BackgroundClinical dogma is that healthy urine is sterile and the presence of bacteria with an inflammatory response is indicative of urinary tract infection (UTI). Asymptomatic bacteriuria (ABU) represents the state in which bacteria are present but the inflammatory response is negligible. Differentiating ABU from UTI is diagnostically challenging, but critical because overtreatment of ABU can perpetuate antimicrobial resistance while undertreatment of UTI can result in increased morbidity and mortality. In this study, we describe key characteristics of the healthy and ABU urine microbiomes utilizing 16S rRNA gene (16S rDNA) sequencing and metaproteomics, with the future goal of utilizing this information to personalize the treatment of UTI based on key individual characteristics.MethodsA cross-sectional study of 26 healthy controls and 27 healthy subjects at risk for ABU due to spinal cord injury-related neuropathic bladder (NB) was conducted. Of the 27 subjects with NB, 8 voided normally, 8 utilized intermittent catheterization, and 11 utilized indwelling Foley urethral catheterization for bladder drainage. Urine was obtained by clean catch in voiders, or directly from the catheter in subjects utilizing catheters. Urinalysis, urine culture and 16S rDNA sequencing were performed on all samples, with metaproteomic analysis performed on a subsample.ResultsA total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline. Urine microbiomes differ by normal bladder function vs. NB, gender, type of bladder catheter utilized, and duration of NB. The top ten bacterial taxa showing the most relative abundance and change among samples were Lactobacillales, Enterobacteriales, Actinomycetales, Bacillales, Clostridiales, Bacteroidales, Burkholderiales, Pseudomonadales, Bifidobacteriales and Coriobacteriales. Metaproteomics confirmed the 16S rDNA results, and functional human protein-pathogen interactions were noted in subjects where host defenses were initiated.ConclusionsCounter to clinical belief, healthy urine is not sterile. The healthy urine microbiome is characterized by a preponderance of Lactobacillales in women and Corynebacterium in men. The presence and duration of NB and method of urinary catheterization alter the healthy urine microbiome. An integrated approach of 16S rDNA sequencing with metaproteomics improves our understanding of healthy urine and facilitates a more personalized approach to prevention and treatment of infection.

OBJECTIVES: To identify risk factors for recurrent urinary tract infection (UTI) and renal scarring in children who have had 1 or 2 febrile or symptomatic UTIs and received no antimicrobial prophylaxis.METHODS: This 2-year, multisite prospective cohort study included 305 children aged 2 to 71 months with vesicoureteral reflux (VUR) receiving placebo in the RIVUR (Randomized Intervention for Vesicoureteral Reflux) study and 195 children with no VUR observed in the CUTIE (Careful Urinary Tract Infection Evaluation) study. Primary exposure was presence of VUR; secondary exposures included bladder and bowel dysfunction (BBD), age, and race. Outcomes were recurrent febrile or symptomatic urinary tract infection ( F/S UTI) and renal scarring.RESULTS: Children with VUR had higher 2-year rates of recurrent F/S UTI (Kaplan-Meier estimate 25.4% compared with 17.3% for VUR and no VUR, respectively). Other factors associated with recurrent CONCLUSIONS: VUR and BBD are risk factors for recurrent UTI, especially when they appear in combination. Strategies for preventing recurrent UTI include antimicrobial prophylaxis and treatment of BBD. WHAT'S KNOWN ON THIS SUBJECT:Vesicoureteral reflux is recognized as an important risk factor for recurrent urinary tract infection and renal scarring. Less is known about the contribution of other risk factors to these outcomes. WHAT THIS STUDY ADDS:This study found that information about vesicoureteral reflux and bladder and bowel dysfunction can be used to identify children at low, medium, and high risk of recurrent urinary tract infection, information that clinicians could use to select children for specific preventive therapies.

No abstract

Patients at risk for developing nosocomial infection can be identified using a multivariate logistic regression model with a high degree of sensitivity and specificity. These data indicate that institutional nosocomial rates need to be adjusted for risk factors. This model could help target patients at high risk for developing nosocomial infections for preventive strategies.