SRMBuilder: a user-friendly tool for selected reaction monitoring data analysis

With high sensitivity and reproducibility, selected reaction monitoring (SRM) has become increasingly popular in proteome research for targeted quantification of low abundance proteins and post translational modification. SRM is also well accepted in other mass-spectrometry based research areas such as lipidomics and metabolomics, which necessitates the development of easy-to-use software for both post-acquisition SRM data analysis and quantification result validation. Here, we introduce a software tool SRMBuilder, which can automatically parse SRM data in multiple file formats, assign transitions to compounds, match light/heavy transition/compound pairs and provide a user-friendly graphic interface to manually validate the quantification result at transition/compound/sample level. SRMBuilder will greatly facilitate processing of the post-acquisition data files and validation of quantification result for SRM. The software can be downloaded for free from http://www.proteomics.ac.cn/software/proteomicstools/index.htm as part of the software suite ProteomicsTools.     

^18O内标质谱法比较定量蛋白质组学计量的数学算法

18O内标蛋白质质谱定量分析是一种极具前景的比较蛋白组学研究技术,虽然该方法与迄今所有内标法相比有一系列优点,但是由于其质谱是由16O未标记品种,单及双18O标记品种分子同位素峰簇相互迭加所构成的复杂谱,定量分析的关键是发展有效的质谱解析算法。有鉴于此,综述和讨论了18O内标质谱差异比较蛋白质分析过程中,分子同位素簇分布的简化计算方法,以及质谱混和谱解析的数学方法。     

Quantitative proteomics analysis of adsorbed plasma proteins classifies nanoparticles with different surface properties and size

Nanoparticle biological activity, biocompatibility and fate can be directly affected by layers of readily adsorbed host proteins in biofluids. Here, we report a study on the interactions between human blood plasma proteins and nanoparticles with a controlled systematic variation of properties using (18)O-labeling and LC-MS-based quantitative proteomics. We developed a novel protocol to both simplify isolation of nanoparticle bound proteins and improve reproducibility. LC-MS analysis identified and quantified 88 human plasma proteins associated with polystyrene nanoparticles consisting of three different surface chemistries and two sizes, as well as, for four different exposure times (for a total of 24 different samples). Quantitative comparison of relative protein abundances was achieved by spiking an (18)O-labeled "universal" reference into each individually processed unlabeled sample as an internal standard, enabling simultaneous application of both label-free and isotopic labeling quantification across the entire sample set. Clustering analysis of the quantitative proteomics data resulted in distinctive patterns that classified the nanoparticles based on their surface properties and size. In addition, temporal data indicated that the formation of the stable protein corona was at equilibrium within 5 min. The comprehensive quantitative proteomics results obtained in this study provide rich data for computational modeling and have potential implications towards predicting nanoparticle biocompatibility.     

Candidate verification of iron-regulated Neisseria meningitidis proteins using isotopic versions of tandem mass tags (TMT) and single reaction monitoring

Tandem Mass Tags (TMT) are suited to both global and targeted quantitation approaches of proteins and peptides. Different versions of these tags allow for the generation of both isobaric and isotopic sets of reagents sharing the same common structure. This feature allows for a straightforward transfer of data obtained during discovery studies into targeted investigations. In prior discovery studies, an isobaric set of these reagents was used to identify Neisseria meningitidis proteins expressed under iron-limitation. Here, we apply isotopic versions of those reagents in combination with single reaction monitoring to verify selected candidates found to be differentially regulated in these discovery studies, representing both well-known and novel iron-regulated proteins, such as the MtrCDE drug efflux pump. In this targeted approach (TMT–SRM), the selectivity of SRM is maintained while allowing the incorporation of an internal reference standard into the experiment. By monitoring 184 transitions, TMT–SRM resulted in the quantitation of 33 peptides representing 12 proteins. The acquired data corroborated the results obtained during the discovery phase. Furthermore, these data obtained by MS-based quantitation of peptides were independently confirmed by western blotting results, an orthogonal approach based on quantitation at the protein level.     

Platform for establishing interlaboratory reproducibility of selected reaction monitoring-based mass spectrometry peptide assays

Mass spectrometry (MS) is an attractive alternative to quantification of proteins by immunoassays, particularly for protein biomarkers of clinical relevance. Reliable quantification requires that the MS-based assays are robust, selective, and reproducible. Thus, the development of standardized protocols is essential to introduce MS into clinical research laboratories. The aim of this study was to establish a complete workflow for assessing the transferability and reproducibility of selected reaction monitoring (SRM) assays between clinical research laboratories. Four independent laboratories in North America, using identical triple-quadrupole mass spectrometers (Quantum Ultra, Thermo), were provided with standard protocols and instrumentation settings to analyze unknown samples and internal standards in a digested plasma matrix to quantify 51 peptides from 39 human proteins using a multiplexed SRM assay. The interlaboratory coefficient of variation (CV) was less than 10% for 25 of 39 peptides quantified (12 peptides were not quantified based upon hydrophobicity) and exhibited CVs less than 20% for the remaining peptides. In this report, we demonstrate that previously developed research platforms for SRM assays can be improved and optimized for deployment in clinical research environments.     

Amine-reactive isobaric tagging reagents: requirements for absolute quantification of proteins and peptides

Amine-reactive isobaric tagging reagents such as iTRAQ (isobaric tags for relative and absolute quantitation) have recently become increasing popular for relative protein quantification, cell expression profiling, and biomarker discovery. This is due mainly to the possibility of simultaneously identifying and quantifying multiple samples. The principles of iTRAQ may also be applied to absolute protein quantification with the use of synthetic peptides as standards. The prerequisites that must be fulfilled to perform absolute quantification of proteins by iTRAQ have been investigated and are described here. Three samples of somatropin were quantified using iTRAQ and synthetic peptides as standards, corresponding to a portion of the protein sequence. The results were compared with those obtained by quantification of the same protein solutions using double exact matching isotope dilution mass spectrometry (IDMS). To obtain reliable results, the appropriate standard peptides needed to be selected carefully and enzymatic digestion needed to be optimized to ensure complete release of the peptides from the protein. The kinetics and efficiency of the iTRAQ derivatization reaction of the standard peptides and digested proteins with isobaric tagging reagents were studied using a mixture of seven synthetic peptides and their corresponding labeled peptides. The implications of incomplete derivatization are also presented.     

Relative quantification of proteins across the species boundary through the use of shared peptides

We show that shared peptides of proteins that are encoded in different species are suitable for cross-species relative protein quantification. A 14N-containing proteome from the thermoacidophilic archaeon Sulfolobus tokodaii was mixed with a 15N-labeled proteome from Sulfolobus solfataricus. Using three shared peptides per protein, the relative abundance of six orthologous proteins was calculated. Observed standard deviations were approximately 10%, indicating that the trypsin accessibility to cleavage sites was not altered in the orthologs. The abundance ratios of the and subunits of the Thermosome were 0.64 and 1.24 in Sulfolobus tokodaii compared to Sulfolobus solfataricus, suggesting a different stoichiometry of the complex in both species. In addition, an in silico study was performed on the occurrence of shared peptides. Inter- and intra-species peptide redundancy was investigated in the model organisms Homo sapiens, Mus musculus, Escherichia coli K12, Escherichia coli O157:H7, S. solfataricus, and S. tokodaii. M. musculus and H. sapiens share 30-50% of all peptides (6-15 residues). Moreover, approximately one-third of all proteins shared > or = 40% of their peptides with at least one other protein in the related species, thus offering strong potential for cross-species relative protein quantification. Conversely, approximately 40% of all peptides (6-15 residues) encoded in H. sapiens are encoded multiple times and therefore complicate identification and quantification.     

Systematic quantification of peptides/proteins in urine using selected reaction monitoring

The evaluation of biomarkers in bodily fluids necessitates the development of robust methods to quantify proteins in a complex background, using large sets of samples. The ability to multiplex numerous analytes in a single assay expedites the process. Liquid chromatography-mass spectrometry (LC-MS) analyses performed in selected reaction monitoring (SRM) in conjunction with stable isotope dilution MS present an effective way to detect and quantify biomarker candidates in bodily fluids. The strategy presented involves an initial qualification of predefined sets of proteins in urine. The technique was applied to detect and quantify peptides in urine samples as surrogates for a few endogenous proteins. Multiplexed assays were developed to analyze proteins associated with bladder cancer; a few exogenous proteins were added as internal standards. The sample preparation and the analytical protocols were optimized to ensure reproducibility, analytical precision, and quantification limits in the low nanogram per milliliter range. Analyses were performed using known amounts of isotopically labeled peptides. Systematic replication of the measurements indicated intra-assay and inter-assay variability, with CVs in the range of 10%. The differences measured for two targeted proteins were correlated with their level of expression in the corresponding tumors using immunohistochemistry.     

Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition

Relative quantification methods have dominated the quantitative proteomics field. There is a need, however, to conduct absolute quantification studies to accurately model and understand the complex molecular biology that results in proteome variability among biological samples. A new method of absolute quantification of proteins is described. This method is based on the discovery of an unexpected relationship between MS signal response and protein concentration: the average MS signal response for the three most intense tryptic peptides per mole of protein is constant within a coefficient of variation of less than +/-10%. Given an internal standard, this relationship is used to calculate a universal signal response factor. The universal signal response factor (counts/mol) was shown to be the same for all proteins tested in this study. A controlled set of six exogenous proteins of varying concentrations was studied in the absence and presence of human serum. The absolute quantity of the standard proteins was determined with a relative error of less than +/-15%. The average MS signal responses of the three most intense peptides from each protein were plotted against their calculated protein concentrations, and this plot resulted in a linear relationship with an R(2) value of 0.9939. The analyses were applied to determine the absolute concentration of 11 common serum proteins, and these concentrations were then compared with known values available in the literature. Additionally within an unfractionated Escherichia coli lysate, a subset of identified proteins known to exist as functional complexes was studied. The calculated absolute quantities were used to accurately determine their stoichiometry.     

18O-Labeled lipid hydroperoxides and HPLC coupled to mass spectrometry as valuable tools for studying the generation of singlet oxygen in biological system

Decomposition of lipid hydroperoxides (LOOH) is known to generate toxic products capable to induce tissue injury. We have recently confirmed that decomposition of LOOH into peroxyl radicals is a potential source of singlet oxygen ((1)O(2) in biological system. Using (18)O-labeled linoleic acid hydroperoxide (LA(18)O(18)OH) in the presence of Ce(4+) or Fe(2+), we observed the formation of (18)O-labeled (1)O(2) ((18)[(1)O(2)]) by chemical trapping of (1)O(2) with 9,10-diphenylanthracene (DPA) and detecting the corresponding (18)O-labeled DPA endoperoxide (DPA(18)O(18)O) by HPLC coupled to tandem mass spectrometry (HPLC-MS/MS). (18)O-Labeled alcohol and ketone were also detected providing further evidence for the generation of (1)O(2) by the Russell mechanism. Similarly the reaction of LA(18)O(18)OH with peroxynitrite also generated (18)[(1)O(2)].In conclusion, these results indicates that the use of (18)O-labeled LOOH associated with HPLC-MS/MS can be an useful tool to clarify mechanistic features involved in the reaction of LOOH in biological media.     

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of G_i2 (a heterotrimeric G-protein α-subunit) is described in detail.     

High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites

The detection and quantification of plasma (serum) proteins at or below the ng/ml concentration range are of critical importance for the discovery and evaluation of new protein biomarkers. This has been achieved either by the development of high sensitivity ELISA or other immunoassays for specific proteins or by the extensive fractionation of the plasma proteome followed by the mass spectrometric analysis of the resulting fractions. The first approach is limited by the high cost and time investment for assay development and the requirement of a validated target. The second, although reasonably comprehensive and unbiased, is limited by sample throughput. Here we describe a method for the detection of plasma proteins at concentrations in the ng/ml or sub-ng/ml range and their accurate quantification over 5 orders of magnitude. The method is based on the selective isolation of N-glycosites from the plasma proteome and the detection and quantification of targeted peptides in a quadrupole linear ion trap instrument operated in the multiple reaction monitoring (MRM) mode. The unprecedented sensitivity of the mass spectrometric analysis of minimally fractionated plasma samples is the result of the significantly reduced sample complexity of the isolated N-glycosites compared with whole plasma proteome digests and the selectivity of the MRM process. Precise quantification was achieved via stable isotope dilution by adding (13)C- and/or (15)N-labeled reference analytes. We also demonstrate the possibility of significantly expanding the number of MRM measurements during one single LC-MS run without compromising sensitivity by including elution time constraints for the targeted transitions, thus allowing quantification of large sets of peptides in a single analysis.     

Introducing AAA-MS, a rapid and sensitive method for amino acid analysis using isotope dilution and high-resolution mass spectrometry

Accurate quantification of pure peptides and proteins is essential for biotechnology, clinical chemistry, proteomics, and systems biology. The reference method to quantify peptides and proteins is amino acid analysis (AAA). This consists of an acidic hydrolysis followed by chromatographic separation and spectrophotometric detection of amino acids. Although widely used, this method displays some limitations, in particular the need for large amounts of starting material. Driven by the need to quantify isotope-dilution standards used for absolute quantitative proteomics, particularly stable isotope-labeled (SIL) peptides and PSAQ proteins, we developed a new AAA assay (AAA-MS). This method requires neither derivatization nor chromatographic separation of amino acids. It is based on rapid microwave-assisted acidic hydrolysis followed by high-resolution mass spectrometry analysis of amino acids. Quantification is performed by comparing MS signals from labeled amino acids (SIL peptide- and PSAQ-derived) with those of unlabeled amino acids originating from co-hydrolyzed NIST standard reference materials. For both SIL peptides and PSAQ standards, AAA-MS quantification results were consistent with classical AAA measurements. Compared to AAA assay, AAA-MS was much faster and was 100-fold more sensitive for peptide and protein quantification. Finally, thanks to the development of a labeled protein standard, we also extended AAA-MS analysis to the quantification of unlabeled proteins.     

Global absolute quantification of a proteome: Challenges in the deployment of a QconCAT strategy

In this paper, we discuss the challenge of large-scale quantification of a proteome, referring to our programme that aims to define the absolute quantity, in copies per cell, of at least 4000 proteins in the yeast Saccharomyces cerevisiae. We have based our strategy on the well-established method of stable isotope dilution, generating isotopically labelled peptides using QconCAT technology, in which artificial genes, encoding concatenations of tryptic fragments as surrogate quantification standards, are designed, synthesised de novo and expressed in bacteria using stable isotopically enriched media. A known quantity of QconCAT is then co-digested with analyte proteins and the heavy:light isotopologues are analysed by mass spectrometry to yield absolute quantification. This workflow brings issues of optimal selection of quantotypic peptides, their assembly into QconCATs, expression, purification and deployment.     

Enhancing the stability of O-labeled peptides through removal of immobilized trypsin by ZipTips

Trypsin-catalyzed ¹⁸O labeling is increasingly used in shotgun proteomics for relative peptide/protein quantitation. However, precise quantitative measurements are often complicated by the instability of ¹⁸O-labeled peptides caused mainly by oxygen back-exchange. Although a number of attempts have been made to reduce or prevent oxygen back-exchange, there is still room for improvement. Here we demonstrate that the removal of immobilized trypsin by filtration using ZipTips can efficiently minimize oxygen back-exchange and enhance the stability of ¹⁸O-labeled peptides under various pH conditions. The ¹⁸O-labeled peptides processed by the approach were successfully separated by immobilized pH gradient–isoelectric focusing (IPG–IEF), and no marked decrease in the extent of labeling was observed. The results also demonstrated that there was no correlation between the extent of ¹⁸O labeling and molecular weight or isoelectric point (pI). The approach presented here is especially applicable to microscale samples. Its ability to generate stably ¹⁸O-labeled samples without back-exchange should expand the application scope of the ¹⁸O-labeling technique.     

Quantitative proteomic analysis of mouse embryonic fibroblasts and induced pluripotent stem cells using 16O/18O labeling

Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here, we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. With this platform, a total of 2481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex, were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1), and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.     

Applying selected reaction monitoring to targeted proteomics

Selected reaction monitoring (SRM) is a highly selective and sensitive mass spectrometric methodology for precise and accurate quantification of low-abundant proteins in complex mixtures and for characterization of modified peptides, and constitutes the method of choice in targeted proteomics. Owing to its outstanding features, SRM arises as an alternative to antibody-based assays for discovery and validation of clinically relevant biomarkers, a topic that is tackled in this article. Several of the obstacles encountered in SRM experiments, mainly those derived from shared physicochemical properties of peptides (e.g., mass, charge and chromatographic retention time), can compromise selectivity and quantitation. We illustrate how to circumvent these limitations on the basis of using time-scheduled chromatographic approaches and choosing appropriate spectrometric conditions, including the careful selection of the precursor and diagnostic ions.     

Targeted proteomic analysis of glycolysis in cancer cells

Altered expression of glycolysis proteins is an important yet poorly understood characteristic of cancer. To better understand the glycolytic changes during tumorigenesis, we designed a liquid chromatography multiple reaction monitoring (LC-MRM) assay targeting the "glycolysis proteome" in MCF-7 breast cancer cells, using isotope-coded dimethylation of peptides for relative quantification. In silico, dimethyl labeled tryptic peptides [M + 2H](2+) (of length n) and their y(n-1) fragment ions were determined based on UniprotKB database sequence entries for glycolysis proteins, related branching pathways, and reference proteins. Using predicted transitions ([M + 2H](2+) → y(n-1)), MRM-initiated detection and sequencing (MIDAS) was performed on a dimethyl-labeled, tryptic digest from MCF-7 cells, using two-dimensional liquid chromatography mass spectrometry analysis. Three transitions for each peptide were selected from identified spectra and assessed using 1D-LC-MRM-MS. Collision energy (CE) and dwell times were optimized and matching transitions for "heavy" isotope-coded dimethylated peptides were calculated. Resulting LC-MRM transitions were then used to measure changes in the glycolytic proteome in insulin-like growth factor-1 (IGF-1)-stimulated MCF-7 cells and other breast cell lines. Increases in the expression of glycolysis proteins leading to lactic acid production were observed common to IGF-1-stimulated MCF-7 cells and the invasive MDA-MB-231 cell line. Preliminary analysis of lung tumors with varied states of differentiation demonstrated the clinical applicability of LC-MRM and showed decreased levels of PGK1 in poorly differentiated tumors.     

Protein significance analysis in selected reaction monitoring (SRM) measurements

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that provides sensitive and accurate protein detection and quantification in complex biological mixtures. Statistical and computational tools are essential for the design and analysis of SRM experiments, particularly in studies with large sample throughput. Currently, most such tools focus on the selection of optimized transitions and on processing signals from SRM assays. Little attention is devoted to protein significance analysis, which combines the quantitative measurements for a protein across isotopic labels, peptides, charge states, transitions, samples, and conditions, and detects proteins that change in abundance between conditions while controlling the false discovery rate. We propose a statistical modeling framework for protein significance analysis. It is based on linear mixed-effects models and is applicable to most experimental designs for both isotope label-based and label-free SRM workflows. We illustrate the utility of the framework in two studies: one with a group comparison experimental design and the other with a time course experimental design. We further verify the accuracy of the framework in two controlled data sets, one from the NCI-CPTAC reproducibility investigation and the other from an in-house spike-in study. The proposed framework is sensitive and specific, produces accurate results in broad experimental circumstances, and helps to optimally design future SRM experiments. The statistical framework is implemented in an open-source R-based software package SRMstats, and can be used by researchers with a limited statistics background as a stand-alone tool or in integration with the existing computational pipelines.