IsobarPTM: A software tool for the quantitative analysis of post-translationally modified proteins☆

The establishment of extremely powerful proteomics platforms able to map thousands of modification sites, e.g. phosphorylations or acetylations, over entire proteomes calls for equally powerful software tools to effectively extract useful and reliable information from such complex datasets. We present a new quantitative PTM analysis platform aimed at processing iTRAQ or Tandem Mass Tags (TMT) labeled peptides. It covers a broad range of needs associated with proper PTM ratio analysis such as PTM localization validation, robust ratio computation and statistical assessment, and navigable user report generation. IsobarPTM is made available as an R Bioconductor package and it can be run from the command line by non R specialists. Biological significance “IsobarPTM is a new software tool facilitating the quantitative analysis of protein modification regulation streamlining important issues related to PTM localization and statistical modeling. Users are provided with a navigable spreadsheet report, which also annotate already public modification sites.” This article is part of a Special Issue entitled: From Genome to Proteome: Open Innovations.

[1]  Brian E. Ruttenberg,et al.  PhosphoScore: an open-source phosphorylation site assignment tool for MSn data. , 2008, Journal of proteome research.

[2]  Martin Zeller,et al.  SLoMo: automated site localization of modifications from ETD/ECD mass spectra. , 2009, Journal of proteome research.

[3]  Markus Müller,et al.  EasyProt--an easy-to-use graphical platform for proteomics data analysis. , 2013, Journal of proteomics.

[4]  Steven P Gygi,et al.  A probability-based approach for high-throughput protein phosphorylation analysis and site localization , 2006, Nature Biotechnology.

[5]  Karl Mechtler,et al.  General statistical modeling of data from protein relative expression isobaric tags. , 2011, Journal of proteome research.

[6]  Robert Burke,et al.  ProteoWizard: open source software for rapid proteomics tools development , 2008, Bioinform..

[7]  M. Mann,et al.  Global, In Vivo, and Site-Specific Phosphorylation Dynamics in Signaling Networks , 2006, Cell.

[8]  S. Mohammed,et al.  Improved peptide identification by targeted fragmentation using CID, HCD and ETD on an LTQ-Orbitrap Velos. , 2011, Journal of proteome research.

[9]  Jennifer M. Bolin,et al.  Proteomic and phosphoproteomic comparison of human ES and iPS cells , 2011, Nature Methods.

[10]  Cathy H. Wu,et al.  The Universal Protein Resource (UniProt): an expanding universe of protein information , 2005, Nucleic Acids Res..

[11]  B. Kuster,et al.  Confident Phosphorylation Site Localization Using the Mascot Delta Score , 2010, Molecular & Cellular Proteomics.

[12]  M. Mann,et al.  Proteomic analysis of post-translational modifications , 2003, Nature Biotechnology.

[13]  Edward L. Huttlin,et al.  Systematic and quantitative assessment of the ubiquitin-modified proteome. , 2011, Molecular cell.

[14]  Derek J. Bailey,et al.  COMPASS: A suite of pre‐ and post‐search proteomics software tools for OMSSA , 2011, Proteomics.

[15]  Forest M White,et al.  Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML. , 2012, Nature chemical biology.

[16]  Bin Zhang,et al.  PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse , 2011, Nucleic Acids Res..

[17]  T. Köcher,et al.  Universal and confident phosphorylation site localization using phosphoRS. , 2011, Journal of proteome research.

[18]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[19]  Edward L Huttlin,et al.  Correct Interpretation of Comprehensive Phosphorylation Dynamics Requires Normalization by Protein Expression Changes* , 2011, Molecular & Cellular Proteomics.

[20]  Amos Bairoch,et al.  neXtProt: a knowledge platform for human proteins , 2011, Nucleic Acids Res..

[21]  Chunaram Choudhary,et al.  Proteome-wide Analysis of Lysine Acetylation Suggests its Broad Regulatory Scope in Saccharomyces cerevisiae* , 2012, Molecular & Cellular Proteomics.

[22]  Yi Zhang,et al.  multiplierz: an extensible API based desktop environment for proteomics data analysis , 2009, BMC Bioinformatics.

[23]  Arne G. Schmeisky,et al.  Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium , 2012, Molecular systems biology.

[24]  B. Kuster,et al.  Proteomics: a pragmatic perspective , 2010, Nature Biotechnology.

[25]  R. Aebersold,et al.  Quantitative analysis of protein phosphorylation on a system-wide scale by mass spectrometry-based proteomics. , 2010, Methods in enzymology.

[26]  Reinout Raijmakers,et al.  RockerBox: analysis and filtering of massive proteomics search results. , 2011, Journal of proteome research.

[27]  D. N. Perkins,et al.  Probability‐based protein identification by searching sequence databases using mass spectrometry data , 1999, Electrophoresis.

[28]  K. Parker,et al.  Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents*S , 2004, Molecular & Cellular Proteomics.

[29]  John S Garavelli,et al.  The RESID Database of Protein Modifications as a resource and annotation tool , 2004, Proteomics.

[30]  Andrew H. Thompson,et al.  Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. , 2003, Analytical chemistry.

[31]  J. Thomson,et al.  Human embryonic stem cell phosphoproteome revealed by electron transfer dissociation tandem mass spectrometry , 2009, Proceedings of the National Academy of Sciences.

[32]  K. Clauser,et al.  Modification Site Localization Scoring: Strategies and Performance , 2012, Molecular & Cellular Proteomics.

[33]  Karl Mechtler,et al.  High precision quantitative proteomics using iTRAQ on an LTQ Orbitrap: a new mass spectrometric method combining the benefits of all. , 2009, Journal of proteome research.

[34]  Patrick G. A. Pedrioli,et al.  Phosphoproteomic Analysis Reveals Interconnected System-Wide Responses to Perturbations of Kinases and Phosphatases in Yeast , 2010, Science Signaling.

[35]  A. Masselot,et al.  OLAV: Towards high‐throughput tandem mass spectrometry data identification , 2003, Proteomics.

[36]  D. Sabatini,et al.  The mTOR-Regulated Phosphoproteome Reveals a Mechanism of mTORC1-Mediated Inhibition of Growth Factor Signaling , 2011, Science.