Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

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 features are important for accurate diagnosis of OC. Our study warrants further analyses of the importance of microbial features in regards to oncological diagnostics and possible prognostic and interventional medicine.Ope

Prospective examination of the changes in the urinary microbiome induced by transrectal biopsy of the prostate using 16S rRNA gene analysis.

OBJECTIVES: To prospectively examine the changes in microbiota within the urinary tract after transrectal prostate biopsy. MATERIALS AND METHODS: Data, urine, and fecal samples prospectively collected from 30 patients before and after transrectal biopsy of the prostate. DNA was extracted from urine collected after a prostate massage before and after prostate biopsy, and from fecal samples collected before the biopsy. We sequenced DNA using the bacterial 16S rRNA high-throughput next-generation sequencing and analyzed changes in microbial profiles for taxonomy comparison between samples. RESULTS: Pre-biopsy urinary microbial profiles contained Lactobacillus and Staphylococcus bacteria. Post-biopsy urinary microbial profiles included lower levels of Lactobacillus and higher levels of Prevotella bacteria. Bacteroides bacteria were predominant in fecal samples. We identified two clustering patterns containing both pre- and post-biopsy urine samples. Cluster 1 had a urine cluster pattern that was distinct from fecal, whereas cluster 2 was similar to fecal. We observed two different modes of microbial changes, 11 patients had both of their urine (pre and post) samples associated with a particular cluster group, whereas others (n = 15) had movement between clusters 1 and 2 following the biopsy procedure. Four patient\u27s post-biopsy urine microbial profiles clustered very tightly to the fecal microbial profile. CONCLUSIONS: We describe two models of change in the urinary tract microbiota after prostate biopsy using 16S RNA gene analysis. Further research to determine what controls changes in the urinary microbiota after prostate biopsy can help us understand why some patients are more susceptible to develop post-biopsy infections

Effects of coconut oil on glycemia, inflammation, and urogenital microbial parameters in female Ossabaw mini-pigs.

Forty percent of American women are obese and at risk for type II diabetes, impaired immune function, and altered microbiome diversity, thus impacting overall health. We investigated whether obesity induced by an excess calorie, high fat diet containing hydrogenated fats, fructose, and coconut oil (HFD) altered glucose homeostasis, peripheral immunity, and urogenital microbial dynamics. We hypothesized that HFD would cause hyperglycemia, increase peripheral inflammation, and alter urogenital microbiota to favor bacterial taxonomy associated with inflammation. We utilized female Ossabaw mini-pigs to model a 'thrifty' metabolic phenotype associated with increased white adipose tissue mass. Pigs were fed HFD (~4570 kcal/pig/day) or lean (~2000 kcal/pig/day) diet for a total of 9 estrous cycles (~6 months). To determine the effect of cycle stage on cytokines and the microbiome, animals had samples collected during cycles 7 and 9 on certain days of the cycle: D1, 4, 8, 12, 16, 18. Vaginal swabs or cervical flushes assessed urogenital microbiota. Systemic fatty acids, insulin, glucose, and cytokines were analyzed. Pig weights and morphometric measurements were taken weekly. Obese pigs had increased body weight, length, heart and belly girth but similar glucose concentrations. Obese pigs had decreased cytokine levels (IL-1β, TNF-α, IL-4, IL-10), arachidonic acid and plasma insulin, but increased levels of vaccenic acid. Obese pigs had greater urogenital bacterial diversity, including several taxa known for anti-inflammatory properties. Overall, induction of obesity did not induce inflammation but shifted the microbial communities within the urogenital tract to an anti-inflammatory phenotype. We postulate that the coconut oil in the HFD oil may have supported normal glucose homeostasis and modulated the immune response, possibly through regulation of microbial community dynamics and fatty acid metabolism. This animal model holds promise for the study of how different types of obesity and high fat diets may affect metabolism, immune phenotype, and microbial dynamics

The Effect of the Urinary and Fecal Microbiota on Lower Urinary Tract Symptoms Measured by the International Prostate Symptom Score: Analysis Utilizing Next-Generation Sequencing

INTRODUCTION AND OBJECTIVES: There is accumulating evidence that variations in the human microbiota may promote different benign disease conditions. Our goal was to examine the correlation between urinary and fecal microbial profiles and the different aspect of lower urinary tract symptoms (LUTS) in adult males. MATERIALS AND METHODS: We extracted total DNA from urine and fecal samples from a group of adult males through institutional review board. At the same time, International Prostate Symptom Score (I-PSS) data was collected. We then amplified the extracted DNA and sequenced it using bacterial 16S rRNA gene high-throughput next-generation sequencing platform, and analyzed microbial profiles for taxonomy to examine the correlation between the different operational taxonomy units (OTUs) and LUTS represented by the overall all I-PSS score, the different symptom levels of I-PSS (mild, moderate, and severe), and its subcomponents of storage, nocturia, voiding, and bother. RESULTS: We included 30 patients in our analysis (60 samples, one urine, and one fecal per patient). Forty-eight fecal OTUs showed significant correlation with one or more of the I-PSS components; 27 with nocturia, 19 with bother, 16 with storage symptoms, and 9 with voiding complaints. The most substantial negative (protective) correlation was between Lachnospiraceae Blautia, a bacteria that increase the availability of gut anxiolytic and antidepressant short chain fatty acids, and bother (correlation coefficient - 0.702, p-value 0.001). The abundance of Lachnospiraceae Blautia continued to have protective correlation against LUTS when looking at the different levels of I-PSS severity (moderate and severe vs. mild, correlation coefficient - 0.6132, p-value 0.002). Ten unique urinary OTUs showed significant correlation with LUTS; 8 with nocturia, 1 with bother, 3 with storage, and 1 with void, but no fecal OUT had more than low correlation with the outcomes of interest in this study. CONCLUSIONS: Our prospective work finds a plausible correlation between Lachnospiraceae Blautia and LUTS. Additional studies are needed to determine if the correlations found in this research are applicable to the general population of patients affected by LUTS

Children's strategies for numerosity judgement in square grids: the relationship between process and product data

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Morphometric measurements for lean and obese Ossabaw pigs.

<p>Morphometric measurements for lean and obese Ossabaw pigs.</p

Alpha-diversity on number of OTUs observed.

<p>Results are expressed as least squared mean ± SEM (control, <i>n</i> = 3; obese, <i>n</i> = 2).</p

PCoA plots of distances between pig urogenital bacterial communities.

<p>Variances explained are shown on the axes. Plots include all vaginal swab and cervical flush samples taken of each pig throughout the course of the study. (A) Comparison of lean and obese animals throughout the whole study. (B) Comparison of all samples from both obese and lean animals during the induction versus the maintenance phase of the diet. Each point represents one sample. The color key provides information to determine the influence of features on spatial placement.</p

Average glucose concentration and change in insulin, HOMA-IR, and free fatty acids from beginning to end of trial for lean and obese pigs.

<p>Average glucose concentration and change in insulin, HOMA-IR, and free fatty acids from beginning to end of trial for lean and obese pigs.</p

Relative abundance of prominent phyla and <i>Lactobaciullus</i> genus in vaginal swabs and cervical flushes of both treatment groups during induction and maintenance phases.

<p>Data are shown as least squares mean ± SEM.</p