The clinical implications of bacterial pathogenesis and mucosal immunity in chronic urinary tract infection

Evaluation of phylogroup, sequence type, resistome and virulome in Escherichia coli resulting in feline bacterial cystitis and subclinical bacteriuria

There is limited information on E. coli from feline urine and whether associated virulence and antimicrobial resistance patterns contribute to disease manifestations. This study aimed to characterise E. coli isolates, sequence types (ST), antimicrobial resistance (ARG) and virulence associated genes (VAG) from cats in primary care with subclinical bacteriuria (SBU) or lower urinary tract infection (LUTI). Whole genome sequencing (WGS) was performed on E. coli isolates that had been stored from a longitudinal health monitoring programme. Clinical records were reviewed to determine underlying disease conditions, phenotypic susceptibility and SBU and LUTI status. Descriptive review of phylogroup and ST was assessed together with evaluation of ARG and VAG by ST and based on SBU or LUTI status. WGS data was available for 152 E. coli isolates from cats (n = 26 with LUTI, n = 126 with SBU). The most common phylogroup was B2 with ST73, ST80, ST83 and ST127 predominating and ST80 being associated with clinical LUTI. Evaluating all isolates, there was no difference in prevalence of MDR status, total VAG or ARG count from cats with SBU or LUTI. Exploring individual VAG, ibeA, an invasin, and kpsT, part of the group 2 polysaccharide capsule, were associated with LUTI whilst P-fimbrial genes (pap) were associated with SBU. Based on this study, evidence is limited that expression of LUTI is directly related to ST or virulome and there is no evidence for increased resistome with SBU. However, low prevalence of cats with clinical LUTI may have precluded identification of associations.

Microbiologist in the Clinic: Antibiotic Dependent in her 30 s

In this third episode of the Microbiologist in the Clinic series, clinicians and laboratory scientists share their perspectives about a 32 y/o female who has become antibiotic-dependent for her urinary symptoms. Despite escalating methods of antibiotic administration, the patient has persistent and recurrent "UTI" symptoms. Extensive testing has not provided guidance for her treating clinicians. The challenges of this clinical presentation are discussed with evidence for evaluation and treatment.

Novel Techniques to Unravel Causative Bacterial Ecological Shifts in Chronic Urinary Tract Infection

Chronic urinary tract infection (UTI) presents with protracted lower urinary tract symptoms and elevated urinary leukocyte counts, but its bacterial etiological agents remain obscure. In this cross-sectional investigation, we aimed to unravel the role of the bladder microbiota in chronic UTI pathogenesis by studying the host immune response. Urine samples were collected from healthy controls (HT), chronic UTI patients who had not initiated treatment (PT) and those undergoing treatment (OT), then sorted into white blood cell (WBC) and epithelial cell (EPC) fractions. Bacteria associated with both fractions were identified by chromogenic agar culture coupled with mass spectrometry and 16S rRNA sequencing. Distinct WBC-exclusive bacteria were observed in the healthy population, but this pattern was less obvious in patients, plausibly due to epithelial shedding and breaching of the urothelial barrier. We also described a bacterial fingerprint guided by Escherichia that was able to stratify patients based on symptom severity. Clustering analyses of mean rank changes revealed highly statistically significant upward and downward ecological shifts in communities of bacteria between the healthy and diseased populations. Interestingly, many of the most abundant genera identified in sequencing remained stable when compared between the study cohorts. We concluded that reshuffling of the urinary microbiome, rather than the activity of a single known urinary pathogen, could drive chronic UTI.

Asymptomatic bacteriuria and its associated fetomaternal outcomes among pregnant women delivering at Bugando Medical Centre in Mwanza, Tanzania

BACKGROUND

Asymptomatic bacteriuria (ASB) affects 23.9% of pregnant women globally and, if left untreated, can lead to adverse fetomaternal outcomes. In Tanzania, ASB prevalence has ranged from 13% to 17% over the past decade. Yet, its impact on fetomaternal outcomes remains unexplored, hindering the development of screening strategies, antimicrobial therapies, and preventive measures for this vulnerable population.

METHODS

A cross-sectional analytical study was conducted on 1,093 pregnant women admitted for delivery at Bugando Medical Center (BMC) in Mwanza, Tanzania, from July to December 2022. Socio-demographic, obstetric, and clinical data were collected from the women, along with mid-stream urine samples for analysis. Fetomaternal outcomes were assessed within 72 hours after delivery.

RESULTS

The median age of participants was 29 years (range: 15-45 years). ASB prevalence among pregnant women was 16.9% (185/1093), with a 95% CI of 14.6-19.3%. Risk factors for ASB included anemia (OR: 5.3; 95% CI = 3.7-8.2, p-value <0.001) and a history of antenatal care admission (OR 4.2; 95% CI = 2.9-6.1, p-value <0.001). Among all participants, 82 (7.5%), 65 (5.9%), 49 (4.5%), and 79 (7.2%) experienced pre-term labor (PTL), premature rupture of membrane (PROM), preeclampsia, and delivered newborns with low birthweight (LBW), respectively. Among the 185 patients with ASB, the respective proportions of PTL, PROM, preeclampsia, and LBW were 25.4%, 17.3%, 9.2%, and 12.4%. Multivariable logistic regression analysis revealed significant associations between ASB and PTL [OR (95% CI): 8.8 (5.5-14.5); p-value <0.001], PROM [OR (95% CI): 4.5 (2.5-8.0); p-value <0.001], and LBW [OR (95% CI): 2.0 (1.2-3.5); p-value = 0.011]. Escherichia coli (50.8%) and Klebsiella pneumoniae (14.05%) were the most common pathogens, with low resistance rates to nitrofurantoin, amoxicillin-clavulanate, and cephalosporins-antibiotics considered safe during pregnancy-ranging from 8.2% to 31.0%.

CONCLUSION

The prevalence of ASB among pregnant women in Tanzania remains high and is associated with adverse fetomaternal outcomes. Integrating routine urine culture screening for all pregnant women, irrespective of symptoms, and providing specific antimicrobial therapies during antenatal care can help prevent adverse pregnancy outcomes.

Case reports of immune-related cystitis and the antibody combination hypothesis

Immune-related cystitis is a rare condition, and its diagnostic criteria and pathogenesis are not yet fully understood. Here, we report two cases of immune-related cystitis. Both patients were previously diagnosed with lung squamous cell carcinoma and received combined treatment with immune checkpoint inhibitors and chemotherapy, leading to hemorrhagic cystitis. We reviewed the cystoscopic images and pathological features of previous cases and found that autoantibodies against hemidesmosomes may be the cause of immune-related cystitis, proposing the "antibody combination" hypothesis to explain the tissue specificity of the condition.

Microbiologist in the Clinic: Postmenopausal Woman with Chronic OAB and Positive Urine Culture

In this second episode of the Microbiologist in the Clinic series, clinicians and laboratory scientists share their perspectives about a 75-year-old woman who was diagnosed with asymptomatic bacteriuria based on positive urine cultures. The patient and her GP are concerned about this laboratory finding as the patient will become immunosuppressed with planned chemotherapy. The patient has had an overactive bladder (OAB) for approximately 20 years, with good control of her urinary urgency and frequency (no incontinence) with a stable dose of OAB medication. The challenges of this clinical presentation are discussed, with evidence for evaluation and treatment.

Epidemiological insights into seasonal, sex‑specific and age‑related distribution of bacterial pathogens in urinary tract infections

Urinary tract infections (UTIs) are prevalent and recurrent bacterial infections that affect individuals worldwide, posing a significant burden on healthcare systems. The present study aimed to explore the epidemiology of UTIs, investigating the seasonal, gender-specific and age-related bacterial pathogen distribution to guide clinical diagnosis. Data were retrospectively collected from electronic medical records and laboratory reports of 926 UTIs diagnosed in Fuding Hospital (Fujian University of Traditional Chinese Medicine, Fuding, China). Bacterial isolates were identified using standard microbiological techniques. χ2 tests were performed to assess associations between pathogens and the seasons, sex and age groups. Significant associations were found between bacterial species and seasons. Enterococcus faecium exhibited a substantial prevalence in spring (χ2, 12.824; P=0.005), while Acinetobacter baumannii demonstrated increased prevalence in autumn (χ2, 16.404; P=0.001). Female patients showed a higher incidence of UTIs. Gram-positive bacteria were more prevalent in males, with Staphylococcus aureus showing significant male predominance (χ2, 14.607; P<0.001). E. faecium displayed an age-related increase in prevalence (χ2, 17.775; P<0.001), whereas Escherichia coli tended to be more prevalent in younger patients (χ2, 12.813; P=0.005). These findings highlight the complex nature of UTIs and offer insights for tailored diagnostic and preventive strategies, potentially enhancing healthcare outcomes.

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection

Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. This manual technique is technically difficult, time-consuming and prone to inter-observer errors. The application of computer vision to this domain has been slow due to the lack of a clinical image dataset from UTI patients. We present an open dataset containing 300 images and 3,562 manually annotated urinary cells labelled into seven classes of clinically significant cell types. It is an enriched dataset acquired from the unstained and untreated urine of patients with symptomatic UTI using a simple imaging system. We demonstrate that this dataset can be used to train a Patch U-Net, a novel deep learning architecture with a random patch generator to recognise urinary cells. Our hope is, with this dataset, UTI diagnosis will be made possible in nearly all clinical settings by using a simple imaging system which leverages advanced machine learning techniques.

The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics?

Advances in consumer electronics, alongside the fields of microfluidics and nanotechnology have brought to the fore low-cost wearable/portable smart devices. Although numerous smart devices that track digital biomarkers have been successfully translated from bench-to-bedside, only a few follow the same fate when it comes to track traditional biomarkers. Current practices still involve laboratory-based tests, followed by blood collection, conducted in a clinical setting as they require trained personnel and specialized equipment. In fact, real-time, passive/active and robust sensing of physiological and behavioural data from patients that can feed artificial intelligence (AI)-based models can significantly improve decision-making, diagnosis and treatment at the point-of-procedure, by circumventing conventional methods of sampling, and in person investigation by expert pathologists, who are scarce in developing countries. This review brings together conventional and digital biomarker sensing through portable and autonomous miniaturized devices. We first summarise the technological advances in each field vs the current clinical practices and we conclude by merging the two worlds of traditional and digital biomarkers through AI/ML technologies to improve patient diagnosis and treatment. The fundamental role, limitations and prospects of AI in realizing this potential and enhancing the existing technologies to facilitate the development and clinical translation of "point-of-care" (POC) diagnostics is finally showcased.