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1 Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, 1340 Jefferson Park Ave., Charlottesville, VA 22908, USA.
2 Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, 1340 Jefferson Park Ave., Charlottesville, VA 22908, USA. Electronic address: melissakendall@virginia.edu.
1 Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, 1340 Jefferson Park Ave., Charlottesville, VA 22908, USA.
2 Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, 1340 Jefferson Park Ave., Charlottesville, VA 22908, USA. Electronic address: melissakendall@virginia.edu.
Growth of a microorganism in a host is essential for infection, and bacterial pathogens have evolved to utilize specific metabolites to enhance replication in vivo. Now, emerging data demonstrate that pathogens rely on microbiota-derived metabolites as a form of bacterial-bacterial communication to gain information about location within a host and modify virulence gene expression accordingly. Thus, metabolite-sensing is critical for pathogens to establish infection. Here, we highlight recent examples of how the foodborne pathogen enterohemorrhagic Escherichia coli O157:H7 (EHEC) exploits microbiota-derived metabolites to recognize the host intestinal environment and control gene expression that results in controlled expression of virulence traits.
EHEC responds to microbiota-derived metabolites to activate complex regulatory cascades. EHEC senses ethanolamine,…
Figure 1
EHEC responds to microbiota-derived metabolites to activate complex regulatory cascades. EHEC senses ethanolamine, butyrate, and succinate to activate virulence gene expression, whereas the two-component system FusKR represses LEE expression in response to fucose. Ethanolamine is sensed through EutR as well as an unidentified ethanolamine sensor; butyrate is sensed through the transcription factor Lrp; succinate is sensed by Cra. Black lines indicate direct interaction, and grey hashed arrows indicate indirect regulation. For details, refer to main text.
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