Urethral obstruction (UO) is a devastating, common, and recurrent manifestation of feline interstitial cystitis (FIC) in male cats. Inflammation caused by FIC can result in the formation of “urethral plugs” of inflammatory cells, protein, crystals, and debris that obstruct urine flow out of the urethra, causing life-threatening hyperkalemia and azotemia. It is estimated that 18% to 60% of male cats with UO have urethral plugs secondary to FIC.1 An additional 15% to 53% with UO do not have an obvious cause of obstruction, with some authors postulating that bladder inflammation leads to urethral spasm and a functional UO.1 In cats that develop UO, management with urethral catheterization, fluids, and analgesia is required to treat the acute crisis, resulting in a significant financial burden for clients. Additionally, 15% to 40% of cats with UO go on to have recurrent episodes, resulting in the need for repeated hospitalizations.1 Although the survival rate for cats with UO that are treated is high at 90% to 95%, due to the recurrent nature of the condition and resultant financial strain, many cats with UO are ultimately euthanized.1
Interstitial cystitis and bladder pain syndrome (IC/BPS) in humans is a condition that bears a remarkable similarity to FIC.2,3 Both syndromes result in the clinical signs of dysuria, hematuria, and pollakiuria secondary to inflammation within the bladder; however, the relatively small size of the feline male urethra predisposes cats to UO. The underlying etiology of IC/BPS and FIC has yet to be elucidated but has been postulated to be secondary to neurogenic inflammation and/or disruption of the urothelial barrier.2 Historically, bladder inflammation in IC/BPS patients was thought to be sterile as bacteria were infrequently detected using traditional culture.4 Similarly, a study5 of male cats with UO found that no cats had detectable bacteriuria on presentation using bacterial culture. However, many organisms are fastidious and difficult to grow in culture, thus potentially underestimating the role that bacteria may play in urinary disorders.6 In humans, studies4,6,7 using molecular methods of detecting bacterial DNA suggest that the urinary bladder hosts a resident microbial population in health, and this population may be altered with disease. In humans with IC/BPS, there is documentation of decreased urinary microbial diversity as well as alterations in the predominant bacterial taxa present compared to healthy women (ie, urinary dysbiosis).7–9 The development of urinary dysbiosis in a disease state disrupting the rich and diverse resident urinary microbiota has important implications for urinary health. It is postulated that the urinary microbiota may play important physiologic functions, including the regulation of epithelial junctions, the maintenance of the urothelial barrier, nervous system interactions, competition with pathogens, and the production of antimicrobial compounds.6
The discovery of commensal urinary microbiota is in large part due to the advent of next-generation sequencing (NGS), which is a relatively new technology that allows for nucleic acid sequencing that is better able to detect the DNA in samples with low biomass compared to previous sequencing methods. Next-generation sequencing has been used to evaluate the urinary microbiota of healthy dogs, revealing diverse and unique urinary microbiota in that species.10 The feline urinary microbiome has been minimally investigated to date.11–14 As there are substantial similarities between IC in cats and humans, and urinary dysbiosis has been shown to occur in human IC/BPS patients, the urinary microbiota may play a role in feline cystitis as well. If urinary dysbiosis can be documented in cats with UO, this would set the stage for subsequent investigations into how modulation of the urinary microbiota might be able to reduce the incidence of UO.
We hypothesized that the feline urinary tract harbors a unique urinary microbiota best characterized by 16S rRNA gene sequencing that deviates from health (ie, undergoes dysbiosis) with UO secondary to FIC. Our specific aims included documenting differences in microbial community members and structure in healthy cats versus those with UO and comparing the composition of the feline urinary microbiota with the oral, preputial, and rectal microbial communities to determine if feline urinary microbiota are unique or related to these sites, and characterizing these previously unknown microbial communities using 16S rRNA gene sequencing will reveal rich and diverse urinary microbial communities despite a lack of bacterial growth on traditional urine culture.
Methods
This study was a prospective, observational study. Male cats presenting to the University of Missouri Veterinary Health Center with physical examination findings consistent with UO were eligible for inclusion. Healthy volunteer male cats solicited from the veterinary school community were used as age-matched controls. Both groups had a baseline CBC, chemistry panel, urinalysis, urine culture, and focal bladder ultrasound performed. Cats were excluded if there was evidence of urinary tract infection or urolithiasis, antimicrobial administration or urinary catheterization in the past 30 days, or a comorbid condition. Healthy cats were also excluded if physical examination or sample acquisition resulted in significant stress such that sedation would be required for handling. Informed owner consent was obtained for all cats and was approved by the university IACUC (#9782).
Cats with UO had a peripheral IV catheter placed, and a blood sample was obtained from the catheter at the time of placement. If the sample obtained from the peripheral catheter was insufficient for analysis, additional blood was taken from the jugular, cephalic, or medial saphenous vein when the patient was sedated for urinary catheter placement. Healthy subjects had blood samples taken from the jugular, cephalic, or medial saphenous vein via direct venipuncture.
Sample collection and DNA extraction
All cats had a cystocentesis performed to collect urine samples. In cats with UO, cystocentesis was performed prior to urinary catheter placement, which has been shown to be safe.31 The abdomen was clipped and prepared with dilute chlorhexidine solution, and a 22-gauge needle was aseptically inserted into the bladder to obtain a sterile sample. The urine sample was separated into aliquots for urinalysis (2 mL), urine culture (1 mL), and 16S rRNA gene amplicon sequencing (3 to 6 mL). Prior to obtaining the urine sample, the site of the needle insertion was swabbed with a sterile moistened cotton tip applicator, moistened with sterile water, for 15 to 20 seconds. This sample was used as a control to correct for contamination of the urine sample with dermal microbes. Three moistened cotton tip applicators were used to separately swab the prepuce, buccal mucosa, and rectum for 15 to 20 seconds. The swabs were placed into separate 15-mL conical vials, each containing 5 mL of sterile water. In UO cats, cystocentesis and swabbing were performed under the same sedation already required for urinary catheter placement to reduce patient stress. The choice of analgesia, sedatives, and urinary catheter type was at the discretion of the attending clinician. The urine sample for NGS and the oral, skin, genital, and rectal swabs were centrifuged at 2,150 X g for 20 minutes, and the supernatant was discarded. To the remaining pellet from each sample, 800 μL of lysis buffer was added and vortexed until thoroughly mixed. The mixtures were transferred to 2-mL sterile tubes and stored at −80 °C until DNA extraction. DNA was extracted using QIAamp PowerFecal Pro DNA extraction kits (Qiagen) according to the manufacturer's instructions.10 After extraction, DNA was stored at −20 °C prior to library preparation.
Bacterial culture
Samples for urine culture were incubated on tryptic soy agar with 5% sheep blood, MacConkey agar, chocolate agar plates incubated in 5% CO2, and prereduced tryptic soy agar with 5% sheep blood. Plates were inoculated with a sample swab for aerobic, capnophilic, and anaerobic bacterial isolation. Plates were incubated at 35 °C in air, 5% CO2, or anaerobic conditions for 72 hours and examined for colony formation.
16S rRNA library preparation and sequencing
The V4 region of the 16S rRNA gene was used to generate amplicons using single-indexed universal primers flanked by standard adapter sequences (Illumina). These were pooled for sequencing using the MiSeq platform (Illumina) and V2 chemistry with 2 X 250-bp paired-end reads. Quantitative Insights into Molecular Ecology 232 was used to process the 16S rRNA amplicon sequences. Paired-end reads were first trimmed of the universal (515 forward/806 reverse) primers and Illumina adapters using cutadapt.29 Sequences containing indels and those left untrimmed were discarded. The reads were then truncated to 150 bp in length, merged (a minimum of 12-bp overlap), and denoised into unique amplicon sequence variants (ASVs) using DADA2.30 Chimeras were removed using the consensus method. Resolved features were then assigned a taxonomic classification with a sklearn approach using a SILVA 138 reference database15 trimmed to the V4 region. The resulting feature table was purged of contaminating features using the prevalence-based method from the decontam library32 with default settings.
Bioinformatics
Microbiota data analysis was performed within R, version 4.2.29 α Diversity metrics were calculated using the microbiome (Chao-1, Shannon) and vegan (Simpson) libraries.30–32 Differences in β diversity were visualized using principal coordinate analysis. Distance matrices were generated from a table using the vegan library.31,32 Matrices were generated using both weighted (Bray-Curtis) and unweighted (Jaccard) distances. A Calliez-corrected principal coordinate analysis was performed on the appropriate distance matrix using the ape library.29 Estimated contributions of the buccal, rectal, and genital microbiomes (source) to the urinary microbiome (sink) were determined using SourceTracker230 with default settings.
Univariate data were reported at mean ± SE. Differences in univariate data were assessed using Wilcoxon rank-sum tests within the sample site. Differences in β diversity (multivariate data) were assessed using permutational multivariate analysis of variance with 9,999 permutations. Genus-level differential abundance testing was performed using linear discriminant analysis (LDA) effect size31 within the microbiomeMarker library.32 Differentially abundant features were identified based on an LDA score > 2 and P < .05.
Results
Population
A total of 30 male castrated cats were including, 15 cats diagnosed with a UO and 15 cats that were age matched to the exact year. The mean age of the cats was 4 ± 0.48 years old. The samples were collected from 2020 through 2021.
Decontamination
Due to the low biomass of urine samples, we first removed contaminating ASVs from our dataset using decontam.32 We removed 141 contaminating features (12.7%) identified in abdominal skin swabs from the site of needle insertion. Ninety-four contaminating features (2.59%) detected in negative control swabs were then removed from the preputial, buccal, and rectal samples. Following decontamination, absolute feature counts were increased (P < .001) in urine samples and decreased (P = .028) in rectal swabs collected from patients with UO (Supplementary Figure S1).
α Diversity
We next assessed whether UO affected the microbial richness and diversity of the oral, rectal, genital, and urinary microbiota. Community richness (Chao-1 index) was significantly increased when compared to the healthy controls in the preputial (P = .009) and buccal (P = .002) microbiota in patients with UO (Figure 1). Interestingly, UO significantly reduced microbial diversity in skin sample from the cystocentesis site and urine sample using both Shannon (Figure 1) and weighted and unweighted Simpson (Supplementary Figure S2) indices.
Within-sample richness (A) and diversity (B) observed in feline patients with urethral obstruction and healthy controls. **P < .01; ***P < .001. Wilcoxon rank-sum test.
Citation: American Journal of Veterinary Research 2025; 10.2460/ajvr.24.07.0213
β Diversity
Microbial composition significantly differed between sample sites using both weighted (Bray-Curtis; sample: F = 7.91; P < .001) and unweighted distances (Jaccard; sample: F = 5.21; P < .001; Supplementary Figure S3). Within each sample site, we observed significant differences in unweighted community composition between groups in buccal (F = 2.52; P < .001), preputial (F = 2.41; P < .001), and urinary (F = 8.69; P < .001) samples (Figure 2). Significant differences in microbial composition were also observed in buccal (F = 3.50; P < .001), preputial (F = 3.21; P < .001), and urinary (F = 11.68; P < .001) samples using weighted distances (Supplementary Figure S4).
Principal coordinate analyses depicting differences in unweighted community composition in control ([A] F = 1.00; P = .466), cysto ([B] F = 1.09; P = .167), urine ([C] F = 8.69; P < .001), preputial ([D] F = 2.41; P < .001), buccal ([E] F = 2.52; P < .001), and rectal ([F] F = 0.93; P = .580) samples. One-way permutational ANOVA within sample site. PCO = Principal coordinate analyses.
Citation: American Journal of Veterinary Research 2025; 10.2460/ajvr.24.07.0213
Differential abundance testing
Given that the largest difference in microbial composition was observed in urine samples, we next applied the LDA effect size31,32 differential abundance tool to identify genus-level microbial biomarkers of the urinary microbiota in feline patients with urethral obstruction and healthy controls. Only Pedobacter (phylum Bacteroidota) was identified as a biomarker of UO in the urinary microbiota (LDA, 2.641; P < .001). Pedobacter was the dominant taxa identified in the urinary microbiota of patients with UO (44.1% ± 16%) relative to healthy controls (0.227% ± 0.025%; Figure 3). Manual alignment of the dominant ASV sequence using the National Center for Biotechnology Information Basic Local Alignment Search Tool revealed a 100% identity (E = 9e−132) to P lithocola strain CCM 869129 and less than 100% identity to other strains.
Absolute Pedobacter feature counts observed in the urinary microbiome. ***P < .001. Wilcoxon rank-sum test.
Citation: American Journal of Veterinary Research 2025; 10.2460/ajvr.24.07.0213
SourceTracker
Lastly, we sought to determine whether the oral, genital, and/or rectal microbial communities contributed to the shifts in composition observed in the urinary microbiota during UO. Using SourceTracker2,30 we identified that the contribution of the buccal (P = .002) and rectal (P = .003) microbiotas to the urinary microbiota was significantly reduced in UO patients; however, a significant increase in microbial contribution from an unknown source (P = .003) was observed relative to healthy controls (Figure 4). Focusing on potential Pedobacter sources, an increase in absolute Pedobacter feature counts in rectal swabs was observed in UO patients (Supplementary Figure S5).
Relative predicted microbial contribution of sample site to urinary microbiome determined by SourceTracker2. **P < .01. Wilcoxon rank-sum test.
Citation: American Journal of Veterinary Research 2025; 10.2460/ajvr.24.07.0213
Discussion
The results of this study support the hypothesis that the feline urinary tract harbors a unique urinary microbiota that deviates from health with UO secondary to FIC. Pedobacter was found to be a biomarker of dysbiosis in cats with UO compared to the healthy controls. When comparing the feline urinary microbiota with the oral, preputial, and rectal microbial communities, the urinary microbiota was specific to the urinary tract and was also altered with UO. However, there were also differences found in the other sites when comparing the UO cats to the healthy cats. This demonstrates that dysbiosis in the urinary microbiota affects the microbiota in other areas of the body or that a change in the microbiota in other areas of the body could affect the urinary microbiota. All cats included had negative urine cultures, indicating that there is a specific bacterial microbiota that cannot be detected on routine urine cultures, and the microbiota shifts observed in this study also cannot be detected on routine urine cultures.
The β diversity showed differences in the microbial composition and showed differences between the oral, preputial, and urinary samples. The most significant difference in microbial composition was found between the urine of healthy cats compared to cats with UO, indicating that the urinary microbiota could play a role in UO; however, it is also plausible that the altered urinary microbiota in cats with UO was a result of the disease process rather than a cause. The difference in urinary microbial composition between the 2 groups was further investigated to identify genus-level microbial biomarkers that could indicate UO. Pedobacter was an identified biomarker of UO. It is important to note that the detection of Pedobacter in these samples is only detecting DNA and not the live organism; this does not indicate that Pedobacter infection contributes to UO. Collectively, these data suggest that UO alters the composition of the urinary microbiota with a specific increase in Pedobacter abundance. The overgrowth of Pedobacter is noteworthy in that in other studies,30,31 all strains of this genus are multidrug resistant and intrinsically resistant to several classes of antibiotics, including β-lactams, aminoglycosides, ciprofloxacin, colistin, and others. While the urinary microbiota presumably returns to that of a healthy cat with low numbers of Pedobacter following removal of the UO, proliferation of multidrug-resistant bacteria is always of concern due to the potential for opportunistic infection or lateral gene transfer. Although the results demonstrate a potential overgrowth of a specific bacterium in the microbiota, this does not indicate that antibiotics are necessary. It is uncertain whether this change occurs secondary to UO or if it is a potential contributor to UO. Since Pedobacter is an inherently antibiotic-resistant organism, empiric treatment with antibiotics could contribute to increasingly resistant infections. Instead, other treatment modalities, such as probiotics or prebiotics, could be investigated in the future as novel treatment options.
When analyzing the microbiota in the other sites, there were differences between the healthy and UO groups, indicating that the presence of UO affects the microbiota in other areas in the body and that the microbiota between sites contribute to one another. When comparing the microbial community richness in the UO group, there was a significant increase in richness in the preputial and oral microbiota, which was not found in the cystocentesis skin site or urinary samples. Increased microbial community richness indicates that there was an increase in the total number of bacterial species in the preputial and oral samples. There was a significant reduction in the microbial diversity of the skin samples and urine samples, meaning that there were smaller amounts of individual bacteria from each of the bacterial species found. These changes in community richness and diversity in the UO group support that there are broad shifts in overall microbial composition, indicating urinary dysbiosis along with dysbiosis that occurs in other areas of the body.
The data supports that there is dysbiosis not only in the urine samples but also in other areas of the body; however, the largest difference in microbial composition is noted in the urine samples with Pedobacter being the dominant taxa identified. It was determined that the contribution of the oral and rectal microbiota to the urinary microbiota was significantly reduced in the UO group, and a significant increase in microbial contribution from an unknown source was identified. There was an increase in Pedobacter in the rectal microbiota samples; therefore, the abundance of Pedobacter in cystocentesis samples from UO cats might originate from the rectum. If the source of Pedobacter originates from the rectum, it is possible that altering the gastrointestinal microbiome could prevent the predominance of Pedobacter and reduce or eliminate the urinary dysbiosis that occurs with UO. Alternatively, Pedobacter, an environmental bacterium, may be normally cleared, but during the disease process of UO there is an opportunity for this specific bacterium to overgrow. The sources contributing to overall shifts in the urinary microbiota composition during UO were unable to be identified in this study.
This study supports the presence of a resident microbiota in the urine of healthy cats and cats with UO, which has been minimally supported in recent veterinary literature.11,13,14 After removing ASVs from the control swabs, there was an increase in absolute feature counts in the urinary samples. The fact that our study supported the presence of a urinary microbiota when other studies were unable to and supported the presence of dysbiosis in the urinary microbiota with UO is very important to recognize as this may provide a better understanding as to how UOs develop or affect the microbiota in cats. In addition, this could provide a novel treatment pathway that has not been explored. Prior studies,11,14 which also controlled for contaminants using a similar technique, were unable to find a resident microbiota in the urinary tract of healthy cats or cats with FIC, which the results of our study directly contradict. The results of this study contradicting prior studies is similar to the human studies4,7,14 conducted in women with PBS/IC, where there have been conflicting results. In support of our study findings, another study12 supported the presence of microbiota in healthy cats, cats with FIC, and cats with chronic kidney disease; however, the information on the microbiota was limited. This study had supporting evidence that environmental factors can alter the urine metabolome in both healthy and diseased states.12 Our study was unable to determine the source of the Pedobacter in the UO group, and the results suggested that it could be from either the rectal microbiota or an environmental source. The results of this study add significant value to the current information on the urinary microbiota in cats as it demonstrates different conclusions than what has previously been reported.
Despite the compelling results of our study, there are nonetheless limitations to the experimental design and outcomes. While efforts were made to identify and remove contaminating bacterial DNA from the skin, other minor sources of contamination are recognized.32 Similarly, efforts were made to account for the low biomass of several samples, but it is possible that certain bacteria that were present were simply not detected. Another limitation to 16S rRNA gene sequencing is that it was unable to determine the absolute bacterial load; thus, the observed differences in abundance may not reflect total bacterial load; however, differences in bacterial load of specific taxa (eg, Pedobacter) would be expected given the dramatic differences in the detected abundance in such low-biomass communities. Additionally, NGS may be performed using different processing techniques, and results can be inconsistent and may not be reproducible because of this variability and lack of a universal standard approach.33,34
This is a limitation of this study; however, a single laboratory was used where the sequencing, processing, and taxonomic classification methods used have been well validated. The results of this study are preliminary and would need to be repeated to fully validate the results given the evidence that NGS studies can be difficult to reproduce with consistent results. Due to financial limitations, this study could not be repeated on a separate population of cats, but future studies investigating the urinary microbiome of cats with UO may be warranted to determine if the findings of this study are reproducible.
In conclusion, our preliminary data demonstrate a dramatic change in the urinary microbiota of obstructed cats characterized by the proliferation of Pedobacter. While the specific source of Pedobacter was not definitively ascertained, the highest read counts from other potential source sites were obtained from rectal swabs. It was unable to be determined if this dysbiosis contributes to the development of UO or if this dysbiosis occurs secondary to UO. These preliminary data support the presence of dysbiosis in cats with UO, although future studies are needed to validate these changes. Documenting dysbiosis in UO cats has the potential to provide an avenue for novel therapeutics, and further exploration into the treatment of dysbiosis and outcomes for UO cats can be explored in the future.
Supplementary Materials
Supplementary materials are posted online at the journal website: avmajournals.avma.org.
Acknowledgments
The authors would like to acknowledge the University of Missouri Genomics Technology Core for their work with 16S rRNA library preparation and sequencing.
Disclosures
The authors have nothing to disclose. No AI-assisted technologies were used in the generation of this manuscript.
Funding
Funded by the Kent Tomazi Memorial Research Fund in Veterinary Medicine.
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