Journal
PLOS ONE
Volume 11, Issue 4, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0154329
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- University of Hohenheim
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The intestinal microbiota and its metabolites appear to be an important factor for gastrointestinal function and health. However, research is still needed to further elaborate potential relationships between nutrition, gut microbiota and host's health by means of a suitable animal model. The present study examined the effect of two different diets on microbial composition and activity by using the pig as a model for humans. Eight pigs were equally allotted to two treatments, either fed a low-fat/high-fiber (LF), or a high-fat/low-fiber (HF) diet for 7 weeks. Feces were sampled at day 7 of every experimental week. Diet effects on fecal microbiota were assessed using quantitative real-time PCR, DNA fingerprinting and meta-proteomics. Furthermore, fecal short-chain fatty acid (SCFA) profiles and ammonia concentrations were determined. Gene copy numbers of lactobacilli, bifidobacteria (P<0.001) and Faecalibacterium prausnitzii (P<0.05) were higher in the LF pigs, while Enterobacteriaceae were more abundant in the HF pigs (P<0.001). Higher numbers of proteins affiliated to Enterobacteriaceae were also present in the HF samples. Proteins for polysaccharide breakdown did almost exclusively originate from Prevotellaceae. Total and individual fecal SCFA concentrations were higher for pigs of the LF treatment (P<0.05), whereas fecal ammonia concentrations did not differ between treatments (P>0.05). Results provide evidence that beginning from the start of the experiment, the LF diet stimulated beneficial bacteria and SCFA production, especially butyrate (P<0.05), while the HF diet fostered those bacterial groups which have been associated with a negative impact on health conditions. These findings correspond to results in humans and might strengthen the hypothesis that the response of the porcine gut microbiota to a specific dietary modulation is in support of using the pig as suitable animal model for humans to assess diet-gut-microbiota interactions.
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