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Frontiers in Cellular and Infection Microbiology
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Article . 2019
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Two-Component Systems in Francisella Species

Authors: Monique L. van Hoek; Ky V. Hoang; Ky V. Hoang; John S. Gunn; John S. Gunn; John S. Gunn;

Two-Component Systems in Francisella Species

Abstract

Bacteria alter gene expression in response to changes in their environment through various mechanisms that include signal transduction systems. These signal transduction systems use membrane histidine kinase with sensing domains to mediate phosphotransfer to DNA-binding proteins that alter the level of gene expression. Such regulators are called two-component systems (TCSs). TCSs integrate external signals and information from stress pathways, central metabolism and other global regulators, thus playing an important role as part of the overall regulatory network. This review will focus on the knowledge of TCSs in the Gram-negative bacterium, Francisella tularensis, a biothreat agent with a wide range of potential hosts and a significant ability to cause disease. While TCSs have been well-studied in several bacterial pathogens, they have not been well-studied in non-model organisms, such as F. tularensis and its subspecies, whose canonical TCS content surprisingly ranges from few to none. Additionally, of those TCS genes present, many are orphan components, including KdpDE, QseC, QseB/PmrA, and an unnamed two-component system (FTN_1452/FTN_1453). We discuss recent advances in this field related to the role of TCSs in Francisella physiology and pathogenesis and compare the TCS genes present in human virulent versus. environmental species and subspecies of Francisella.

Keywords

Histidine Kinase, Virulence, sensor histidine kinase, response regulator, Gene Expression Regulation, Bacterial, Microbiology, QR1-502, QseB, DNA-Binding Proteins, QseC, Cellular and Infection Microbiology, Bacterial Proteins, Protein Domains, two-component system (TCS), Animals, Humans, Francisella, Francisella tularensis, Tularemia, Signal Transduction

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
Green
gold