Mycoplasma and Ureaplasma Molecular Testing Does Not Correlate with Irritative or Painful Lower Urinary Tract Symptoms.

PURPOSE: For patients with persistent irritative lower urinary tract symptoms, such as dysuria and urinary frequency, evaluation for the atypical organisms Ureaplasma and Mycoplasma has been a common part of care. However, these species are genitourinary colonizers and have not been established as causative pathogens in chronic lower urinary tract symptoms. We therefore sought to evaluate diagnostic testing patterns for Ureaplasma and Mycoplasma and characterize the associations of these bacteria with irritative lower urinary tract symptoms using molecular detection techniques. MATERIALS AND METHODS: Ureaplasma/Mycoplasma testing patterns for 2019 were assessed using an anonymized data repository. Clean catch urine specimens (179) were collected prospectively from female and male patients with and without irritative lower urinary tract symptoms. Quantitative polymerase chain reaction evaluated urinary Ureaplasma and Mycoplasma DNA concentrations, while next-generation sequencing assessed the relative abundance of Ureaplasma and Mycoplasma within the urinary bacterial population. RESULTS: Ureaplasma/Mycoplasma testing was common, with 575 tests performed in 2019 in our community hospital system. In our cohort, Ureaplasma and Mycoplasma were identified in similar proportions in symptomatic and asymptomatic subjects: 25% of female controls and 27% of females with lower urinary tract symptoms and 9.5% of asymptomatic males and 3.3% of men with symptoms (p=0.87 and p=0.91 for females and males, respectively). Regression analysis revealed that both abundance and concentrations of Mycoplasmataceae correlated negatively with a range of irritative lower urinary tract symptoms, including dysuria and urethral pain. CONCLUSIONS: A statistically significant negative correlation of Ureaplasma/Mycoplasma levels with a variety of lower urinary tract symptoms suggests that polymerase chain reaction-based Mycoplasmataceae detection has little diagnostic benefit in assessment of chronic irritative urinary symptoms.

Unsupervised Machine Learning Approaches Reveal Distinct Phenotypes of Perceived Bladder Pain: A Pilot Study.

Interstitial cystitis/bladder pain syndrome (IC/BPS) is defined as an unpleasant sensation perceived to be related to the bladder with associated urinary symptoms. Due to difficulties discriminating pelvic visceral sensation, IC/BPS likely represents multiple phenotypes with different etiologies that present with overlapping symptomatic manifestations, which complicates clinical management. We hypothesized that unique bladder pain phenotypes or "symptomatic clusters" would be identifiable using machine learning analysis (unsupervised clustering) of validated patient-reported urinary and pain measures. Patients (n = 145) with pelvic pain/discomfort perceived to originate in the bladder and lower urinary tract symptoms answered validated questionnaires [OAB Questionnaire (OAB-q), O'Leary-Sant Indices (ICSI/ICPI), female Genitourinary Pain Index (fGUPI), and Pelvic Floor Disability Index (PFDI)]. In comparison to asymptomatic controls (n = 69), machine learning revealed three bladder pain phenotypes with unique, salient features. The first group chiefly describes urinary frequency and pain with the voiding cycle, in which bladder filling causes pain relieved by bladder emptying. The second group has fluctuating pelvic discomfort and straining to void, urinary frequency and urgency without incontinence, and a sensation of incomplete emptying without urinary retention. Pain in the third group was not associated with voiding, instead being more constant and focused on the urethra and vagina. While not utilized as a feature for clustering, subjects in the second and third groups were significantly younger than subjects in the first group and controls without pain. These phenotypes defined more homogeneous patient subgroups which responded to different therapies on chart review. Current approaches to the management of heterogenous populations of bladder pain patients are often ineffective, discouraging both patients and providers. The granularity of individual phenotypes provided by unsupervised clustering approaches can be exploited to help objectively define more homogeneous patient subgroups. Better differentiation of unique phenotypes within the larger group of pelvic pain patients is needed to move toward improvements in care and a better understanding of the etiologies of these painful symptoms.

Optimization of DNA extraction from human urinary samples for mycobiome community profiling.

INTRODUCTION: Recent data suggest the urinary tract hosts a microbial community of varying composition, even in the absence of infection. Culture-independent methodologies, such as next-generation sequencing of conserved ribosomal DNA sequences, provide an expansive look at these communities, identifying both common commensals and fastidious organisms. A fundamental challenge has been the isolation of DNA representative of the entire resident microbial community, including fungi. MATERIALS AND METHODS: We evaluated multiple modifications of commonly-used DNA extraction procedures using standardized male and female urine samples, comparing resulting overall, fungal and bacterial DNA yields by quantitative PCR. After identifying protocol modifications that increased DNA yields (lyticase/lysozyme digestion, bead beating, boil/freeze cycles, proteinase K treatment, and carrier DNA use), all modifications were combined for systematic confirmation of optimal protocol conditions. This optimized protocol was tested against commercially available methodologies to compare overall and microbial DNA yields, community representation and diversity by next-generation sequencing (NGS). RESULTS: Overall and fungal-specific DNA yields from standardized urine samples demonstrated that microbial abundances differed significantly among the eight methods used. Methodologies that included multiple disruption steps, including enzymatic, mechanical, and thermal disruption and proteinase digestion, particularly in combination with small volume processing and pooling steps, provided more comprehensive representation of the range of bacterial and fungal species. Concentration of larger volume urine specimens at low speed centrifugation proved highly effective, increasing resulting DNA levels and providing greater microbial representation and diversity. CONCLUSIONS: Alterations in the methodology of urine storage, preparation, and DNA processing improve microbial community profiling using culture-independent sequencing methods. Our optimized protocol for DNA extraction from urine samples provided improved fungal community representation. Use of this technique resulted in equivalent representation of the bacterial populations as well, making this a useful technique for the concurrent evaluation of bacterial and fungal populations by NGS.