Title |
Discovery of Enzymatic Targets of Transcriptional Activators via in Vivo Covalent Chemical Capture
|
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Published in |
Journal of the American Chemical Society, September 2016
|
DOI | 10.1021/jacs.6b07680 |
Pubmed ID | |
Authors |
Amanda Dugan, Chinmay Y. Majmudar, Rachel Pricer, Sherry Niessen, Jody K. Lancia, Hugo Yik-Hong Fung, Benjamin F. Cravatt, Anna K. Mapp |
Abstract |
The network of activator protein-protein interactions (PPIs) that underpin transcription initiation is poorly defined, particularly in the cellular context. The transient nature of these contacts and the often low abundance of the participants present significant experimental hurdles. Through the coupling of in vivo covalent chemical capture and shotgun LC-MS/MS (MudPIT) analysis, we can trap the PPIs of transcriptional activators in a cellular setting and identify the binding partners in an unbiased fashion. Using this approach, we discover that the prototypical activators Gal4 and VP16 target the Snf1 (AMPK) kinase complex via direct interactions with both the core enzymatic subunit Snf1 and the exchangeable subunit Gal83. Further, we use a tandem reversible formaldehyde and irreversible covalent chemical capture approach (TRIC) to capture the Gal4-Snf1 interaction at the GAL1 promoter in live yeast. Together, these data support a critical role for activator PPIs in both the recruitment and positioning of important enzymatic complexes at a gene promoter and represents a technical advancement in the discovery of new cellular binding targets of transcriptional activators. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 50% |
France | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
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Scientists | 3 | 75% |
Members of the public | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 2% |
Unknown | 58 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 16 | 27% |
Student > Master | 7 | 12% |
Student > Bachelor | 6 | 10% |
Researcher | 6 | 10% |
Student > Doctoral Student | 5 | 8% |
Other | 8 | 14% |
Unknown | 11 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 25 | 42% |
Biochemistry, Genetics and Molecular Biology | 10 | 17% |
Agricultural and Biological Sciences | 4 | 7% |
Engineering | 3 | 5% |
Computer Science | 1 | 2% |
Other | 3 | 5% |
Unknown | 13 | 22% |