Dynamics of the Urinary Bacterial Microbiota

Overview

Urinary tract infections (UTIs) are one of the most common bacterial infections in humans (Flores-Mireles et al., 2015). They rank first among healthcare-associated infections (Daniau et al., 2020) and second among community-acquired infections. Their diagnosis is based on the presence of urinary symptoms, confirmed by performing a urine culture culture (UCEC), which consists of collecting the patient's bladder urine. Urine samples are generally considered sterile when they do not allow the identification of uropathogenic bacteria using standard clinical culture procedures (Caron et al., 2018). However, conventional urine culture has low sensitivity, with the rate of positive urine cultures in patients with acute cystitis being estimated at 60% (Schmiemann et al., 2010). It is now established that urine has its own microbiota, that is, a set of microorganisms residing in the bladder, most of which are not cultivable under conventional laboratory conditions. The relationship between the dynamics of urinary microbiota composition and the pathobiology of UTIs is beginning to be studied in humans (Neugent et al., 2020). Price et al. analyzed the urine of women with UTI symptoms using EQUC culture, compared to a symptom-free control group (Price et al., 2016). More precise identification of cultured bacteria revealed the presence of bacteria that were not detected using conventional culture (such as Lactobacillus iners, Gardnerella vaginalis, Prevotella sp., and Aerococcus urinae). In addition, sequencing allowed the characterization of polymicrobial communities, present in many of the samples analyzed. These findings have led to a significant revision of the traditional perception of UTIs. It has thus been suggested that, following a disruption in the homeostasis of the urinary microbiota (urinary dysbiosis), certain bacteria considered commensals of the urinary tract can become pathogenic and lead to UTIs (Gerges-Knafl et al., 2020).

Metabolomics allows the study of an individual's metabolic profile. It provides valuable insights into the complex interplay between biology, environment, and lifestyle. Metabolites present in urine could provide unique insights into the pathogenesis of infections, including the host's immune response and the metabolic pathways of the infecting pathogen. Furthermore, integrating urinary metabolomics with other "omics" technologies, such as microbiome, offers a more comprehensive view of the complex interactions that occur during an infection. Existing studies of the urinary microbiome are primarily retrospective, conducted on small patient populations, and with little medical data collected. This study therefore proposes to prospectively enroll 150 subjects (50 patients with proven UTI and 100 healthy volunteers) to study their bacterial urinary microbiota using EQUC and NGS techniques, compared to standard culture results. In addition, precise medical metadata will be collected prospectively and compared with microbiota data. The research hypothesis is that the composition of the bacterial urinary microbiota differs between patients with clinically proven UTI and those without UTI. This study will also test other secondary hypotheses, including: * That certain bacterial species present in the urine of adult women are not routinely detected using standard culture conditions. * That certain bacterial species in the urinary microbiota are not cultivable and are detectable only by NGS. * That patients with clinically proven UTI have a lower diversity and less richness of the bacterial urinary microbiota compared to patients without UTI. * That host factors are associated with microbial signatures. * That the urinary metabolome of patients with UTI is different from that of healthy volunteers