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      Microbial Fermentation of Dietary Protein: An Important Factor in Diet–Microbe–Host Interaction

      review-article
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      Microorganisms
      MDPI
      gut microbiota, protein fermentation, amino acids, host-microbial interaction

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          Abstract

          Protein fermentation by gut microbiota contributes significantly to the metabolite pool in the large intestine and may contribute to host amino acid balance. However, we have a limited understanding of the role that proteolytic metabolites have, both in the gut and in systemic circulation. A review of recent studies paired with findings from previous culture-based experiments suggests an important role for microbial protein fermentation in altering the gut microbiota and generating a diverse range of bioactive molecules which exert wide-ranging host effects. These metabolic products have been shown to increase inflammatory response, tissue permeability, and colitis severity in the gut. They are also implicated in the development of metabolic disease, including obesity, diabetes, and non-alcoholic fatty liver disease (NAFLD). Specific products of proteolytic fermentation such as hydrogen sulfide, ammonia, and p-Cresol may also contribute to the development of colorectal cancer. These findings are in conflict with other studies showing that tryptophan metabolites may improve gut barrier function and attenuate severity in a multiple sclerosis model. Further research examining proteolytic fermentation in the gut may be key to our understanding of how microbial and host metabolism interact affecting health.

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          Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces.

          Weight loss diets for humans that are based on a high intake of protein but low intake of fermentable carbohydrate may alter microbial activity and bacterial populations in the large intestine and thus impact on gut health. In this study, 19 healthy, obese (body mass index range, 30 to 42) volunteers were given in succession three different diets: maintenance (M) for 3 days (399 g carbohydrate/day) and then high protein/medium (164 g/day) carbohydrate (HPMC) and high protein/low (24 g/day) carbohydrate (HPLC) each for 4 weeks. Stool samples were collected at the end of each dietary regimen. Total fecal short-chain fatty acids were 114 mM, 74 mM, and 56 mM (P < 0.001) for M, HPMC, and HPLC diets, respectively, and there was a disproportionate reduction in fecal butyrate (18 mM, 9 mM, and 4 mM, respectively; P < 0.001) with decreasing carbohydrate. Major groups of fecal bacteria were monitored using nine 16S rRNA-targeted fluorescence in situ hybridization probes, relative to counts obtained with the broad probe Eub338. No significant change was seen in the relative counts of the bacteroides (Bac303) (mean, 29.6%) or the clostridial cluster XIVa (Erec482, 23.3%), cluster IX (Prop853, 9.3%), or cluster IV (Fprau645, 11.6%; Rbro730 plus Rfla729, 9.3%) groups. In contrast, the Roseburia spp. and Eubacterium rectale subgroup of cluster XIVa (11%, 8%, and 3% for M, HPMC, and HPLC, respectively; P < 0.001) and bifidobacteria (4%, 2.1%, and 1.9%, respectively; P = 0.026) decreased as carbohydrate intake decreased. The abundance of butyrate-producing bacteria related to Roseburia spp. and E. rectale correlated well with the decline in fecal butyrate.
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            Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men.

            There is growing interest in understanding how diet affects the intestinal microbiota, including its possible associations with systemic diseases such as metabolic syndrome. Here we report a comprehensive and deep microbiota analysis of 14 obese males consuming fully controlled diets supplemented with resistant starch (RS) or non-starch polysaccharides (NSPs) and a weight-loss (WL) diet. We analyzed the composition, diversity and dynamics of the fecal microbiota on each dietary regime by phylogenetic microarray and quantitative PCR (qPCR) analysis. In addition, we analyzed fecal short chain fatty acids (SCFAs) as a proxy of colonic fermentation, and indices of insulin sensitivity from blood samples. The diet explained around 10% of the total variance in microbiota composition, which was substantially less than the inter-individual variance. Yet, each of the study diets induced clear and distinct changes in the microbiota. Multiple Ruminococcaceae phylotypes increased on the RS diet, whereas mostly Lachnospiraceae phylotypes increased on the NSP diet. Bifidobacteria decreased significantly on the WL diet. The RS diet decreased the diversity of the microbiota significantly. The total 16S ribosomal RNA gene signal estimated by qPCR correlated positively with the three major SCFAs, while the amount of propionate specifically correlated with the Bacteroidetes. The dietary responsiveness of the individual's microbiota varied substantially and associated inversely with its diversity, suggesting that individuals can be stratified into responders and non-responders based on the features of their intestinal microbiota.
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              Metabolomics Reveals Metabolic Biomarkers of Crohn's Disease

              The causes and etiology of Crohn's disease (CD) are currently unknown although both host genetics and environmental factors play a role. Here we used non-targeted metabolic profiling to determine the contribution of metabolites produced by the gut microbiota towards disease status of the host. Ion Cyclotron Resonance Fourier Transform Mass Spectrometry (ICR-FT/MS) was used to discern the masses of thousands of metabolites in fecal samples collected from 17 identical twin pairs, including healthy individuals and those with CD. Pathways with differentiating metabolites included those involved in the metabolism and or synthesis of amino acids, fatty acids, bile acids and arachidonic acid. Several metabolites were positively or negatively correlated to the disease phenotype and to specific microbes previously characterized in the same samples. Our data reveal novel differentiating metabolites for CD that may provide diagnostic biomarkers and/or monitoring tools as well as insight into potential targets for disease therapy and prevention.
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                Author and article information

                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                13 January 2019
                January 2019
                : 7
                : 1
                : 19
                Affiliations
                Department of Agriculture, Food & Nutritional Science, University of Alberta, Ag/For Centre, Edmonton Alberta, T6G 2P5, Canada; nmay@ 123456ualberta.ca
                Author notes
                [* ]Correspondence: willing@ 123456ualberta.ca ; Tel.: +1-780-492-8908
                Article
                microorganisms-07-00019
                10.3390/microorganisms7010019
                6352118
                30642098
                b39d39be-1b99-440c-af32-ff8090418b5c
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 December 2018
                : 09 January 2019
                Categories
                Review

                gut microbiota,protein fermentation,amino acids,host-microbial interaction

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