PMID:21185072

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Citation

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

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.

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Keywords

phenotype; phenomic profiling; phenotypic signature; hierarchical clustering; responsive genome; high-throughput; chemical genomics; stress; essential; function; antibiotic resistance; synergy

Main Points of the Paper

  • Key Motivation- provide phenotypes for mutants of genes without functional annotation
  • Central Goal- systematically evaluate the impact of every gene deletion on E.coli fitness in diverse environments
  • Phenomic Profiling- quantitative description of the response of all single-gene deletions to physiologically relevant stresses and drug challenges
    • profiled ~4,000 genes in 324 conditions covering 114 unique stresses (more than half were antimicrobial/antibiotic stress)
    • identified thousands of phenotypes
    • identified a diverse set of conditionally essential genes
      • Identified 116 rich-media conditionally essential (CE) genes
    • facilitates high-confidence association of genes of unknown function to those of known function
    • generates numerous leads concerning drug function
  • Hierarchical clustering
  • Phenotypic Signature- response of each mutant strain across all conditions
    • high correlation b/t two phenotypic signatures implies a functional connection b/t genes

Materials and Methods Used

Strain Details

  • Keio single-gene deletion library
  • essential gene hypomorphs
  • RNA/small protein knockout library

Equipment and Reagents

Procedure

Phenomic Profiling

Data Analysis

Hierarchical clustering

Phenotype Annotations

See Help:AnnotationTable for details on how to edit this table.

OMP Accession Taxon Information Genotype Information (if known) OMP ID OMP Term Name Phenotype Details Related Rows ECO ID ECO Term Name Notes Status

Escherichia coli

K-12 BW25113

ECK3620-RFAP

sensitivity to 0.1% bile salts

Growth

slow growth

Growth Curve

rfaP phosphorylates core heptose of lipopolysaccharide

Escherichia coli

K-12 BW25113

ECK0223-LPCA

sensitivity to 1.2 mM DIBUCAINE

Growth

slow growth

Growth Curve

the target of DIBUCAINE is the membrane (pmf)

Escherichia coli

K-12 BW25113

ECK3610-RFAF

sensitivity to 0.1% bile salts

Growth

slow growth

Growth Curve

rfaF = ADP-heptose:LPS heptosyltransferase II

target of bile salts: membrane

Escherichia coli

K-12 BW25113

ECK3042-RFAE

sensitivity to 30 µg/ml NOVOBIOCIN

Growth

slow growth

Growth Curve

ECK3042-RFAE = heptose 7-phosphate kinase/heptose 1-phosphate adenyltransferase

the target of NOVOBIOCIN is DNA gyrase

Escherichia coli

K-12 BW25113

ECK3610-RFAE

sensitivity to 0.1% bile salts

Growth

slow growth

Growth Curve

ECK3042-RFAE = heptose 7-phosphate kinase/heptose 1-phosphate adenyltransferase

target of bile salts: membrane


Notes

References

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