Basidiomycota species in Drosophila gut are associated with host fat metabolism.

The importance of bacterial microbiota on host metabolism and obesity risk is well documented. However, the role of fungal microbiota on host storage metabolite pools is largely unexplored. We aimed to investigate the role of microbiota on D. melanogaster fat metabolism, and examine interrelatedness between fungal and bacterial microbiota, and major metabolic pools. Fungal and bacterial microbiota profiles, fat, glycogen, and trehalose metabolic pools are measured in a context of genetic variation represented by whole genome sequenced inbred Drosophila Genetic Reference Panel (DGRP) samples. Increasing Basidiomycota, Acetobacter persici, Acetobacter pomorum, and Lactobacillus brevis levels correlated with decreasing triglyceride levels. Host genes and biological pathways, identified via genome-wide scans, associated with Basidiomycota and triglyceride levels were different suggesting the effect of Basidiomycota on fat metabolism is independent of host biological pathways that control fungal microbiota or host fat metabolism. Although triglyceride, glycogen and trehalose levels were highly correlated, microorganisms' effect on triglyceride pool were independent of glycogen and trehalose levels. Multivariate analyses suggested positive interactions between Basidiomycota, A. persici, and L. brevis that collectively correlated negatively with fat and glycogen pools. In conclusion, fungal microbiota can be a major player in host fat metabolism. Interactions between fungal and bacterial microbiota may exert substantial control over host storage metabolite pools and influence obesity risk.

Quantitative real-time PCR analysis of bacterial biomarkers enable fast and accurate monitoring in inflammatory bowel disease.

Inflammatory bowel diseases (IBD) affect millions of people worldwide with increasing incidence. Ulcerative colitis (UC) and Crohn's disease (CD) are the two most common IBDs. There is no definite cure for IBD, and response to treatment greatly vary among patients. Therefore, there is urgent need for biomarkers to monitor therapy efficacy, and disease prognosis. We aimed to test whether qPCR analysis of common candidate bacteria identified from a patient's individual fecal microbiome can be used as a fast and reliable personalized microbial biomarker for efficient monitoring of disease course in IBD. Next generation sequencing (NGS) of 16S rRNA gene region identified species level microbiota profiles for a subset of UC, CD, and control samples. Common high abundance bacterial species observed in all three groups, and reported to be associated with IBD are chosen as candidate marker species. These species, and total bacteria amount are quantified in all samples with qPCR. Relative abundance of anti-inflammatory, beneficial Faecalibacterium prausnitzii, Akkermansia muciniphila, and Streptococcus thermophilus was significantly lower in IBD compared to control samples. Moreover, the relative abundance of the examined common species was correlated with the severity of IBD disease. The variance in qPCR data was much lower compared to NGS data, and showed much higher statistical power for clinical utility. The qPCR analysis of target common bacterial species can be a powerful, cost and time efficient approach for monitoring disease status and identify better personalized treatment options for IBD patients.