Gut microbiome correlates of recurrent urinary tract infection: a longitudinal, multi-center study

Abstract

Background: Urinary tract infections (UTI) affect approximately 250 million people annually worldwide. Patients often experience a cycle of antimicrobial treatment and recurrent UTI (rUTI) that is thought to be facilitated by a gut reservoir of uropathogenic Escherichia coli (UPEC).

Methods: 125 patients with UTI caused by an antibiotic-resistant organism (ARO) were enrolled from July 2016 to May 2019 in a longitudinal, multi-center cohort study. Multivariate statistical models were used to assess the relationship between uropathogen colonization and recurrent UTI (rUTI), controlling for clinical characteristics. 644 stool samples and 895 UPEC isolates were interrogated for taxonomic composition, antimicrobial resistance genes, and phenotypic resistance. Cohort UTI gut microbiome profiles were compared against published healthy and UTI reference microbiomes, as well as assessed within-cohort for timepoint- and recurrence-specific differences.

Findings: Risk of rUTI was not independently associated with clinical characteristics. The UTI gut microbiome was distinct from healthy reference microbiomes in both taxonomic composition and antimicrobial resistance gene (ARG) burden, with 11 differentially abundant taxa at the genus level. rUTI and non-rUTI gut microbiomes in the cohort did not generally differ, but gut microbiomes from urinary tract colonized patients were elevated in E. coli abundance 7-14 days post-antimicrobial treatment. Corresponding UPEC gut isolates from urinary tract colonizing lineages showed elevated phenotypic resistance against 11 of 23 tested drugs compared to non-colonizing lineages.

Interpretation: The gut microbiome is implicated in UPEC urinary tract colonization during rUTI, serving as an ARG-enriched reservoir for UPEC. UPEC can asymptomatically colonize the gut and urinary tract, and post-antimicrobial blooms of gut E. coli among urinary tract colonized patients suggest that cross-habitat migration of UPEC is an important mechanism of rUTI. Thus, treatment duration and UPEC populations in both the urinary and gastrointestinal tract should be considered in treating rUTI and developing novel therapeutics.

Funding: This work was supported in part by awards from the U.S. Centers for Disease Control and Prevention Epicenter Prevention Program (grant U54CK000482; principal investigator, V.J.F.); to J.H.K. from the Longer Life Foundation (an RGA/Washington University partnership), the National Center for Advancing Translational Sciences (grants KL2TR002346 and UL1TR002345), and the National Institute of Allergy and Infectious Diseases (NIAID) (grant K23A1137321) of the National Institutes of Health (NIH); and to G.D. from NIAID (grant R01AI123394) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant R01HD092414) of NIH. R.T.'s research was funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation; grant 402733540). REDCap is Supported by Clinical and Translational Science Award (CTSA) Grant UL1 TR002345 and Siteman Comprehensive Cancer Center and NCI Cancer Center Support Grant P30 CA091842. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

Keywords: Antimicrobial resistance; Escherichia coli; Gut microbiome; Recurrent urinary tract infection.

Fig. 1

Study overview. (A) A cohort of 125 patients with UTI were enrolled from four hospital centers in the US. Questionnaires regarding UTI symptoms were collected at time of hospital visit. Stool and urine samples were collected from diagnosis (DxU) to enrollment (E) to 6 months after end of antibiotic treatment for UTI (180 d). Patients experiencing multiple episodes of UTI (rUTI) re-started the follow-up period beginning with another DxU sample. Stool and Urine samples were plated for selective culture, sequenced, and tested for antibiotic susceptibility. 644 stool samples from 106 patients were further subject to metagenomic sequencing. (B) Flow chart illustrating cohort context and samples utilized in previous and current analyses.

Fig. 2

Comparison of microbiomes between healthy and UTI individuals. 20 published microbiomes from a healthy humans study (HH), and 31 published microbiomes from an rUTI study (UMB) were included for cross-cohort comparisons with our samples (STL). (A) Richness is higher in healthy microbiomes compared to UTI (Kruskal–Wallis, P = 0.055). Box indicates first and third quartiles, and whiskers extend to data within 1.5 times the interquartile range (IQR). Line in box indicates median. Datapoints beyond 1.5 times IQR are considered outliers. (B) Microbiomes were significantly different by study (PERMAOMVA, P = 0.001) but (C) Healthy and UTI microbiomes were significantly different even after accounting for study effect (PERMANOVA, P = 0.043). (D) Differentially abundant taxa at the genus level were identified using MaAsLin2. Green and upwards pointing triangles signify taxa enriched in healthy microbiomes, while red and downwards pointing arrows signify taxa enriched in UTI individuals. X-axis denotes the false discovery rate (FDR), and Y-axis shows relative abundance. (E) UTI microbiomes had higher numbers of antimicrobial resistance genes (ARGs) as identified by ShortBRED (Kruskal–Wallis, P = 0.0023). X-axis shows healthy or UTI groups, while Y-axis indicates the number of ARG hits as measured by Reads Per Kilobase of reference sequence per Million sample reads (RPKM). (F) Richness of ARGs was not significantly different between the two groups (Kruskal–Wallis, P = 0.087).

Fig. 3

Urinary tract colonization corresponds to significant differences in gut microbiome at days 7–14 post-abx. (A) Taxonomic compositions of microbiome samples from days 7–14 post-abx were significantly different between urinary tract colonized (Ucol) and non-colonized patients (non-Ucol), even after accounting for age and treatment drug (PERMANOVA, P < 0.05, n = 96). (B and C) MaAsLin2 identified two taxa to be differentially abundant in Ucol patients: Escherichia coli and Paraprevotella xylaniphila. Box indicates first and third quartiles, and whiskers extend to data within 1.5 times the interquartile range (IQR). Line in box indicates median. Datapoints beyond 1.5 times IQR are considered outliers. (D) Ucol patients experience E. coli ‘’blooms' in gut as measured by relative abundance. X-axis corresponds to sampling timepoint (S1: enrollment; S2: end of abx; S3: day3 post-abx; S4: day7; S5: day14; S6: day30; S7: day60; S8: day90; S11: day180). Y-axis rows and bubble colors correspond to patient ID, bubble size denotes relative abundance. Empty circles show 0.00% relative abundance in a sequenced sample. (E) Bacteroides xylanisolvens was the singular differentiating taxon between Ucol patients with recurrence, and Ucol patients without. (F) Firth’s penalized likelihood logistic regression of AST results found gut isolates from Ucol lineages to be enriched in resistance for 11 of 23 tested drugs. Gut isolates from non-Ucol lineages were enriched in resistance to imipenem and meropenem. Circles indicate the odds ratio, while lines show the 95% confidence interval. Bars on the right show the percent of isolates from each group that are resistant to each drug. (G) Ucol gut isolates were significantly higher in AST score compared to non-Ucol gut isolates. Lines in violin plots show quartiles of distribution for each group. (H) Corresponding urinary isolates were not significantly different in AST score between Ucol and non-Ucol groups.