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Nichols, RJ, Sen, S, Choo, YJ, Beltrao, P, Zietek, M, Chaba, R, Lee, S, Kazmierczak, KM, Lee, KJ, Wong, A, Shales, M, Lovett, S, Winkler, ME, Krogan, NJ, Typas, A and Gross, CA (2011) Phenotypic landscape of a bacterial cell. Cell 144:143-56


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.


PubMed PMC3060659 Online version:10.1016/j.cell.2010.11.052


Escherichia coli/drug effects; Escherichia coli/genetics; Escherichia coli/metabolism; Gene Deletion; Gene Expression Profiling; Genome, Bacterial; Genomics; Mutation


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Fitness scores (S-scores) were calculated as described in Collins et al [1] and Typas [2]. Fitness is based on colony size doubly normalized for the sizes of all colonies on the plate and the size of the specific strain under other conditions.


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  1. Collins, SR et al. (2006) A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7 R63 PubMed EcoliWiki page
  2. Typas, A et al. (2008) High-throughput, quantitative analyses of genetic interactions in E. coli. Nat. Methods 5 781-7 PubMed EcoliWiki page