The urinary microbiota of patients with PC tends to cluster separately from those without this disease. Further research is needed to investigate the urinary microbiome potential of serving as a biomarker that could be used to improve the accuracy of pre-biopsy models predicting the presence of PC in post-biopsy tissue examination.

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Patients with urologic chronic pelvic pain syndromes (UCPPS) suffer chronic pelvic pain and dramatically lower quality of life, yet diagnostic markers and effective therapies remain elusive for these costly syndromes 1 . Interstitial cystitis/bladder pain syndrome (IC/BPS or IC) is a debilitating UCPPS condition of pelvic pain and voiding dysfunction that afflicts as many as 8 million U.S. women where depression is a common co-morbidity 2-5 . IC etiology remains unknown, but urothelial lesions and lamina propria mast cells are associated with patient symptoms [6][7][8] . HPA axis dysfunction has been implicated in female and male patients and cats with feline IC 9-13 , and thus may be common among UCPPS, but mechanisms that integrate pelvic pain, voiding dysfunction, HPA activity, and depression are lacking. Because of these long-standing questions, NIDDK has launched its flagship urology study, the Multi-Disciplinary Approaches to Chronic Pelvic Pain (MAPP) Research Network with the most comprehensive studies to date of UCPPS including clinical characterization and epidemiologic and mechanistic studies 14,15 . Operational taxonomic units (OTUsThe microbiome is increasingly appreciated as driving diverse physiologic processes in both health and disease 16,17 . With the notable exception of C. difficile colitis, early studies implicated pathogenic dysbioses primarily at the phylum and genus levels, but more recent studies identify individual species associated with disease. Moreover, individual species within the microbiome have recently been associated with driving disease through altered innate metabolism or altered pharmaceutical metabolism 18 . Despite these advances, it remains unclear whether microbiota contribute to pain syndromes generally and to UCPPS in particular. Consistent with the recent finding of a normal female urinary microbiome 19 , the MAPP Network is also exploring UCPPS microbiota with a focus on the urinary microbiome. MAPP Network studies have identified an association between fungi

e Campylobacter jejuni is a leading cause of human foodborne gastroenteritis worldwide. The interactions between this pathogen and the intestinal microbiome within a host are of interest as endogenous intestinal microbiota mediates a form of resistance to the pathogen. This resistance, termed colonization resistance, is the ability of commensal microbiota to prevent colonization by exogenous pathogens or opportunistic commensals. Although mice normally demonstrate colonization resistance to C. jejuni, we found that mice treated with ampicillin are colonized by C. jejuni, with recovery of Campylobacter from the colon, mesenteric lymph nodes, and spleen. Furthermore, there was a significant reduction in recovery of C. jejuni from ampicillin-treated mice inoculated with a C. jejuni virulence mutant (⌬flgL strain) compared to recovery of mice inoculated with the C. jejuni wildtype strain or the C. jejuni complemented isolate (⌬flgL/flgL). Comparative analysis of the microbiota from nontreated and ampicillin-treated CBA/J mice led to the identification of a lactic acid-fermenting isolate of Enterococcus faecalis that prevented C. jejuni growth in vitro and limited C. jejuni colonization of mice. Next-generation sequencing of DNA from fecal pellets that were collected from ampicillin-treated CBA/J mice revealed a significant decrease in diversity of operational taxonomic units (OTUs) compared to that in control (nontreated) mice. Taken together, we have demonstrated that treatment of mice with ampicillin alters the intestinal microbiota and permits C. jejuni colonization. These findings provide valuable insights for researchers using mice to investigate C. jejuni colonization factors, virulence determinants, or the mechanistic basis of probiotics.

Epithelial ovarian cancer (OC) is the most deadly cancer of the female reproductive system. To date, there is no effective screening method for early detection of OC and current diagnostic armamentarium may include sonographic grading of the tumor and analyzing serum levels of tumor markers, Cancer Antigen 125 (CA-125) and Human epididymis protein 4 (HE4). Microorganisms (bacterial, archaeal, and fungal cells) residing in mucosal tissues including the gastrointestinal and urogenital tracts can be altered by different disease states, and these shifts in microbial dynamics may help to diagnose disease states. We hypothesized that the peritoneal microbial environment was altered in patients with OC and that inclusion of selected peritoneal microbial features with current clinical features into prediction analyses will improve detection accuracy of patients with OC. Blood and peritoneal fluid were collected from consented patients that had sonography confirmed adnexal masses and were being seen at SIU School of Medicine Simmons Cancer Institute. Blood was processed and serum HE4 and CA-125 were measured. Peritoneal fluid was collected at the time of surgery and processed for Next Generation Sequencing (NGS) using 16S V4 exon bacterial primers and bioinformatics analyses. We found that patients with OC had a unique peritoneal microbial profile compared to patients with a benign mass. Using ensemble modeling and machine learning pathways, we identified 18 microbial features that were highly specific to OC pathology. Prediction analyses confirmed that inclusion of microbial features with serum tumor marker levels and control features (patient age and BMI) improved diagnostic accuracy compared to currently used models. We conclude that OC pathogenesis alters the peritoneal microbial environment and that these unique microbial