Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 102, Issue 8, Pages 2862-2867Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0408238102
Keywords
promoter; machine learning; gene transcription; acid pH
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Funding
- NIAID NIH HHS [AI49561, R01 AI049561] Funding Source: Medline
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Genetic and genomic approaches have been successfully used to assign genes to distinct regulatory networks. However, the present challenge of distinguishing differentially regulated genes within a network is particularly hard because members of a given network tend to have similar regulatory features. We have addressed this challenge by developing a method, termed Gene Promoter Scan, that discriminates coregulated promoters by simultaneously considering both multiple cis promoter features and gene expression. Here, we apply this method to probe the regulatory networks governed by the PhoP/PhoQ two-component system in the enteric bacteria Escherichia coli and Salmonella enterica. Our analysis uncovered members of the PhoP regulon and interactions with other regulatory systems that were not discovered in previous approaches. The predictions made by Gene Promoter Scan were experimentally validated to establish that the PhoP protein uses multiple mechanisms to control gene transcription, regulates acid resistance determinants, and is a central element in a highly connected network.
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