mSystems (Aug 2020)

Microbe-Metabolite Associations Linked to the Rebounding Murine Gut Microbiome Postcolonization with Vancomycin-Resistant <named-content content-type="genus-species">Enterococcus faecium</named-content>

  • Andre Mu,
  • Glen P. Carter,
  • Lucy Li,
  • Nicole S. Isles,
  • Alison F. Vrbanac,
  • James T. Morton,
  • Alan K. Jarmusch,
  • David P. De Souza,
  • Vinod K. Narayana,
  • Komal Kanojia,
  • Brunda Nijagal,
  • Malcolm J. McConville,
  • Rob Knight,
  • Benjamin P. Howden,
  • Timothy P. Stinear

DOI
https://doi.org/10.1128/mSystems.00452-20
Journal volume & issue
Vol. 5, no. 4

Abstract

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ABSTRACT Vancomycin-resistant Enterococcus faecium (VREfm) is an emerging antibiotic-resistant pathogen. Strain-level investigations are beginning to reveal the molecular mechanisms used by VREfm to colonize regions of the human bowel. However, the role of commensal bacteria during VREfm colonization, in particular following antibiotic treatment, remains largely unknown. We employed amplicon 16S rRNA gene sequencing and metabolomics in a murine model system to try and investigate functional roles of the gut microbiome during VREfm colonization. First-order taxonomic shifts between Bacteroidetes and Tenericutes within the gut microbial community composition were detected both in response to pretreatment using ceftriaxone and to subsequent VREfm challenge. Using neural networking approaches to find cooccurrence profiles of bacteria and metabolites, we detected key metabolome features associated with butyric acid during and after VREfm colonization. These metabolite features were associated with Bacteroides, indicative of a transition toward a preantibiotic naive microbiome. This study shows the impacts of antibiotics on the gut ecosystem and the progression of the microbiome in response to colonization with VREfm. Our results offer insights toward identifying potential nonantibiotic alternatives to eliminate VREfm through metabolic reengineering to preferentially select for Bacteroides. IMPORTANCE This study demonstrates the importance and power of linking bacterial composition profiling with metabolomics to find the interactions between commensal gut bacteria and a specific pathogen. Knowledge from this research will inform gut microbiome engineering strategies, with the aim of translating observations from animal models to human-relevant therapeutic applications.

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