Personalized medicine will depend on molecular signatures to match the right patients to the right drugs, first in clinical trials, then in clinical practice. Personalized medicine is a new paradigm in which information technology, science, and clinical treatment are synergistically integrated to improve health and patient well-being. This approach requires unusually large databases, relating both molecular and clinical data, such that patients can be proactively selected for the most appropriate therapies. Towards achieving personalized medicine, it is crucial to begin developing sensitive and reliable assays to quantitatively detect the tri-omic signatures of gene expression, metabolite and protein changes and distribution. For proteins, we must measure the homeostatic or aberrant distribution in order to help define the current health status or disease state. The specific, simple and immediate goal of our proposal is to develop a complete proteome centric database to allow the targeted analysis of any human protein(s) of interest through the use of multiple-reaction- monitoring (MRM). We will develop and provide a proteotypic peptide fragmentation database, of at least 4 peptides per human protein-coding gene, with verified rapid and accurate MRM based mass spectrometric assays to unambiguously identify and quantify any protein of the human proteome in a multitude of samples. The estimated number of human protein-coding genes is 20,332 based on strict criteria, but can be as high as 25,000. Our approach involves building a comprehensive, publicly available database for users to query and download all the information required to rapidly implement targeted assays against proteins of interest in plasma or other human tissues. In addition, this effort provides a verified proteotypic peptide database for designing peptide-epitope capture reagents (e.g., antibodies) to further drive the sensitivity of the technique at least 2 orders of magnitude lower than the current instrumental limits of ~1-10 ng/mL. Through the use of the ISB-developed human PeptideAtlas, a highly curated proteotypic peptide compendium of all available mass spectrometry data of human proteins as well as other species, efforts are underway for the building of a comprehensive MRMAtlas that contains complete information on the peptide and peptide fragment mass, fragmentation propensity as well as standardized instrumental conditions to employ for successful application of multiplexed quantitative assays. For our proposal, production of small quantities of peptides (~4 peptides per human protein) based on the proteotypic peptides identified through PeptideAtlas and proteotypic peptide predictability software will be used to build a comprehensive MRMAtlas that will contain all the relevant peptide biophysical information, fragmentation information, instrumental conditions, as well as links to some validated assays, all completed in a 2-year time frame. The time is right to create the complete human proteome MRMAtlas. This will undoubtedly accelerate efforts to develop sensitive and reliable assays for early detection, therapy assessment and prognosis evaluation for cancer as well as other human diseases.

Public Health Relevance

The synergistic combination of proteomics, genomics, metabolomics and clinical data will pave the path to personalized medicine by improving diagnostic capabilities, prognostic accuracy, and the development of new, individually tailored therapeutics.
We aim to implement state-of-the-art proteomics technology to acquire a unique complete human proteomics compendium for targeting and quantitating any human protein in a multiplexed manner. Our ultimate goal is to integrate this unique targeted proteomics database with genomic and clinical databases, thus providing an invaluable national resource that will expedite current efforts to develop highly sensitive and targeted proteomics-based assays for studying human disease to provide better patient care.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
High Impact Research and Research Infrastructure Programs (RC2)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-BCMB-B (99))
Program Officer
Felsenfeld, Adam
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Institute for Systems Biology
United States
Zip Code
Michalik, Stephan; Depke, Maren; Murr, Annette et al. (2017) A global Staphylococcus aureus proteome resource applied to the in vivo characterization of host-pathogen interactions. Sci Rep 7:9718
Zolg, Daniel P; Wilhelm, Mathias; Schnatbaum, Karsten et al. (2017) Building ProteomeTools based on a complete synthetic human proteome. Nat Methods 14:259-262
Price, Nathan D; Magis, Andrew T; Earls, John C et al. (2017) A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nat Biotechnol 35:747-756
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
Kusebauch, Ulrike; Campbell, David S; Deutsch, Eric W et al. (2016) Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome. Cell 166:766-778
Craciun, Florin L; Bijol, Vanesa; Ajay, Amrendra K et al. (2016) RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis. J Am Soc Nephrol 27:1702-13
Vialas, Vital; Sun, Zhi; Reales-Calderón, Jose A et al. (2016) A comprehensive Candida albicans PeptideAtlas build enables deep proteome coverage. J Proteomics 131:122-130
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 136:1732-1735
Qin, Shizhen; Zhou, Yong; Gray, Li et al. (2016) Identification of Organ-Enriched Protein Biomarkers of Acute Liver Injury by Targeted Quantitative Proteomics of Blood in Acetaminophen- and Carbon-Tetrachloride-Treated Mouse Models and Acetaminophen Overdose Patients. J Proteome Res 15:3724-3740
Hesselager, Marianne O; Codrea, Marius C; Sun, Zhi et al. (2016) The Pig PeptideAtlas: A resource for systems biology in animal production and biomedicine. Proteomics 16:634-44

Showing the most recent 10 out of 55 publications