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J Bacteriol. 2003 Aug;185(16):4956-72.

Phenotype microarray analysis of Escherichia coli K-12 mutants with deletions of all two-component systems.

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  • 1Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, USA.

Abstract

Two-component systems are the most common mechanism of transmembrane signal transduction in bacteria. A typical system consists of a histidine kinase and a partner response regulator. The histidine kinase senses an environmental signal, which it transmits to its partner response regulator via a series of autophosphorylation, phosphotransfer, and dephosphorylation reactions. Much work has been done on particular systems, including several systems with regulatory roles in cellular physiology, communication, development, and, in the case of bacterial pathogens, the expression of genes important for virulence. We used two methods to investigate two-component regulatory systems in Escherichia coli K-12. First, we systematically constructed mutants with deletions of all two-component systems by using a now-standard technique of gene disruption (K. A. Datsenko and B. L. Wanner, Proc. Natl. Acad. Sci. USA 97:6640-6645, 2000). We then analyzed these deletion mutants with a new technology called Phenotype MicroArrays, which permits assays of nearly 2,000 growth phenotypes simultaneously. In this study we tested 100 mutants, including mutants with individual deletions of all two-component systems and several related genes, including creBC-regulated genes (cbrA and cbrBC), phoBR-regulated genes (phoA, phoH, phnCDEFGHIJKLMNOP, psiE, and ugpBAECQ), csgD, luxS, and rpoS. The results of this battery of nearly 200,000 tests provided a wealth of new information concerning many of these systems. Of 37 different two-component mutants, 22 showed altered phenotypes. Many phenotypes were expected, and several new phenotypes were also revealed. The results are discussed in terms of the biological roles and other information concerning these systems, including DNA microarray data for a large number of the same mutants. Other mutational effects are also discussed.

PMID:
12897016
[PubMed - indexed for MEDLINE]
PMCID:
PMC166450
Free PMC Article

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