Mass spectrometry based proteomics is a key technology for the identification, quantification and comparison of proteins and their post-translational modifications across all aspects of biology. One major barrier in proteomics workflows is the paucity of flexible and customizable computational frameworks for generating data analysis software pipelines. Current software pipelines are often static, with limited flexibility beyond the specific analyses for which they were created and generally lag behind due to little or no maintenance. These tools therefore lack broad functionality and improvements in areas such as statistical validation, limiting the potential of the software to mere spectrum matching through black box tools. To address these barriers, we have been developing, maintaining and distributing cutting edge proteomics computational tools and standards in data analysis over the last 12 years through our program suite called the Trans-Proteomic Pipeline. Concomitant with software development, we ensure wide community adoption through extensive tutoring to all interested users of the proteomics community. Through our development, we have provided new functionality for proteomics data analyses with both new and improved statistical validation and global qualification. However, with new styles of mass spectrometry instrumentation that attempt to now provide comprehensive analysis, software tools must be continually maintained and new functionality developed in an extensible and flexible framework that ensures robust, routine operation so that it provides the user community, from novice to the most extreme power experts, with trusted results. The Trans-Proteomic Pipeline has been the first and most continually developed and maintained product for these requirements. Our goal of providing all these tools as both full open source and freely available complement of programs, ensures wide adoption and permits community input into the tools development for the broadest and most needed functionality possible. This continuing program of development and maintenance of the Trans-Proteomic Pipeline builds on the successful approach of robust tools development with the focus of """"""""from start to the end analysis"""""""" of proteomics data. With ever increasing data collection rates at a """"""""Moore's Law"""""""" level, this program will continue to develop tools to analyze these larger and larger datasets. We will develop and integrate tools for new styles of proteomic data collection such as multiplexed data-independent analysis capable of providing near full proteome quantitation in a single analysis, integration of next generation RNA-seq genomic analysis for sample specific databases, post-translational modification statistical analysis for confident site specific identification, and the implementation of new selected-reaction monitoring capabilities that drive proteomics as the next generation """"""""Western Blot"""""""". All these efforts are underpinned by a strong computational and biochemistry focused background to ensure the tools are well written with maximum relevance to biology.

Public Health Relevance

Mass spectrometry based proteomics is a key technology for the identification and quantification of proteins in many types of biological samples. Proteomics can be used to determine aberrant expression of proteins that can indicate which cellular systems are under stress or the cause of a disease and proteomics can be used for the discovery of disease biomarkers and validation for therapeutic strategies. At a more basic level, proteomics via mass spectrometry allows for an understanding of how the 20,000 proteins in a human can interact in complex biological systems. However, when compared to other biomedical measurement technologies, this incredibly powerful technology is limited in its scope and its pervasiveness due to the data handling systems taking the output of the mass spectrometers. To understand this data, one needs to quickly, comprehensively and statistically validate this data with confidence to allow all users to understand, compare and share data from the novice to the expert user .The opportunity, presented within this grant, is to take the leading freely available proteomics analysis software suite for the analysis of mass spectrometry, the Trans-Proteomics Pipeline (TPP), and make it easier to use, maintain and extend to ensure all users of mass spectrometry gain the most benefit out of the powerful mass spectrometry technology used for proteomics.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Sheeley, Douglas
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Institute for Systems Biology
United States
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Deutsch, Eric W; Csordas, Attila; Sun, Zhi et al. (2017) The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition. Nucleic Acids Res 45:D1100-D1106
Vizcaíno, Juan Antonio; Mayer, Gerhard; Perkins, Simon et al. (2017) The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics. Mol Cell Proteomics 16:1275-1285
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Xue, Ting; Liu, Ping; Zhou, Yong et al. (2016) Interleukin-6 Induced ""Acute"" Phenotypic Microenvironment Promotes Th1 Anti-Tumor Immunity in Cryo-Thermal Therapy Revealed By Shotgun and Parallel Reaction Monitoring Proteomics. Theranostics 6:773-94
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Maixner, Frank; Krause-Kyora, Ben; Turaev, Dmitrij et al. (2016) The 5300-year-old Helicobacter pylori genome of the Iceman. Science 351:162-165
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Winget, Jason M; Finlay, Deborah; Mills, Kevin J et al. (2016) Quantitative Proteomic Analysis of Stratum Corneum Dysfunction in Adult Chronic Atopic Dermatitis. J Invest Dermatol 136:1732-5

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