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. Molecular & Cellular Proteomics 7:1489 -1500, 2008.A key element of the experimental framework for systems biology is the comprehensive, quantitative measurement of whole biological systems in differentially perturbed states (1). Among the different types of measurements possible, protein quantification is particularly informative because proteins catalyze or control the majority of cellular functions. Currently the most widely applied quantitative proteome analysis technologies consist of the labeling of the samples by stable isotopes, the reproducible separation of complex peptide mixtures, usually by capillary LC, and the identification and quantification of selected peptides by tandem mass spectrometry and sequence database searching (2, 3). Relative quantitative values are generated by these methods if two or more samples are being compared, and absolute quantification can be achieved if suitable, calibrated reference samples are available (4). Using such shotgun methods, in each measurement only a fraction of the analytes present in a complex sample is identified and quantified. Peptide ions are selected by the mass spectrometer automatically based on precursor ion signal intensities. Due to a multitude of factors, including interference between analytes and variations in precursor ion spectra, the selection of peptides is not reproducible in consecutive runs in particular for peptides...

Current affairs in quantitative targeted proteomics: multiple reaction monitoring-mass spectrometry

“…This is an area where MRM-MS is really gaining interest and momentum. Not only can a targeted approach such as MRM-MS lessen the ever challenging dynamic range issues most commonly encountered during global proteomics experiments thereby digging deeper into the low abundance proteome and low stochiometric PTM, this methodology is showing tremendous utility in the verification of both global proteomics identification and quantification data [12,23,[35][36][37][38][39]. Unfortunately, global proteomics data can be inconclusive.…”

“…Like traditional MRM-MS methodology development, the MIDAS workflow is still dependent on two things: (i) that the chosen MRM peptide ionizes efficiently enough to be measured by MS satisfying the first ion, Q1, of the MRM; and (ii) that the peptide fragments well enough and with sufficient intensity to generate the second ion, Q3, of the MRM. If using an in silico methodology to predict ionizable peptides such as; a module in MIDAS, P3 (Proteotypic Peptide Predictor) [22], TIQAM (Targeted Identification for Quantitative Analysis by MRM) [23], as discussed below, or other in silico prediction methods based on amino-acid sequence such as MDIP (Minimum Acceptable Detectability for Identified Peptides) [24], APEX (Absolute Protein Expression) [25] and those predicted are determined empirically to not ionize, another peptide that does ionize from the same protein can be tested and subsequently used instead. TIQAM is another software-derived workflow similar to MIDAS aimed at reducing the time commitment required for the development and validation of MRM assays [23].…”

“…Growing interest in using this technology to quantify proteins has led to a number of new software developments over the last few years. As state above, the MIDAS and TIQAM workflows were developed for targeted detection of proteins [21,44], their respective PTM [8,41] and for the rapid development of MRM assays [1,23,53]. Informatic strategies for the prediction of the most likely peptides (proteotypic peptides) that will be observed for proteins of interest are emerging [14,15,23,54,55].…”

Applications of targeted proteomics in systems biology and translational medicine

“…Following the successful quantification of single proteins or small protein lists, assays for targeted proteomics were established for entire model organisms 16, 46, 47. Applications using medium to large‐sized target lists as is the case for the study of biological networks have pushed technology development.…”

Stable isotopic labeling in proteomics

“…Production problems of QconCAT peptides were recently reported [63] and illustrate the necessity of selecting peptides based on experimental data next to plain predictions. Ideally, proteotypic peptides [64,65] -peptides that are observable by mass spectrometers (thus ionize and fragment well and with m/zvalues well inside the practical m/z-range of the spectrometer used) and can be unambiguously associated to a single protein -should be selected and analyzed by targeted multiple reaction monitoring (MRM) (e.g., [66]). …”