Objectives: Traditionally, the urinary tract has been thought to be sterile in the absence of a clinically identifiable infection. However, recent evidence suggests that the urinary tract harbors a variety of bacterial species, known collectively as the urinary microbiome, even when clinical cultures are negative. Whether these bacteria promote urinary health or contribute to urinary tract disease remains unknown. Emerging evidence indicates that a shift in the urinary microbiome may play an important role in urgency urinary incontinence (UUI). The goal of this prospective pilot study was to determine how the urinary microbiome is different between women with and without UUI. We also sought to identify if characteristics of the urinary microbiome are associated with UUI severity.Methods: We collected urine from clinically well-characterized women with UUI (n = 10) and normal bladder function (n = 10) using a transurethral catheter to avoid bacterial contamination from external tissue. To characterize the resident microbial community, we amplified the bacterial 16S rRNA gene by PCR and performed sequencing using Illumina MiSeq. Sequences were processed using the workflow package QIIME. We identified bacteria that had differential relative abundance between UUI and controls using DESeq2 to fit generalized linear models based on the negative binomial distribution. We also identified relationships between the diversity of the urinary microbiome and severity of UUI symptoms with Pearson's correlation coefficient.Results: We successfully extracted and sequenced bacterial DNA from 95% of the urine samples and identified that there is a polymicrobial community in the female bladder in both healthy controls and women with UUI. We found the relative abundance of 14 bacteria significantly differed between control and UUI samples. Furthermore, we established that an increase in UUI symptom severity is associated with a decrease in microbial diversity in women with UUI.Conclusions: Our study provides further characterization of the urinary microbiome in both healthy controls and extensively phenotyped women with UUI. Our results also suggest that the urinary microbiome may play an important role in the pathophysiology of UUI and that the loss of microbial diversity may be associated with clinical severity.

The HLA-B27 gene is a major risk factor for clinical diseases including ankylosing spondylitis, acute anterior uveitis, reactive arthritis, and psoriatic arthritis, but its mechanism of risk enhancement is not completely understood. The gut microbiome has recently been shown to influence several HLA-linked diseases. However, the role of HLA-B27 in shaping the gut microbiome has not been previously investigated. In this study, we characterize the differences in the gut microbiota mediated by the presence of the HLA-B27 gene. We identified differences in the cecal microbiota of Lewis rats transgenic for HLA-B27 and human β2-microglobulin (hβ2m), compared with wild-type Lewis rats, using biome representational in situ karyotyping (BRISK) and 16S rRNA gene sequencing. 16S sequencing revealed significant differences between transgenic animals and wild type animals by principal coordinates analysis. Further analysis of the data set revealed an increase in Prevotella spp. and a decrease in Rikenellaceae relative abundance in the transgenic animals compared to the wild type animals. By BRISK analysis, species-specific differences included an increase in Bacteroides vulgatus abundance in HLA-B27/hβ2m and hβ2m compared to wild type rats. The finding that HLA-B27 is associated with altered cecal microbiota has not been shown before and can potentially provide a better understanding of the clinical diseases associated with this gene.

Microbial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam, and (iv) predicting the sequence proportion arising from defined contaminant sources implemented in SourceTracker. As expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 80.1% of the most diluted sample arising from contaminant sequences. Inclusion of contaminant sequences led to overinflated diversity estimates and distorted microbiome composition. All methods for contaminant identification successfully identified some contaminant sequences, which varied depending on the method parameters used and contaminant prevalence. Notably, removing sequences present in a negative control erroneously removed >20% of expected sequences. SourceTracker successfully removed over 98% of contaminants when the experimental environments were well defined. However, SourceTracker misclassified expected sequences and performed poorly when the experimental environment was unknown, failing to remove >97% of contaminants. In contrast, the Decontam frequency method did not remove expected sequences and successfully removed 70 to 90% of the contaminants. IMPORTANCE The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

SD-OCT provides a non-invasive method of following long-term retinal changes in mice in vivo. Although rd10 and rd1 mice have mutations in the same gene, they demonstrate significantly different features on SD-OCT.

Objective The HLA-B27/β2 microglobulin (β2m) transgenic rat is a leading model of B27-associated spondyloarthopathy and disease is dependent on the presence of intestinal bacteria. We have shown previously that adult HLA-B27/β2m rats have an altered intestinal microbiota. In this study we sought to better define age-dependent changes to both mucosal immune function and dysbiosis in this model. Methods Intestinal contents were collected from wild type and HLA-B27/β2m+ rats post-weaning (3 and 6 weeks), at disease onset (10 wks) and after the establishment of disease (16 wks). Microbial community structure was determined by 16s sequencing and qRT-PCR. Mucosal and systemic Th1, Th17 and Treg responses were analyzed by flow cytometry, as was the frequency of IgA-coated intestinal bacteria. Intestinal expression of inflammatory cytokines and antimicrobial peptides (AMPs) was determined by qRT-PCR. Results An inflammatory cytokine signature and elevated AMP expression during the post-weaning period preceded the development of clinical bowel inflammation and dysbiosis in HLA-B27/β2m+ rats. An early and sustained expansion of the Th17 pool was specifically observed in cecal and colonic mucosa of HLA-B27/β2m rats. Strongly elevated Akkermansia mucinphilia colonization and IgA coating of intestinal bacteria was significantly associated with HLA-B27 expression and arthritis development. Conclusions and Perspectives HLA-B27/β2m expression in this rat model renders the host hyper-responsive to microbial antigens from infancy. Early activation of innate immunity and expansion of a mucosal Th17 signature are soon followed by dysbiosis in HLA-B27/β2m+ve animals. Perturbed mucosal immunity and dysbiosis strongly merit further study in both pre-diseased and diseased SpA patient populations.

Objective HLA-B27 associated spondyloarthropathies are associated with an altered intestinal microbiota and bowel inflammation. Therefore, we sought to identify B27-dependent changes in both host and microbial metabolites in the HLA-B27/β2m rat and whether microbiota-derived metabolites could impact disease in this major model of spondyloarthropathy. Methods Cecal contents were collected from 6wk (pre-diseased) and 16wk (diseased) Fischer 344 HLA-B27/β2m transgenic rats and WT controls. Metabolomic profiling was performed by high-throughput gas- and liquid-chromatography-based mass spectrometry. HLA-B27/β2m rats were treated with microbial metabolites propionate or butyrate in drinking water for 10wks and disease activity subsequently assessed. Results Our screen identified 582 metabolites, of which over half were significantly altered by B27 expression at 16wks. Both microbial and host metabolites were altered, with multiple pathways including amino acid, carbohydrate, xenobiotic and medium chain fatty acid metabolism affected. Differences were even observed at 6wks, with upregulation of histidine, tyrosine, spermidine, N-acetylmuramate and glycerate in HLA-B27/β2m rats. Administration of the short chain fatty acid propionate significantly attenuated B27-associated inflammatory disease, albeit was not associated with increased FoxP3+ T cell induction, or altered expression of cytokines IL-10, IL-33 or tight junction protein ZO-1. HLA-B27 expression was also associated with altered host expression of microbial metabolite receptor genes FFAR2, FFAR3 and NIACR1. Conclusion HLA-B27 expression profoundly impacts the intestinal metabolome, with changes evident in rats even at 6wks of age. Critically, we demonstrate a microbial metabolite, propionate attenuates development of B27-associated inflammatory disease. These and other microbiota-derived bioactive mediators may provide novel treatment modalities in B27-associated spondyloathropathies.

Sex hormones promote immunoregulatory effects on multiple sclerosis. In the current study we evaluated the composition of the gut microbiota and the mucosal-associated regulatory cells in estrogen or sham treated female mice before and after autoimmune encephalomyelitis (EAE) induction. Treatment with pregnancy levels of estrogen induces changes in the composition and diversity of gut microbiota. Additionally, estrogen prevents EAE-associated changes in the gut microbiota and might promote the enrichment of bacteria that are associated with immune regulation. Our results point to a possible cross-talk between the sex hormones and the gut microbiota which could promote neuroprotection.

Background: Microbial communities are commonly studied using culture-independent methods such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination. This is particularly problematic for sites of low microbial biomass such as the urinary tract, placenta, and lower airway. Computational approaches have been proposed as a post-