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Severe infections emerge from commensal bacteria by adaptive evolution.

ABSTRACT: Bacteria responsible for the greatest global mortality colonize the human microbiota far more frequently than they cause severe infections. Whether mutation and selection among commensal bacteria are associated with infection is unknown. We investigated de novo mutation in 1163 Staphylococcus aureus genomes from 105 infected patients with nose colonization. We report that 72% of infections emerged from the nose, with infecting and nose-colonizing bacteria showing parallel adaptive differences. We found 2.8-to-3.6-fold adaptive enrichments of protein-altering variants in genes responding to rsp, which regulates surface antigens and toxin production; agr, which regulates quorum-sensing, toxin production and abscess formation; and host-derived antimicrobial peptides. Adaptive mutations in pathogenesis-associated genes were 3.1-fold enriched in infecting but not nose-colonizing bacteria. None of these signatures were observed in healthy carriers nor at the species-level, suggesting infection-associated, short-term, within-host selection pressures. Our results show that signatures of spontaneous adaptive evolution are specifically associated with infection, raising new possibilities for diagnosis and treatment.

SUBMITTER: Young BC

PROVIDER: S-EPMC5736351 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Severe infections emerge from commensal bacteria by adaptive evolution.

Young Bernadette C BC Wu Chieh-Hsi CH Gordon N Claire NC Cole Kevin K Price James R JR Liu Elian E Sheppard Anna E AE Perera Sanuki S Charlesworth Jane J Golubchik Tanya T Iqbal Zamin Z Bowden Rory R Massey Ruth C RC Paul John J Crook Derrick W DW Peto Timothy E TE Walker A Sarah AS Llewelyn Martin J MJ Wyllie David H DH Wilson Daniel J DJ

eLife 20171219

Bacteria responsible for the greatest global mortality colonize the human microbiota far more frequently than they cause severe infections. Whether mutation and selection among commensal bacteria are associated with infection is unknown. We investigated de novo mutation in 1163 <i>Staphylococcus aureus</i> genomes from 105 infected patients with nose colonization. We report that 72% of infections emerged from the nose, with infecting and nose-colonizing bacteria showing parallel adaptive differe ...[more]

PMID: 29256859

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Project description:Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances.

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Severe infections emerge from commensal bacteria by adaptive evolution.

Publications

Severe infections emerge from commensal bacteria by adaptive evolution.

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