Nature Chemical BiologySystems BiologyPeer-reviewed journal article
Functional Annotation of Chemical Libraries across Diverse Biological Processes
Jeff S. PiotrowskiiD, Sheena Claire LiiD, Raamesh Deshpande, Scott W. SimpkinsiD, Justin NelsoniD, Yoko YashirodaiD, Jacqueline M. Barber, Hamid SafizadehiD, Erin H. WilsoniD, Hiroki OkadaiD, Abraham Abera GebreiD, Karen Kubo, Nikko P. Torres, Marissa A. LeBlanciD, Kerry AndrusiakiD, Reika Okamoto, Mami Yoshimura, Eva DeRango-Adem, Jolanda S. van LeeuweniD, Katsuhiko ShirahigeiD, Anastasia BaryshnikovaiD, Grant W. BrowniD, Hiroyuki HiranoiD, Michael CostanzoiD, Brenda AndrewsiD, , Charles M. BooneiD
Abstract
Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells to a compound, revealing chemical-genetic interactions that can elucidate a compounds mode of action. We developed a highly parallel and 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 all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode sequencing protocol, enabling 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 7 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.
- Citations
- 96
- FWCI
- 4.58
- Field percentile
- top 4%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interaction networks
Scott W. Simpkins, Justin Nelson, … Chad L. Myers·PLoS Computational BiologyPeer-reviewed·Oct 30, 2018
- Improving prediction of compound function from chemical structure using chemical-genetic networks
Hamid Safizadeh, Scott W. Simpkins, … Chad L. Myers·Journal of Chemical Information and ModelingPeer-reviewed·Jul 28, 2021
- MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action
Justin Nelson, Scott W. Simpkins, … Chad L. Myers·BioinformaticsPeer-reviewed·Nov 29, 2017
- ChemGAPP; A Package for Chemical Genomics Analysis and Phenotypic Profiling.
Hannah M. Doherty, George Kritikos, … Danesh Moradigaravand·bioRxiv·Jan 5, 2023
- Population-scale chemical response revealed by a barcoded yeast collection
Abhishek Dutta, Marion Garin, … Joseph Schacherer·Nature CommunicationsPeer-reviewed·May 28, 2026
- Predicting compound activity from phenotypic profiles and chemical structures
Nikita Moshkov, Tim Becker, … Juan C. Caicedo·Nature CommunicationsPeer-reviewed·Apr 8, 2023