ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

BackgroundSince its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.ResultWe introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.ConclusionsTargeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html

[1]  Sven Nahnsen,et al.  Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics. , 2010, Journal of proteome research.

[2]  Christoph H Borchers,et al.  Multiple Reaction Monitoring-based, Multiplexed, Absolute Quantitation of 45 Proteins in Human Plasma* , 2009, Molecular & Cellular Proteomics.

[3]  Daniel B. Martin,et al.  Computational prediction of proteotypic peptides for quantitative proteomics , 2007, Nature Biotechnology.

[4]  Christoph H Borchers,et al.  A Human Proteome Detection and Quantitation Project* , 2009, Molecular & Cellular Proteomics.

[5]  J. Mesirov,et al.  Prediction of high-responding peptides for targeted protein assays by mass spectrometry , 2009, Nature Biotechnology.

[6]  Henry H. N. Lam,et al.  PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows , 2008, EMBO reports.

[7]  Brendan MacLean,et al.  Bioinformatics Applications Note Gene Expression Skyline: an Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments , 2022 .

[8]  Ruedi Aebersold,et al.  Options and considerations when selecting a quantitative proteomics strategy , 2010, Nature Biotechnology.

[9]  R. Aebersold,et al.  mProphet: automated data processing and statistical validation for large-scale SRM experiments , 2011, Nature Methods.

[10]  Henry H. N. Lam,et al.  A database of mass spectrometric assays for the yeast proteome , 2008, Nature Methods.

[11]  Lennart Martens,et al.  TraML—A Standard Format for Exchange of Selected Reaction Monitoring Transition Lists* , 2011, Molecular & Cellular Proteomics.

[12]  E. Birney,et al.  Patterns of somatic mutation in human cancer genomes , 2007, Nature.

[13]  Christoph H Borchers,et al.  Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma , 2009, Nature Biotechnology.

[14]  R. Aebersold,et al.  Selected reaction monitoring for quantitative proteomics: a tutorial , 2008, Molecular systems biology.

[15]  Paul Shannon,et al.  The Protein Information and Property Explorer 2: Gaggle‐like exploration of biological proteomic data within one webpage , 2011, Proteomics.

[16]  BMC Bioinformatics , 2005 .

[17]  Nichole L. King,et al.  Targeted Quantitative Analysis of Streptococcus pyogenes Virulence Factors by Multiple Reaction Monitoring*S , 2008, Molecular & Cellular Proteomics.

[18]  Susan E Abbatiello,et al.  Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry. , 2010, Clinical chemistry.

[19]  David J. Reiss,et al.  The Gaggle: An open-source software system for integrating bioinformatics software and data sources , 2006, BMC Bioinformatics.

[20]  Gennifer E. Merrihew,et al.  Expediting the development of targeted SRM assays: using data from shotgun proteomics to automate method development. , 2009, Journal of proteome research.