Authors: Jeff S Piotrowski, Sheena C Li, Raamesh Deshpande, Scott W Simpkins, Justin Nelson, Yoko Yashiroda, Jacqueline M Barber, Hamid Safizadeh, Erin Wilson, Hiroki Okada, Abraham A Gebre, Karen Kubo, Nikko P Torres, Marissa A LeBlanc, Kerry Andrusiak, Reika Okamoto, Mami Yoshimura, Eva DeRango-Adem, Jolanda van Leeuwen, Katsuhiko Shirahige, Anastasia Baryshnikova, Grant W Brown, Hiroyuki Hirano, Michael Costanzo, Brenda Andrews, Yoshikazu Ohya, Hiroyuki Osada, Minoru Yoshida, Chad L Myers, Charles Boone
Summary:
Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.
Source:
Nature Chemical Biology; 2017