<p>Recurrent urinary tract infections (rUTIs) are a major clinical challenge, and their increasing prevalence underscores the need to define host-microbiome interactions underlying susceptibility. How the urinary microbiota engages with the biochemical environment of the urogenital tract is yet to be fully defined. Here, we leverage paired metagenomic and quantitative metabolomic data to establish a microbe-metabolite association network of the female urinary microbiome and define metabolic signatures of rUTI. We observe unique metabolic networks of uropathogens and uroprotective species, highlighting potential metabolite-driven ecological shifts influencing rUTI susceptibility. We find distinct metabolites associated with urinary microbiome diversity and identify a lipid signature of active rUTI that accurately distinguishes our cases from controls. Finally, we identify deoxycholic acid as a prognostic indicator for UTI recurrence. Together, these findings provide insight into microbiome-metabolite interactions within the female urinary tract and highlight potential biomarkers for the development of new diagnostic tools to improve patient outcomes.</p>

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Urinary biochemical ecology reveals microbiome-metabolite interactions and metabolic markers of recurrent urinary tract infection

  • Michael L. Neugent,
  • Neha V. Hulyalkar,
  • Debasish Ghosh,
  • Ceejay N. Saenz,
  • Philippe E. Zimmern,
  • Vladimir Shulaev,
  • Nicole J. De Nisco

摘要

Recurrent urinary tract infections (rUTIs) are a major clinical challenge, and their increasing prevalence underscores the need to define host-microbiome interactions underlying susceptibility. How the urinary microbiota engages with the biochemical environment of the urogenital tract is yet to be fully defined. Here, we leverage paired metagenomic and quantitative metabolomic data to establish a microbe-metabolite association network of the female urinary microbiome and define metabolic signatures of rUTI. We observe unique metabolic networks of uropathogens and uroprotective species, highlighting potential metabolite-driven ecological shifts influencing rUTI susceptibility. We find distinct metabolites associated with urinary microbiome diversity and identify a lipid signature of active rUTI that accurately distinguishes our cases from controls. Finally, we identify deoxycholic acid as a prognostic indicator for UTI recurrence. Together, these findings provide insight into microbiome-metabolite interactions within the female urinary tract and highlight potential biomarkers for the development of new diagnostic tools to improve patient outcomes.