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Cell. 2011 Jan 7;144(1):143-56. doi: 10.1016/j.cell.2010.11.052. Epub 2010 Dec 23.

Phenotypic landscape of a bacterial cell.

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  • 1University of California, San Francisco, 94143, USA.

Abstract

The explosion of sequence information in bacteria makes developing high-throughput, cost-effective approaches to matching genes with phenotypes imperative. Using E. coli as proof of principle, we show that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery. Probing growth profiles of a mutant library in hundreds of conditions in parallel yielded > 10,000 phenotypes that allowed us to study gene essentiality, discover leads for gene function and drug action, and understand higher-order organization of the bacterial chromosome. We highlight new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides. This data set, publicly available at http://ecoliwiki.net/tools/chemgen/, is a valuable resource for both the microbiological and bioinformatic communities, as it provides high-confidence associations between hundreds of annotated and uncharacterized genes as well as inferences about the mode of action of several poorly understood drugs.

Copyright © 2011 Elsevier Inc. All rights reserved.

PMID:
21185072
[PubMed - indexed for MEDLINE]
PMCID:
PMC3060659
Free PMC Article
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