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Split Histidine Kinases Enable Ultrasensitivity and Bistability in Two-Component Signaling Networks

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Split Histidine Kinases Enable Ultrasensitivity and Bistability in Two-Component Signaling Networks
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002949
Pubmed ID
Authors

Munia Amin, Steven L. Porter, Orkun S. Soyer

Abstract

Bacteria sense and respond to their environment through signaling cascades generally referred to as two-component signaling networks. These networks comprise histidine kinases and their cognate response regulators. Histidine kinases have a number of biochemical activities: ATP binding, autophosphorylation, the ability to act as a phosphodonor for their response regulators, and in many cases the ability to catalyze the hydrolytic dephosphorylation of their response regulator. Here, we explore the functional role of "split kinases" where the ATP binding and phosphotransfer activities of a conventional histidine kinase are split onto two distinct proteins that form a complex. We find that this unusual configuration can enable ultrasensitivity and bistability in the signal-response relationship of the resulting system. These dynamics are displayed under a wide parameter range but only when specific biochemical requirements are met. We experimentally show that one of these requirements, namely segregation of the phosphatase activity predominantly onto the free form of one of the proteins making up the split kinase, is met in Rhodobacter sphaeroides. These findings indicate split kinases as a bacterial alternative for enabling ultrasensitivity and bistability in signaling networks. Genomic analyses reveal that up 1.7% of all identified histidine kinases have the potential to be split and bifunctional.

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The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Mexico 1 3%
United States 1 3%
Unknown 32 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 37%
Student > Ph. D. Student 9 26%
Student > Master 4 11%
Student > Bachelor 4 11%
Student > Doctoral Student 1 3%
Other 2 6%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 51%
Biochemistry, Genetics and Molecular Biology 6 17%
Engineering 2 6%
Mathematics 1 3%
Computer Science 1 3%
Other 5 14%
Unknown 2 6%