (plus 1187 uncertain and 1755 redundant) entries. GPMDB has 16,190 EC4 entries, and the Human Protein Atlas has 10,475 entries with supportive evidence. neXtProt, PeptideAtlas, and GPMDB are rich resources of information about post-translational modifications (PTMs), single amino acid variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven (B/D)-HPP has created comprehensive SRM resources, generated popular protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative.
Project description:The important biological roles of glycans and their implications in disease development and progression have created a demand for the development of sensitive quantitative glycomics methods. Quantitation of glycans existing at low abundance is still analytically challenging. In this study, an N-linked glycans quantitation method using multiple-reaction monitoring (MRM) on a triple quadrupole instrument was developed. Optimum normalized collision energy (CE) for both sialylated and fucosylated N-glycan was determined to be 30%, whereas it was found to be 35% for either fucosylated or sialylated N-glycans. The optimum CE for mannose and complex type N-glycan was determined to be 35%. Additionally, the use of three transitions was shown to facilitate reliable quantitation. A total of 88 N-glycan compositions in human blood serum were quantified using this MRM approach. Reliable detection and quantitation of these glycans was achieved when the equivalence of 0.005 ?L of blood serum was analyzed. Accordingly, N-glycans down to the 100th of a ?L level can be reliably quantified in pooled human blood serum, spanning a dynamic concentration range of three orders of magnitude. MRM was also effectively utilized to quantitatively compare the expression of N-glycans derived from brain-targeting breast carcinoma cells (MDA-MB-231BR) and metastatic breast cancer cells (MDA-MB-231). Thus, the described MRM method of permethylated N-glycan enables a rapid and reliable identification and quantitation of glycans derived from glycoproteins purified or present in complex biological samples.
Project description:Staphylococcus aureus is one of the important aetiological agents of food intoxications in Europe and can cause gastro-enteritis through the production of various staphylococcal enterotoxins (SEs) in foods. Due to their stability and ease of production and dissemination, some SEs have also been studied as potential agents for bioterrorism. Therefore, specific and accurate analytical tools are required to detect and quantify SEs. Online solid-phase extraction liquid chromatography electrospray ionization tandem mass spectrometry (online SPE-LC-ESI-MS/MS) based on multiple reaction monitoring (MRM) was used to detect and quantify two types of SE (A and B) spiked in milk and buffer solution. SE extraction and concentration was performed according to the European Screening Method developed by the European Reference Laboratory for Coagulase Positive Staphylococci. Trypsin digests were screened for the presence of SEs using selected proteotypic heavy-labeled peptides as internal standards. SEA and SEB were successfully detected in milk samples using LC-MS/MS in MRM mode. The selected SE peptides were proteotypic for each toxin, allowing the discrimination of SEA and SEB in a single run. The detection limit of SEA and SEB was approximately 8 and 4 ng/g, respectively.
Project description:Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments.In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal http://www.drosophila-peptideatlas.org allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed.PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.
Project description:We report an innovative multiplexed liquidchromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS)-based assay for rapidly measuring a large number of disease specific protein biomarkers in human serum. Furthermore, this approach uses stable isotope dilution methodology to reliably quantify candidate protein biomarkers. Human serum was diluted using a stable isotope labeled proteome (SILAP) standard prepared from the secretome of pancreatic cell lines, subjected to immunoaffinity removal of the most highly abundant proteins, trypsin digested, and analyzed by LC-MRM/MS. The method was found to be precise, linear, and specific for the relative quantification of 72 proteins when analyte response was normalized to the relevant internal standard (IS) from the SILAP. The method made it possible to determine statistically different concentrations for three proteins (cystatin M, IGF binding protein 7, and villin 2) in control and pancreatic cancer patient samples. This method proves the feasibility of using a SILAP standard in combination with stable isotope dilution LC-MRM/MS analysis of tryptic peptides to compare changes in the concentration of candidate protein biomarkers in human serum.