Dietary substitution of soybean oil with coconut oil in the absence of dietary antibiotics supports growth performance and immune function in nursery and grower pigs.

BACKGROUND: We hypothesized that supplementation of nursery and grower pig diets with coconut oil in the absence of antibiotics would yield maintenance of glucose homeostasis, growth performance, and immune function similar to what is achieved with nursery and grower pig diets containing antibiotics. Pigs received the same base treatment diets from d24 (weaning) to d71 of age and had blood and fecal samples collected on d24, d31, d45 and d71 for measurement of whole blood glucose, serum insulin, cortisol and cytokines, and fecal microbiome. Pigs had weekly weights and daily feed consumption measured throughout the study. Animals were euthanized at d71 and subcutaneous fat and ileal contents were collected for assessment for fatty acids and microbiome, respectively. Diet treatments consisted of 2% soybean oil plus antibiotics (ABX; n = 22), 2% soybean oil without antibiotics (NABX; n = 22), and 2% coconut oil without antibiotics (COC; n = 22). Statistical analysis examined the effect of diet within each timepoint using a repeated measures ANOVA. RESULTS: Pigs fed COC diet had decreased serum insulin levels, maintained feed intake, feed conversion and weight gain, and, based on serum cytokines and fecal microbiome, were immunologically similar to ABX-fed pigs. However, NABX-fed pigs performed similarly to the ABX-fed pigs in all parameters except for serum cytokines. Additionally, there was no difference in the incidence of diarrhea between any of the diet treatments. CONCLUSIONS: This study demonstrates that dietary antibiotics are not necessary to maintain growth performance in nursery and grower pigs. However, dietary antibiotics appear to modulate circulating cytokine levels. Dietary coconut oil is neither harmful nor helpful to growth performance or immune function in nursery and grower pigs but does modulate serum insulin levels. Therefore, while coconut oil fed at 2% by weight is a suitable substitute for dietary antibiotics, this study suggests that no substitute for dietary antibiotics is needed at all.

The effect of the urinary and faecal microbiota on lower urinary tract symptoms measured by the International Prostate Symptom Score: analysis utilising next-generation sequencing.

OBJECTIVE: To examine the correlation between urinary and faecal microbial profiles and the different aspects of lower urinary tract symptoms (LUTS) in men, as there is accumulating evidence that variations in the human microbiota may promote different benign disease conditions. PATIENTS AND METHODS: We extracted total DNA from urine and faecal samples of a group of men, under an Institutional Review Board-approved protocol. At the same time, International Prostate Symptom Score (IPSS) data were collected. We then amplified the extracted DNA and sequenced it using bacterial 16S ribosomal RNA gene high-throughput next-generation sequencing platform, and analysed the microbial profiles for taxonomy to examine the correlation between the different operational taxonomy units (OTUs) and LUTS represented by the total IPSS, the different symptom levels of the IPSS (mild, moderate, and severe) and its subcomponents of storage, nocturia, voiding, and bother. RESULTS: We included 30 patients (60 samples; one urine and one faecal per patient). In all, 48 faecal OTUs showed a significant correlation with one or more of the IPSS components; 27 with nocturia, 19 with bother, 16 with storage symptoms, and nine with voiding symptoms. The most substantial negative (protective) correlation was between Lachnospiraceae Blautia, a bacteria that increases the availability of gut anxiolytic and antidepressant short-chain fatty acids, and bother (correlation coefficient 0.702; P = 0.001). The abundance of L. Blautia continued to have a protective correlation against LUTS when looking at the different levels of IPSS severity (moderate and severe vs mild, correlation coefficient 0.6132; P = 0.002). Ten unique urinary OTUs showed significant correlation with LUTS; eight with nocturia, one with bother, three with storage, and one with voiding, but no faecal OUT had more than a low correlation with the outcomes of interest in this study. CONCLUSIONS: Our prospective work finds a plausible correlation between L. Blautia and LUTS. Additional studies are needed to determine if the correlations found in the present research are applicable to the general population of patients affected by LUTS.

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's 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.

A prospective study to examine the association of the urinary and fecal microbiota with prostate cancer diagnosis after transrectal biopsy of the prostate using 16sRNA gene analysis.

INTRODUCTION: There is accumulating evidence that variations in the human microbiota may promote disease states including cancer. Our goal was to examine the association between urinary and fecal microbial profiles and the diagnosis of prostate cancer (PC) in patients undergoing transrectal biopsy of the prostate. MATERIALS AND METHODS: We extracted total DNA from urine and fecal samples collected before a prostate biopsy performed for elevated prostatic specific antigen in patients suspected of having PC. 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 comparing those patients diagnosed with PC with those who did not receive that diagnosis. RESULTS: We included 30 patients in our analysis (60 samples, one urine and one fecal per patient). The majority of patients with PC (10/14) had similar bacterial communities within their urinary sample profile and clustered separately than patients without cancer (n = 16). Differential analysis of the operational taxonomical units (OTUs) in urine samples revealed decreased abundance of several bacterial species in patients with prostate cancer. Analysis of the bacterial taxonomies of the fecal samples did not reveal any clustering in concordance with benign or malignant prostate biopsies. Patients who had a Gleason score (GS) of 6 (n = 11) were present in both urine bacterial community clusters, but patients with GS 7 or higher (n = 3) did not cluster tightly with non-cancer subjects. CONCLUSIONS: 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.