Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

Proteomics is gradually complementing large shotgun qualitative studies with hypothesis-driven quantitative experiments. Targeted analyses performed on triple quadrupole instruments in selected reaction monitoring mode are characterized by a high degree of selectivity and low limit of detection; however, the concurrent analysis of multiple analytes occurs at the expense of sensitivity because of reduced dwell time and/or selectivity due to limitation to a few transitions. A new data acquisition paradigm is presented in which selected reaction monitoring is performed in two ways to simultaneously quantify and confirm the identity of the targeted peptides. A first set of primary transitions is continuously monitored during a predetermined elution time window to precisely quantify each peptide. In addition, a set of six to eight transitions is acquired in a data-dependent event, triggered when all the primary transitions exceed a preset threshold. These additional transitions are used to generate composite tandem mass spectra to formally confirm the identity of the targeted peptides. This technique was applied to analyze the tryptic digest of a yeast lysate to demonstrate the performance of the technique. We showed a limit of detection down to tens of attomoles injected and a throughput exceeding 6000 transitions in one 60-min experiment. The technique was integrated into a linear work flow, including experimental design, data acquisition, and data evaluation, enabling large scale proteomic studies.

Aberrant expression, activation, and down-regulation of the epidermal growth factor receptor (EGFR) have causal roles in many human cancers, and post-translational modifications including phosphorylation and ubiquitination and protein-protein interactions directly modulate EGFR function. Quantitative mass spectrometric analyses including selected reaction monitoring (also known as multiple reaction monitoring) were applied to the EGFR and associated proteins. In response to epidermal growth factor (EGF) stimulation of cells, phosphorylations at EGFR Ser991 and Tyr998 accumulated more slowly than at receptor sites involved in RAS-ERK signaling. Phosphorylation-deficient mutant receptors S991A and Y998F activated ERK in response to EGF but were impaired for receptor endocytosis. Consistent with these results, the mutant receptors retained a network of interactions with known signaling proteins including EGF-stimulated binding to the adaptor GRB2. Compared with wild type EGFR the Y998F variant had diminished EGF-stimulated interaction with the ubiquitin E3 ligase CBL, and the S991A variant had decreased associated ubiquitin. The endocytosis-defective mutant receptors were found to have elevated phosphorylation at positions Ser1039 and Thr1041. These residues reside in a serine/threonine-rich region of the receptor previously implicated in p38 mitogen-activated protein kinase-dependent stress/cytokine-induced EGFR internalization and recycling (Zwang, Y., and Yarden, Y. (2006) p38 MAP kinase mediates stress-induced internalization of EGFR: implications for cancer chemotherapy. EMBO J. 25, 4195–4206). EGF-induced phosphorylations at Ser1039 and Thr1041 were blocked by treatment of cells with SB-202190, a selective inhibitor of p38. These results suggest that coordinated phosphorylation of EGFR involving sites Tyr998, Ser991, Ser1039, and Thr1041 governs the trafficking of EGF receptors. This reinforces the notion that EGFR function is manifest through spatially and temporally controlled protein-protein interactions and phosphorylations.

A new strategy using a hybrid linear ion trap/Orbitrap mass spectrometer and multiple post-acquisition data mining techniques was evaluated and applied to the detection and characterization of in vitro metabolites of indinavir. Accurate-mass, full-scan MS and MS/MS data sets were acquired with a generic data-dependent method and processed with extracted-ion chromatography (EIC), mass-defect filter (MDF), product-ion filter (PIF), and neutral-loss filter (NLF) techniques. The high-resolution EIC process was shown to be highly effective in the detection of common metabolites with predicted molecular weights. The MDF process, which searched for metabolites based on the similarity of mass defects of metabolites to those of indinavir and its core substructures, was able to find uncommon metabolites not detected by the EIC processing. The high-resolution PIF and NLF processes selectively detected metabolites that underwent fragmentation pathways similar to those of indinavir or its known metabolites. As a result, a total of 15 metabolites including two new indinavir metabolites were detected and characterized in a rat liver S9 incubation sample. Overall, these data mining techniques, which employed distinct metabolite search mechanisms, were complementary and effective in detecting both common and uncommon metabolites. In summary, the results demonstrated that this analytical strategy enables the high-throughput acquisition of accurate-mass LC/MS data sets, comprehensive search of a variety of metabolites through the post-acquisition processes, and effective structural characterization based on elemental compositions of metabolite molecules and their product ions.

We report herein, facile metabolite identification workflow on the anti-depressant nefazodone, which is derived from accurate mass measurements based on a single run/experimental analysis. A hybrid LTQ/orbitrap mass spectrometer was used to obtain accurate mass full scan MS and MS/MS in a data-dependent fashion to eliminate the reliance on a parent mass list. Initial screening utilized a high mass tolerance ( approximately 10 ppm) to filter the full scan MS data for previously reported nefazodone metabolites. The tight mass tolerance reduces or eliminates background chemical noise, dramatically increasing sensitivity for confirming or eliminating the presence of metabolites as well as isobaric forms. The full scan accurate mass analysis of suspected metabolites can be confirmed or refuted using three primary tools: (1) predictive chemical formula and corresponding mass error analysis, (2) rings-plus-double bonds, and (3) accurate mass product ion spectra of parent and suspected metabolites. Accurate mass characterization of the parent ion structure provided the basis for assessing structural assignment for metabolites. Metabolites were also characterized using parent product ion m/z values to filter all tandem mass spectra for identification of precursor ions yielding similar product ions. Identified metabolite parent masses were subjected to chemical formula calculator based on accurate mass as well as bond saturation. Further analysis of potential nefazodone metabolites was executed using accurate mass product ion spectra. Reported mass measurement errors for all full scan MS and MS/MS spectra was <3 ppm, regardless of relative ion abundance, which enabled the use of predictive software in determining product ion structure. The ability to conduct biotransformation profiling via tandem mass spectrometry coupled with accurate mass measurements, all in a single experimental run, is clearly one of the most attractive features of this methodology.

Objectives The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum. Design and methods The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants. Results In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67–0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts. Conclusions We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications.

The accurate diagnosis of Trisomy 21 requires invasive procedures that carry a risk of miscarriage. The current state-of-the-art maternal serum screening tests measure levels of PAPP-A, free bhCG, AFP, and uE3 in various combinations with a maximum sensitivity of 60-75% and a false positive rate of 5%. There is currently an unmet need for noninvasive screening tests with high selectivity that can detect pregnancies at risk, preferably within the first trimester. The aim of this study was to apply proteomics and mass spectrometry techniques for the discovery of new putative biomarkers for Trisomy 21 in first trimester maternal serum coupled with the immediate development of quantitative selective reaction monitoring (SRM) assays. The results of the novel workflow were 2-fold: (1) we identified a list of differentially expressed proteins in Trisomy 21 vs Normal samples, including PAPP-A, and (2) we developed a multiplexed, high-throughput SRM assay for verification of 12 new putative markers identified in the discovery experiments. To narrow down the initial large list of differentially expressed candidates resulting from the discovery experiments, we incorporated receiver operating characteristic (ROC) curve algorithms early in the data analysis process. We believe this approach provides a substantial advantage in sifting through the large and complex data typically obtained from discovery experiments. The workflow efficiently mined information derived from high-resolution LC-MS/MS discovery data for the seamless construction of rapid, targeted assays that were performed on unfractionated serum digests. The SRM assay lower limit of detection (LLOD) for the target peptides in a background of digested serum matrix was approximately 250-500 attomoles on column and the limit of accurate quantitation (LOQ) was approximately 1-5 femtomoles on column. The assay error as determined by coefficient of variation at LOQ and above ranged from 0 to 16%. The workflow developed in this study bridges the gap between proteomic biomarker discovery and translation into a clinical research environment. Specifically, for Trisomy 21, the described multiplexed SRM assay provides a vehicle for high-throughput verification of these, and potentially other, peptide candidates on larger sample cohorts.

Combining source collision-induced dissociation (CID) and tandem mass spectral acquisition in a pseudo-MS 3 experiment using a linear ion trap results in a highly selective and sensitive approach to identifying glycopeptide elution from a protein digest. The increased sensitivity is partially attributed to the nonselective nature of source CID, which allows simultaneous activation of all charge states and coeluting glycoforms generating greater ion abundance for the mass-to-charge (m/z) 204 and/or 366 oxonium ions. Unlike source CID alone, a pseudo-MS 3 approach adds selectivity while improving sensitivity by eliminating chemical noise during the tandem mass spectral acquisition of the oxonium ions in the linear ion trap. Performing the experiments in the hybrid linear ion trap/Fourier transform-ion cyclotron resonance (FT-ICR) enables subsequent high-resolution/high-mass accuracy full-scan mass spectra (MS) and parallel acquisition of MS/MS in the linear ion trap to be completed in 2 s directly following the pseudo-MS 3 scan to collate identification and characterization of glycopeptides in one experimental scan cycle. Analysis of bovine fetuin digest using the combined pseudo-MS 3 , high-resolution MS, and data-dependent MS/MS events resulted in identification of four N-linked and two O-linked glycopeptides without enzymatic cleavage of the sugar moiety or release of the sialic acids before analysis. In addition, over 95% of the total protein sequence was identified in one analytical run. (J Am Soc Mass Spectrom 2006, 17, 168 -179)