ArticlebioRxiv : the preprint server for biology2026
Optimized Urine Metagenomic Methods Reveal Longitudinal Microbial Community Dynamics and Predictors of Transition from Asymptomatic Colonization to CAUTI.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Urinary tract infections (UTIs) rank among the most common infections globally, with many linked to indwelling urinary catheters. Our prior culture-based longitudinal evaluation of long-term catheterized nursing home residents revealed persistent asymptomatic colonization by pathogens and demonstrated that CAUTI onset was not necessarily due to new pathogen acquisition. In this study, we optimized metagenomics methods to examine the ecological structure underlying persistent colonization and the transition to infection. Results: We present a comprehensive longitudinal metagenomic analysis of catheterized urine specimens, revealing colonization dynamics of 69 microbial species across 198 samples from 9 individuals. Descriptive ecological metrics were combined with Bayesian mixed-effects models that accounted for repeated within-participant sampling to identify clusters of co-occurring species, determine the impact of perturbations such as antibiotic exposure and catheter changes on community structure, and identify taxa predictive of infection sign and symptom onset. Longitudinal specimens clustered into three main ecological phenotypes: 1) moderate diversity, unstable communities (3 participants); 2) high diversity, stable communities that resisted disruption even after multiple catheter changes (3 participants); and 3) low diversity, pathogen-dominated communities (3 participants). Catheter changes alone did not significantly disrupt community composition, while antibiotic exposures induced major shifts often followed by re-colonization with the same genera within subsequent weeks. Six clusters of species were identified for which relative abundances correlated across perturbations to the microbial community, including a mutually exclusive Enterobacterales cluster and fastidious-anaerobe group cluster. 24 species were found to correlate with onset of signs and symptoms of infection, 11 of which were missed by standard urine culture. Conclusions: The catheterized urinary tract represents a novel ecosystem that is resilient to disruption by catheter changes but susceptible to antibiotic perturbation. Antibiotic exposure did deplete all species associated with signs and symptoms but also depleted potentially benign microbes. Our findings have direct implications for catheter management protocols and antibiotic stewardship in long-term catheterized patients. Prospective evaluation using this framework in a larger cohort can help translate these ecological insights into clinical decision-making tools.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.