Mass spectrometry is based on fragmenting biological molecules into smaller pieces, and using the fragment masses as a fingerprint for identifying and quantifying bio-molecules. It is the dominant technology for studying active molecules in healthy and diseased tissue, and identifying protein targets and natural products for novel therapeutics. When the initial proposal Center for Computational Mass Spectrometry (CCMS) was submitted in 2007, the lack of adequate computational tools for analyzing mass spectrometry data was the the key bottleneck. With great success in enabling applications of new experimental techniques such as FTMS, ETD, HCD, top-down mass spectrometry, and many others, the mandate of CCMS continues to be the development of next generation computational technologies and to apply them to open experimental. In this proposal, we will capitalize on our recent results in diverse subfields of computational proteomics and will further branch into previously unexplored MS applications. We will focus specifically on bridging proteomics and genomics technologies using 6 technology research and development platforms. Specifically, we will (a) apply proteogenomics approach for the discovery of abberant cancer genes and analyzing antibody repertoires; (b) sequence natural antibiotics; (c) collate spectral data through spectral archives and networks; (d) develop universal tools for peptide identification; (e) develop tools for top-down proteomics; and, (f) analyzing multiplexed spectra. The technology platforms are driven by a multitude of collaborative biomedical studies where the use of CCMS developed tools is essential for their success. These studies include (a) unraveling the combinatorial histone code in human diseases; (b) a proteogenomics approach to studies of oral microbiome and polybacterial infections; (c) detecting inter-species chemical interactions; (d) developing a systems approach towards the therapeutic modulation of the acetylome ; (e) developing tools for monoclonal and polyclonal antibody sequencing; (f) development of breast cancer vaccines; (g) clinical cancer proteogenomics; (h) discovery of lantibiotics; (i) discovering proteomic biomarkers for drug toxicity in cancer patients; and, (j) identifying protein-protein interactions and post-translational modifications in cataractous lens. These projects require three-way collaborative efforts on a wide range of topics involving biomedical scientists, mass spectrometrists, and computational scientists from various institutions. CCMS will also train students and practicing scientists from all over the world in computational proteomics, and educate the proteomics community about modern computational mass spectrometry to encourage its wide adoption.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Biotechnology Resource Grants (P41)
Project #
5P41GM103484-08
Application #
9099881
Study Section
Special Emphasis Panel (ZRG1)
Project Start
Project End
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
8
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of California San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Tripathi, Anupriya; Melnik, Alexey V; Xue, Jin et al. (2018) Intermittent Hypoxia and Hypercapnia, a Hallmark of Obstructive Sleep Apnea, Alters the Gut Microbiome and Metabolome. mSystems 3:
Patin, Nastassia V; Floros, Dimitrios J; Hughes, Chambers C et al. (2018) The role of inter-species interactions in Salinispora specialized metabolism. Microbiology 164:946-955
Gurevich, Alexey; Mikheenko, Alla; Shlemov, Alexander et al. (2018) Increased diversity of peptidic natural products revealed by modification-tolerant database search of mass spectra. Nat Microbiol 3:319-327
Wang, Mingxun; Wang, Jian; Carver, Jeremy et al. (2018) Assembling the Community-Scale Discoverable Human Proteome. Cell Syst 7:412-421.e5
Mohimani, Hosein; Gurevich, Alexey; Shlemov, Alexander et al. (2018) Dereplication of microbial metabolites through database search of mass spectra. Nat Commun 9:4035
Rozanov, Dmitri V; Rozanov, Nikita D; Chiotti, Kami E et al. (2018) MHC class I loaded ligands from breast cancer cell lines: A potential HLA-I-typed antigen collection. J Proteomics 176:13-23
Fisher, Mark F; Zhang, Jingjing; Taylor, Nicolas L et al. (2018) A family of small, cyclic peptides buried in preproalbumin since the Eocene epoch. Plant Direct 2:
Beyter, Doruk; Lin, Miin S; Yu, Yanbao et al. (2018) ProteoStorm: An Ultrafast Metaproteomics Database Search Framework. Cell Syst 7:463-467.e6
Puri, Aaron W; Mevers, Emily; Ramadhar, Timothy R et al. (2018) Tundrenone: An Atypical Secondary Metabolite from Bacteria with Highly Restricted Primary Metabolism. J Am Chem Soc 140:2002-2006
Kolmogorov, Mikhail; Kennedy, Eamonn; Dong, Zhuxin et al. (2017) Single-molecule protein identification by sub-nanopore sensors. PLoS Comput Biol 13:e1005356

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