Two-Component Signal Transduction System in 10,000 E. coli and Salmonella Genomes

By March 21, 2017Posters

Duah Alkam, Visanu Wanchai, David Ussery

Background: Bacteria have the astounding ability to withstand, survive and even thrive in diverse environments. Response to different environments is mediated in part by Two-Component Signal Transduction Systems (TCST) which are composed of a transmembrane sensor histidine kinase and an intracellular response regulator. The sensor histidine kinase transmits extracellular cues downstream to the response regulator which effects intracellular changes (usually modifications in gene expression) which enable the cell to adapt to the environment. For example, the E. coli BarA-UvrY two-component system is needed for switching between glycolytic and gluconeogenic pathways. Thus two-component systems are essential to bacterial survival.

Results: We used protein functional domains to identify two-component systems in 5,305 genomes of Escherichia coli and 5,177 genomes of Salmonella enterica. We first identified 29 known histidine kinases and 31 known response regulators in the E. coli K-12 MG1655 reference genome, and 30 histidine kinases and 37 response regulators in the S. enterica subsp. enterica serovar Typhimurium LT2 reference genome. We then used the Pfam domains of these proteins to identify matching and novel proteins in the E. coli and S. enterica genomes. We found that a range of 30 to 35 histidine kinases and 35 to 40 response regulators are present across the E. coli genomes, in S. enterica we found a range of 30 to 37 histidine kinases and 35 to 42 response regulators.

Conclusion: Here we introduce a method to swiftly compare thousands of genomes by using protein functional domains. Using this computational approach, within a few seconds, we extracted the total number of two-component systems across roughly 5,000 genomes of each E. coli and S. enterica. We show that, by using protein functional domains, it will be possible to compare proteins of all bacteria within seconds. This work is funded in part from the Arkansas Research Alliance and the Helen Adams & Arkansas Research Alliance Professor & Chair.

Arkansas Center for Genomic Epidemiology & Medicine and The Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205

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