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1.  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.
PMCID: PMC3857306  PMID: 22577019
Bioinformatics; Mass Spectrometry; Selected Reaction Monitoring; Transition
2.  Cross-Atlantic modification and validation of the A Tool to Assess Quality of Life in Idiopathic Pulmonary Fibrosis (ATAQ-IPF-cA) 
BMJ Open Respiratory Research  2014;1(1):e000024.
The A Tool to Assess Quality of Life in Idiopathic Pulmonary Fibrosis (ATAQ-IPF) was developed in the USA to assess health-related quality of life in patients with IPF. It is likely that some of the original ATAQ-IPF items perform differently when applied in different countries. This paper reports results of a study conducted to identify the need to refine the content of the ATAQ-IPF to minimise cross-country bias between the USA and the UK.
The ATAQ-IPF and other study measures were completed by patients attending specialist IPF clinics in the USA and UK. Rasch analysis was used to determine which items performed differently across countries (USA vs UK) and refine the original ATAQ-IPF to an instrument without cross-country bias (ATAQ-IPF-cA). Preliminary validation of the modified instrument was examined by assessing correlations between ATAQ-IPF-cA scores and scores from dyspnoea-specific patient-reported outcome (PRO) measures.
139 patients with IPF (USA=74; UK=65) participated in the study. A total of 41 items and 4 domains were removed from the original, 86-item instrument to yield the 43 items and 10 domains of the ATAQ-IPF-cA. Each domain had good fit to the Rasch model, internal consistency was comparable to the corresponding domains for the original ATAQ-IPF, and validity was supported by significant correlations between its scores and scores from dyspnoea-specific PROs.
The reliability and validity of the substantially shortened ATAQ-IPF-cA are acceptable and comparable to the original instrument. We recommend use of the ATAQ-IPF-cA in IPF studies in which participants are enrolled from the USA and UK.
PMCID: PMC4212790  PMID: 25478176
Interstitial Fibrosis
3.  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.
PMCID: PMC3832291  PMID: 22318887
data repository; MRM; software; SRM; targeted proteomics
4.  Integrated Bioinformatics for MS-Based Proteomics 
A typical tandem mass spectrometry (MS/MS) proteomics workflow involves a series of steps including format conversion, spectrum identification, peptide validation, protein inference, quantification, interpretation, and public repository deposition. This talk will provide an overview of the proteomic bioinformatics resources developed at the Institute for Systems Biology, covering the Trans-Proteomic Pipeline (TPP) and related tools, the PeptideAtlas public repository, and the emerging SRMAtlas resource. The TPP provides an easily-installable suite of tools to enable users to perform nearly all steps in an MS/MS analysis workflow. PeptideAtlas is a multi-species public compendium of peptide and protein identifications assembled from a large number of uniformly processed MS/MS experiments, along with tools to use the information in a variety of ways. SRMAtlas is a resource that enables the design of selected reaction monitoring (SRM) experiments based on information from several different sources. In addition, the interface of these resources with community standardization and cooperation efforts such as the Proteomics Standards Initiative and the ProteomeXchange Consortium will be presented.
PMCID: PMC3186501
5.  Development of the ATAQ-IPF: a tool to assess quality of life in IPF 
There is no disease-specific instrument to assess health-related quality of life (HRQL) in patients with idiopathic pulmonary fibrosis (IPF).
Patients' perspectives were collected to develop domains and items for an IPF-specific HRQL instrument. We used item variance and Rasch analysis to construct the ATAQ-IPF (A Tool to Assess Quality of life in IPF).
The ATAQ-IPF version 1 is composed of 74 items comprising 13 domains. All items fit the Rasch model. Domains and the total instrument possess acceptable psychometric characteristics for a multidimensional questionnaire. The pattern of correlations between ATAQ-IPF scores and physiologic variables known to be important in IPF, along with significant differences in ATAQ-IPF scores between subjects using versus those not using supplemental oxygen, support its validity.
Patient-centered and careful statistical methodologies were used to construct the ATAQ-IPF version 1, an IPF-specific HRQL instrument. Simple summation scoring is used to derive individual domain scores as well as a total score. Results support the validity of the ATAQ-IPF, and future studies will build on that validity.
PMCID: PMC2920246  PMID: 20673370
6.  Selected Reaction Monitoring (SRM) Analysis of Epidermal Growth Factor Receptor (EGFR) in Formalin Fixed Tumor Tissue 
Clinical proteomics  2012;9(1):5.
Analysis of key therapeutic targets such as epidermal growth factor receptor (EGFR) in clinical tissue samples is typically done by immunohistochemistry (IHC) and is only subjectively quantitative through a narrow dynamic range. The development of a standardized, highly-sensitive, linear, and quantitative assay for EGFR for use in patient tumor tissue carries high potential for identifying those patients most likely to benefit from EGFR-targeted therapies.
A mass spectrometry-based Selected Reaction Monitoring (SRM) assay for the EGFR protein (EGFR-SRM) was developed utilizing the Liquid Tissue®-SRM technology platform. Tissue culture cells (n = 4) were analyzed by enzyme-linked immunosorbent assay (ELISA) to establish quantitative EGFR levels. Matching formalin fixed cultures were analyzed by the EGFR-SRM assay and benchmarked against immunoassay of the non-fixed cultured cells. Xenograft human tumor tissue (n = 10) of non-small cell lung cancer (NSCLC) origin and NSCLC patient tumor tissue samples (n = 23) were microdissected and the EGFR-SRM assay performed on Liquid Tissue lysates prepared from microdissected tissue. Quantitative curves and linear regression curves for correlation between immunoassay and SRM methodology were developed in Excel.
The assay was developed for quantitation of a single EGFR tryptic peptide for use in FFPE patient tissue with absolute specificity to uniquely distinguish EGFR from all other proteins including the receptor tyrosine kinases, IGF-1R, cMet, Her2, Her3, and Her4. The assay was analytically validated against a collection of tissue culture cell lines where SRM analysis of the formalin fixed cells accurately reflects EGFR protein levels in matching non-formalin fixed cultures as established by ELISA sandwich immunoassay (R2 = 0.9991). The SRM assay was applied to a collection of FFPE NSCLC xenograft tumors where SRM data range from 305amol/μg to 12,860amol/μg and are consistent with EGFR protein levels in these tumors as previously-reported by western blot and SRM analysis of the matched frozen tissue. In addition, the SRM assay was applied to a collection of histologically-characterized FFPE NSCLC patient tumor tissue where EGFR levels were quantitated from not detected (ND) to 670amol/μg.
This report describes and evaluates the performance of a robust and reproducible SRM assay designed for measuring EGFR directly in FFPE patient tumor tissue with accuracy at extremely low (attomolar) levels. This assay can be used as part of a complementary or companion diagnostic strategy to support novel therapies currently under development and demonstrates the potential to identify candidates for EGFR-inhibitor therapy, predict treatment outcome, and reveal mechanisms of therapeutic resistance.
PMCID: PMC3464929  PMID: 22554165
Formalin fixed; FFPE; EGFR; Gefitinib; Targeted therapy; Patient tissue; Quantitative; Personalized medicine; Molecular diagnostics; Non-small cell lung cancer
7.  Estimation of Absolute Protein Quantities of Unlabeled Samples by Selected Reaction Monitoring Mass Spectrometry* 
Molecular & Cellular Proteomics : MCP  2011;11(3):M111.013987.
For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the “best flyer” hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R2 of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM, such as high sensitivity, selectivity, reproducibility, and dynamic range, and estimates absolute protein concentrations of selected proteins at minimized costs.
PMCID: PMC3316728  PMID: 22101334
8.  A rapid, reproducible, on-the-fly orthogonal array optimization method for targeted protein quantification by LC/MS and its application for accurate and sensitive quantification of carbonyl reductases in human liver 
Analytical chemistry  2010;82(7):2680-2689.
Liquid chromatography (LC)/mass spectrometry (MS) in selected-reactions-monitoring (SRM) mode provides a powerful tool for targeted protein quantification. However, efficient, high-throughput strategies for proper selection of signature peptides (SP) for protein quantification and accurate optimization of their SRM conditions remain elusive. Here we describe an on-the-fly, orthogonal array optimization (OAO) approach that enables rapid, comprehensive, and reproducible SRM optimization of a large number of candidate peptides in a single nanoflow-LC/MS run. With the optimized conditions, many peptide candidates can be evaluated in biological matrices for selection of the final SP. The OAO strategy employs a systematic experimental design that strategically varies product ions, de-clustering energy and collision energy in a cycle of 25 consecutive SRM trials, which accurately reveals the effects of these factors on the single-to-noise ratio of a candidate peptide, and optimizes each. As proof of concept, we developed a highly sensitive, accurate, and reproducible method for the quantification of carbonyl reductases CBR1 and CBR3 in human liver. Candidate peptides were identified by nano-LC/LTQ/Orbitrap, filtered using a stringent set of criteria, and subjected to OAO. After evaluating both sensitivity and stability of the candidates, two SP were selected for quantification of each protein. As a result of the accurate OAO of assay conditions, sensitivities of 80 and 110 amol were achieved for CBR1 and CBR3, respectively. The method was validated and used to quantify the CBRs in 33 human liver samples. The mean level of CBR1 was 93.4±49.7 (range: 26.2–241) ppm of total protein, and for CBR3 was 7.69±4.38 (range: 1.26–17.9) ppm. Key observations of this study are that: i) evaluation of peptide stability in the target matrix is essential for final selection of the SP; ii) utilization of two unique SP contributes to high reliability of target protein quantification; and iii) it is beneficial to construct calibration curves using standard proteins of verified concentrations to avoid severe biases that may result if synthesized peptides alone are used. Overall, the OAO method is versatile and adaptable to high-throughput quantification of validated biomarkers identified by proteomic discovery experiments.
PMCID: PMC2883886  PMID: 20218584
9.  Review of Software Tools for Design and Analysis of Large scale MRM Proteomic Datasets 
Methods (San Diego, Calif.)  2013;61(3):287-298.
Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow.
PMCID: PMC3775261  PMID: 23702368
Targeted proteomics; multiple reaction monitoring; database; bioinformatics; mass spectrometry
10.  Automated Selected Reaction Monitoring Software for Accurate Label-Free Protein Quantification 
Journal of Proteome Research  2012;11(7):3766-3773.
Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5–19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.
PMCID: PMC3426189  PMID: 22658081
targeted proteomics; mass spectrometry; selected reaction monitoring; label-free; software; quantification; Streptococcus pyogenes
11.  [No title available] 
Mass spectrometry (MS)-based proteomics fulfills most of the requirements for systems biology and due to the rapid development of new analytical strategies, it has become an essential tool to study molecular and cellular processes in living cells and organisms. In this regard, shotgun proteomics has proven to be valuable technique for the identification of large sets of proteins whereas targeted proteomics based on selected reaction monitoring (SRM) has emerged as a powerful technology for the reproducible and accurate quantification of subsets of proteins under multiple perturbed conditions. In parallel to these approaches, several efforts in instrumentation have been made to achieve sequencing of all the analytes present in a sample by acquiring fragment ion spectra in a data independent acquisition (DIA) manner1. Recently, a novel targeted data analysis strategy has been developed that brings consistent and accurate quantification capabilities of SRM to a level of extensive proteome coverage by mining the complete fragment ion spectra (SWATH-MS) generated during DIA2. This tutorial explains the application of SRM and DIA for quantitative proteomics, including the generation of MS/MS assays which can be used to acquire the analytes of interest by SRM or to extract the ion chromatograms from DIA data sets, and more particularly from data acquired by SWATH-MS.
PMCID: PMC3635450
12.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments 
Bioinformatics  2010;26(7):966-968.
Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools.
Availability: Single-click, self-updating web installation is available at This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC2844992  PMID: 20147306
13.  Expediting the Development of Targeted SRM Assays: Using Data from Shotgun Proteomics to Automate Method Development 
Journal of proteome research  2009;8(6):2733-2739.
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.
PMCID: PMC2743471  PMID: 19326923
14.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
15.  In silico design of targeted SRM-based experiments 
BMC Bioinformatics  2012;13(Suppl 16):S8.
Selected reaction monitoring (SRM)-based proteomics approaches enable highly sensitive and reproducible assays for profiling of thousands of peptides in one experiment. The development of such assays involves the determination of retention time, detectability and fragmentation properties of peptides, followed by an optimal selection of transitions. If those properties have to be identified experimentally, the assay development becomes a time-consuming task. We introduce a computational framework for the optimal selection of transitions for a given set of proteins based on their sequence information alone or in conjunction with already existing transition databases. The presented method enables the rapid and fully automated initial development of assays for targeted proteomics. We introduce the relevant methods, report and discuss a step-wise and generic protocol and we also show that we can reach an ad hoc coverage of 80 % of the targeted proteins. The presented algorithmic procedure is implemented in the open-source software package OpenMS/TOPP.
PMCID: PMC3489541  PMID: 23176520
16.  Development of a Chip/Chip/SRM platform using digital chip isoelectric focusing and LC-Chip mass spectrometry for enrichment and quantitation of low abundance protein biomarkers in human plasma 
Journal of proteome research  2011;11(2):808-817.
Protein biomarkers are critical for diagnosis, prognosis, and treatment of disease. The transition from protein biomarker discovery to verification can be a rate limiting step in clinical development of new diagnostics. Liquid chromatography-selected reaction monitoring mass spectrometry (LC-SRM MS) is becoming an important tool for biomarker verification studies in highly complex biological samples. Analyte enrichment or sample fractionation is often necessary to reduce sample complexity and improve sensitivity of SRM for quantitation of clinically relevant biomarker candidates present at the low ng/mL range in blood. In this paper, we describe an alternative method for sample preparation for LC-SRM MS, which does not rely on availability of antibodies. This new platform is based on selective enrichment of proteotypic peptides from complex biological peptide mixtures via isoelectric focusing (IEF) on a digital ProteomeChip (dPC™) for SRM quantitation using a triple quadrupole (QQQ) instrument with an LC-Chip (Chip/Chip/SRM). To demonstrate the value of this approach, the optimization of the Chip/Chip/SRM platform was performed using prostate specific antigen (PSA) added to female plasma as a model system. The combination of immunodepletion of albumin and IgG with peptide fractionation on the dPC, followed by SRM analysis, resulted in a limit of quantitation of PSA added to female plasma at the level of ~1–2.5 ng/mL with a CV of ~13%. The optimized platform was applied to measure levels of PSA in plasma of a small cohort of male patients with prostate cancer (PCa) and healthy matched controls with concentrations ranging from 1.5 to 25 ng/mL. A good correlation (r2 = 0.9459) was observed between standard clinical ELISA tests and the SRM-based-assay. Our data demonstrate that the combination of IEF on the dPC and SRM (Chip/Chip/SRM) can be successfully applied for verification of low abundance protein biomarkers in complex samples.
PMCID: PMC3656385  PMID: 22098410
Isoelectric focusing; IEF; digital ProteomeChip; dPC; selected reaction monitoring; SRM; prostate specific antigen; PSA; QQQ; LC-Chip
17.  P204-T Targeted Quantitative Protein Analysis in Human Plasma Using High-Resolution Multiple Selected Reaction Monitoring Assays on a Triple Quadruple Mass Spectrometer 
There is huge need for discovery and validation of novel biomarkers for early diagnoses of various diseases. Usually, a common endpoint for a biomarker discovery experiment is a list of putative marker proteins, and a reasonable next step will be to perform targeted quantitative measurements of these proteins in an expanded patient population to assess their validity as markers. Analytical accuracy and precision are required for unambiguous quantitative analysis of these targeted proteins from complex biological fluids, such as human plasma/serum. Wide dynamic range and high sensitivity are also critical for detecting low-abundance proteins from the complex samples.
One approach for this application is the use of tandem mass spectrometry to monitor a unique peptide (or peptides) from a protein of interest by a selected reaction monitoring (SRM) assay, or by simultaneous analysis of many peptides by a multiple selected reaction monitoring (mSRM) assay. This approach can be extended further to provide absolute quantitation of targeted proteins by incorporation of appropriate stable isotope-labeled peptides as internal standards. While mSRM assays are sensitive for targeted peptides, in a complex matrix, such as human serum, assay selectivity can become a major issue. It is often difficult to differentiate between the targeted peptide signal and matrix background, particularly when quantifying many very low abundance proteins. The unique high-resolution SRM (h-SRM) capability of the TSQ Quantum Ultra can help to significantly overcome this problem and increase mSRM assay specificity.
In this presentation, we demonstrate the TSQ Quantum Ultra mass spectrometer’s unparalleled capability for highly sensitive and accurate multiple protein quantitation from human plasma by using high-resolution multiple reaction assays. Over 300 mSRM transition assays were developed for detecting major proteins and known biomarkers simultaneously from human plasma by using both unit mass resolution and high-resolution on the Q1 quadruple.
PMCID: PMC2292018
18.  Rapid development of sensitive, high-throughput, quantitative and highly selective mass spectrometric targeted immunoassays for clinically important proteins in human plasma and serum 
Clinical biochemistry  2013;46(6):399-410.
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.
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.
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.
PMCID: PMC3779129  PMID: 23313081
Biomarker; SRM assay; Mass spectrometry; Proteomics; Immunoassay; Clinical proteomics
19.  Effect of Collision Energy Optimization on the Measurement of Peptides by Selected Reaction Monitoring (SRM) Mass Spectrometry 
Analytical chemistry  2010;82(24):10116-10124.
Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool (
PMCID: PMC3005404  PMID: 21090646
20.  Selected reaction monitoring for quantitative proteomics: a tutorial 
Systems biology relies on data sets in which the same group of proteins is consistently identified and precisely quantified across multiple samples, a requirement that is only partially achieved by current proteomics approaches. Selected reaction monitoring (SRM)—also called multiple reaction monitoring—is emerging as a technology that ideally complements the discovery capabilities of shotgun strategies by its unique potential for reliable quantification of analytes of low abundance in complex mixtures. In an SRM experiment, a predefined precursor ion and one of its fragments are selected by the two mass filters of a triple quadrupole instrument and monitored over time for precise quantification. A series of transitions (precursor/fragment ion pairs) in combination with the retention time of the targeted peptide can constitute a definitive assay. Typically, a large number of peptides are quantified during a single LC-MS experiment. This tutorial explains the application of SRM for quantitative proteomics, including the selection of proteotypic peptides and the optimization and validation of transitions. Furthermore, normalization and various factors affecting sensitivity and accuracy are discussed.
PMCID: PMC2583086  PMID: 18854821
mass spectrometry; MRM; proteomics; quantitative; SRM
21.  A highly sensitive targeted mass spectrometric assay for quantification of AGR2 protein in human urine and serum 
Journal of proteome research  2013;13(2):875-882.
Anterior gradient 2 (AGR2) is a secreted, cancer-associated protein in many types of epithelial cancer cells. We developed a highly sensitive targeted mass spectrometric assay for quantification of AGR2 in urine and serum. Digested peptides from clinical samples were processed by PRISM (high pressure and high resolution separations coupled with intelligent selection and multiplexing), which incorporates high pH reversed-phase LC separations to fractionate and select target fractions for follow-on LC-SRM analyses. The PRISM-SRM assay for AGR2 showed a reproducibility of <10% CV and LOQ values of ~130 pg/mL in serum and ~10 pg per 100 μg total protein mass in urine, respectively. A good correlation (R2 = 0.91) was observed for the measurable AGR2 concentrations in urine between SRM and ELISA. Based on an initial cohort of 37 subjects, urinary AGR2/PSA concentration ratios showed a significant difference (P = 0.026) between non-cancer and cancer. Large clinical cohort studies are needed for the validation of AGR2 as a useful diagnostic biomarker for prostate cancer. Our work validated the approach of identifying candidate secreted protein biomarkers through genomics and measurement by targeted proteomics, especially for proteins where no immunoassays are available.
PMCID: PMC3975687  PMID: 24251762
AGR2; PSA; prostate cancer; PRISM-SRM; human urine; human serum
22.  Selected reaction monitoring (SRM) mass spectrometry without isotope labeling can be used for rapid protein quantification 
The validation of putative biomarker candidates has become the major bottle-neck in protein biomarker development. Conventional immunoaffinity methods are limited by the availability of antibodies and kits. Here we demonstrated the feasibility of using the selected reaction monitoring (SRM) without isotope labeling to achieve fast and reproducible quantification of serum proteins. The SRM/MRM assays for three standard serum proteins, including ceruloplasmin (CP), serum aymloid A (SAA) and sex hormone binding globulin (SHBG) have good linear ranges, generally 103 – 104. There are almost perfect correlations between SRM intensities and the loaded peptide amounts (R2 is usually ~0.99). Our data suggest that SRM/MRM is able to quantify proteins at 0.2 – 2 fmol level, which are comparable to the commercial ELISA/LUMINEX kits for these proteins. Excellent correlations between SRM/MRM and ELISA/LUMINEX assays were observed for SAA and SHBG (R2 = 0.928 and 0.851 respectively). The correlation between SRM/MRM and ELISA for CP is less desirable (R2 = 0.565). The reproducibility for SRM/MRM assays is generally very good but may depend on the proteins/peptides (R2 = 0.931 and 0.882 for SAA and SHBG, and 0.723 for CP). SRM/MRM assay without isotope labeling is a rapid and useful method for protein biomarker validation in a modest number of samples and is especially useful when other assays such as ELISA or Luminex beads are not available.
PMCID: PMC4121859  PMID: 21594933
SRM/MRM; ELISA; Biomarker validation
23.  Long-gradient separations coupled with selected reaction monitoring for highly sensitive, large scale targeted protein quantification in a single analysis 
Analytical chemistry  2013;85(19):10.1021/ac402105s.
Long-gradient separations coupled to tandem MS were recently demonstrated to provide a deep proteome coverage for global proteomics; however, such long-gradient separations have not been explored for targeted proteomics. Herein, we investigate the potential performance of the long-gradient separations coupled with selected reaction monitoring (LG-SRM) for targeted protein quantification. Direct comparison of LG-SRM (5 h gradient) and conventional LC-SRM (45 min gradient) showed that the long-gradient separations significantly reduced background interference levels and provided an 8- to 100-fold improvement in LOQ for target proteins in human female serum. Based on at least one surrogate peptide per protein, an LOQ of 10 ng/mL was achieved for the two spiked proteins in non-depleted human serum. The LG-SRM detection of seven out of eight endogenous plasma proteins expressed at ng/mL or sub-ng/mL levels in clinical patient sera was also demonstrated. A correlation coefficient of >0.99 was observed for the results of LG-SRM and ELISA measurements for prostate-specific antigen (PSA) in selected patient sera. Further enhancement of LG-SRM sensitivity was achieved by applying front-end IgY14 immunoaffinity depletion. Besides improved sensitivity, LG-SRM potentially offers much higher multiplexing capacity than conventional LC-SRM due to an increase in average peak widths (~3-fold) for a 300-min gradient compared to a 45-min gradient. Therefore, LG-SRM holds great potential for bridging the gap between global and targeted proteomics due to its advantages in both sensitivity and multiplexing capacity.
PMCID: PMC3839867  PMID: 24004026
long-gradient; targeted quantification; low-abundance protein; human serum; sensitivity; reproducibility
24.  A Multi-Centric Study To Assess Reproducibility of Protein Quantification By SRM LC-MS Proteomic Analysis 
In order to evaluate the robustness and reproducibility, within and across laboratories, of the SRM quantification methodology, we set up a multi-centric study (PME7) carried out at 9 laboratories, most of them members of the ProteoRed-ISCIII network of proteomics facilities in Spain.
Each participant laboratory received identical samples of a “Quantitative Proteomics Sample Set” prepared by Sigma-Aldrich. The sample set consisted of 5 different samples A-E, containing tryptic digests of 9 human proteins, spiked in different amounts to a yeast lysate digest. The amounts of these proteins are distributed in three different concentration “Tiers”: Tier 1: 3 protein digests in the range 25-2500 fmol / microgram of yeast lysate; Tier 2: 3 protein digests in the range 2.5- 1250 fmol / microgram of yeast lysate; Tier 3: 3 protein digests in the range 0.25-25 fmol / microgram of yeast lysate. In addition, each sample contains identical amount (250 fmol) of a tenth protein digest, for normalization purposes. Finally, two different labeled AQUA peptides per protein were added to each sample in defined amounts.
The five samples were analyzed in triplicate by SRM at the different laboratories, using similar, but not strictly identical, chromatographic and spectrometric conditions, and with different instruments. Each laboratory reported results on relative quantification (fold changes between A-E samples) and absolute quantification based on the AQUA peptide standards.
The results demonstrate a good degree of reproducibility of targeted quantification measurements by SRM at different laboratories, irrespective of the method of analysis and the spectrometer used. The average %CV of the measured absolute protein amounts ranges from less than 10% for Tier 1 proteins, to 40-60% for the proteins at the lowest concentrations.
The results obtained at each laboratory allow the assessment of the limitations in sensitivity and limits of quantification under the diverse analytical conditions used.
PMCID: PMC3630565
25.  OmicsHub Proteomics Software Tool 
OmicsHub Proteomics integrates in one single platform all the steps of a Mass Spectrometry Experiment reducing time and data management complexity. The proteomics data automation and data management/analysis provided by OmicsHub Proteomics solves the typical problems your lab members find on a daily basis and makes life easier when performing tasks such as multiple search engine support, pathways integration or custom report generation for external customers. OmicsHub has been designed as a central data management system to collect, analyze and annotate proteomics experimental data enabling users to automate tasks. OmicsHub Proteomics helps laboratories to easily meet proteomics standards such as PRIDE or FuGE and works with controlled vocabulary experiment annotation. The software enables your lab members to take a greater advantage of the Mascot and Phenyx search engines unique capabilities for protein identification. Multiple searches can be launch at once, allowing peak list data from several spots or chromatograms to be sent concurrently to Mascot/Phenyx. OmicsHub Proteomics works for both LC and Gel workflows. The system allows to store and compare proteomics data generated from different Mass Spectrometry instruments in a single platform instead of having a specific software for each of them. It is a web application which installs in a single server needing just Web Browser to have access to it. All experimental actions are userstamp and datestamp allowing the audit tracking of every action performed in OmicsHub. Some of the OmicsHub Proteomics main features are Protein identification, Biological annotation, Report customization, PRIDE standard, Pathways integration, Group proteins results removing redundancy, Peak filtering and FDR cutoff for decoy databases. OmicsHub Proteomics its flexible enough to parsers for new file formats to be easily imported and fits your budget having a very competitive price for its perpetual license.
PMCID: PMC2918172

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