Proteins are functional molecules in living systems and carry out most beneficial and deleterious function that affects life. A single protein may be involved in many different functional pathways and in living cells, interactions among proteins are the single strongest determinants that drive function. Therefore, the greatest opportunity to map coordinates of protein function for unknown or uncharacterized gene products would be presented if protein interaction networks that involve these proteins could visualized. The Protein Interaction Technology Core in this project is the product of many years of development efforts to pioneer new capabilities for visualization of protein interaction networks in live cells. This core will provide novel cross-linking and protein interaction identification technologies to support the overarching goal to place uncharacterized gene products within protein interaction networks in live A. baumannii cells. Through the core efforts to identify cross-linked peptides, interacting partner proteins and topological features of these interactions will be visualized. These data will form the basis of new interaction networks that can be mapped onto existing crystal structures for homologous or orthologous proteins and existing networks in other organisms to help link uncharacterized genes.

Public Health Relevance

Neariy all diseases are mediated by proteins and the ability to comprehend function of uncharacterized proteins requires increased efforts to identify protein-protein interactions that exist in cells. This Core will identify protein-protein interaction networks in the pathogen A. baumannii to help map functionality of uncharacterized genes in these bacteria.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Program--Cooperative Agreements (U19)
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Special Emphasis Panel (ZAI1-FDS-M)
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University of Washington
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Schweppe, Devin K; Chavez, Juan D; Lee, Chi Fung et al. (2017) Mitochondrial protein interactome elucidated by chemical cross-linking mass spectrometry. Proc Natl Acad Sci U S A 114:1732-1737
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Schweppe, Devin K; Zheng, Chunxiang; Chavez, Juan D et al. (2016) XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data. Bioinformatics 32:2716-8

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