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You have accessJournal of UrologyInfections/Inflammation/Cystic Disease of the Genitourinary Tract: Kidney however, it is unknown how urobiome composition is affected by the chemical environment of the urinary tract. Here, we use urine metabolomics and metagenomic sequencing of a controlled, cross-sectional cohort of postmenopausal women to identify urinary metabolites associated with rUTI susceptibility and urobiome taxonomic composition. METHODS: Clean catch midstream urine was collected from a cross-sectional cohort of postmenopausal women (n=75) divided into three groups based on rUTI history and current UTI status. We previously performed whole genome metagenomic sequencing (WGMS) of urine to yield urobiome taxonomic profiles. In matched samples, we performed targeted liquid chromatography mass spectrometry (LC-MS/MS) to profile urinary metabolites using the Biocrates Quant 500 assay on a Xevo TQ-S tandem quadrupole LC-MS/MS system (Waters). The Biocrates assay was performed per manufacturer's standard operating procedures using validated MRM transitions for the quantification of >600 analytes. The Wilcoxon rank sum test was used to screen differential metabolites between cohort groups. RESULTS: Significant differences in the urinary metabolome composition between women with no lifetime history of UTI and those presenting with an active, culture-confirmed rUTI were observed. Discriminating metabolites included a strong enrichment of putrescine and several ceramide and dihydroceramide species, including Cer(d18:2/16:0), Cer(d18:1/16:0), and Dh-Cer(d18:0/16:0), in active rUTI patients, while women with no history of UTI were enriched for dicarboxylic acids DiCA 14:0 and 12:0. We further identified discriminatory metabolic features enriched in urobiomes dominated by protective Lactobacillus species (>20% urobiome relative abundance), including 3 ceramides (d18:1/20:0, d18:2/20:0, and d18:1/20:0), cholesterol ester 14:0, 2 acylcarnitines (C16 and C14:1-OH), and Taurine. CONCLUSIONS: Here we present novel associations between the postmenopausal urobiome and urinary metabolites utilizing WGMS and targeted LC-MS/MS of >600 analytes. These metabolic associations may provide critical insight into metabolic interactions between the urinary environment and the resident microbiota as well as serve as biomarkers of urologic disease to be used in the development of new diagnostic platforms. Source of Funding: This work was supported by the Welch Foundation (AT- 2030-20200401) and the National Institutes of Health (1R01DK131267-01) to N.J.D. and (1F32DK128975-01A1) to M.L.N. This work was also supported by The Felicia and John Cain Distinguished Chair in Women's Health to P.E.Z © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e1118 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Michael L. Neugent More articles by this author Neha V. Hulyalkar More articles by this author Kevin C. Lutz More articles by this author Qiwei Li More articles by this author Philippe E. Zimmern More articles by this author Vladimir Shulaev More articles by this author Nicole J. De Nisco More articles by this author Expand All Advertisement PDF downloadLoading ...
Neugent et al. (Mon,) studied this question.