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A Systems Chemoproteomic Analysis of Acyl-CoA/Protein Interaction Networks

  1. Author:
    Levy, Michaella J
    Montgomery, David C
    Sardiu, Mihaela E
    Montano,Jose
    Bergholtz, Sarah E
    Nance,Kellie
    Thorpe,Abbey
    Fox,Stephen
    Lin, Qishan
    Andresson,Thorkell
    Florens, Laurence
    Washburn, Michael P
    Meier,Jordan

  2. Author Address

    Stowers Institute for Medical Research, Kansas City, MO 64110, USA., Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA., Laboratory of Proteomics and Analytical Technologies, Leidos, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA., RNA Epitranscriptomics & Proteomics Resource, University of Albany, 1400 Washington Avenue, Albany, NY 12222, USA., Stowers Institute for Medical Research, Kansas City, MO 64110, USA; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA. Electronic address: jordan.meier@nih.gov.,
    1. Year: 2020
    2. Date: MAR 19
    3. Epub Date: 2019 12 05
  2. Journal: Cell chemical biology
    1. 27
    2. 3
    3. Pages: 322-+
  4. Type of Article: Article
  5. ISSN: 2451-9448
  1. Abstract:

    Acyl-coenzyme A (CoA)/protein interactions are essential for life. Despite this importance, their global scope and selectivity remains undefined. Here, we describe CATNIP (CoA/AcetylTraNsferase Interaction Profiling), a chemoproteomic platform for the high-throughput analysis of acyl-CoA/protein interactions in endogenous proteomes. First, we apply CATNIP to identify acetyl-CoA-binding proteins through unbiased clustering of competitive dose-response data. Next, we use this method to profile the selectivity of acyl-CoA/protein interactions, leading to the identification of specific acyl-CoA engagement signatures. Finally, we apply systems-level analyses to assess the features of protein networks that may interact with acyl-CoAs, and use a strategy for high-confidence proteomic annotation of acetyl-CoA-binding proteins to identify a site of non-enzymatic acylation in the NAT10 acetyltransferase domain that is likely driven by acyl-CoA binding. Overall, our studies illustrate how chemoproteomics and systems biology can be integrated to understand the roles of acyl-CoA metabolism in biology and disease. Published by Elsevier Ltd.

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External Sources

  1. View Full Text
  2. DOI: 10.1016/j.chembiol.2019.11.011
  3. PMID: 31836350
  4. View record in Web of Science®
  5. WOS: 000521101900010
  6. PII : S2451-9456(19)30393-9

Library Notes

  1. Fiscal Year: FY2019-2020
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