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      Diet-induced extinction in the gut microbiota compounds over generations

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          Abstract

          The gut is home to trillions of microbes that play a fundamental role in many aspects of human biology including immune function and metabolism 1, 2 . The reduced diversity of the Western microbiota compared to populations living traditional lifestyles presents the question of which factors have driven microbiota change during modernization. Microbiota accessible carbohydrates (MACs) found in dietary fiber, play a key role in shaping this microbial ecosystem, and are strikingly reduced in the Western diet relative to more traditional diets 3 . Here we show that changes in the microbiota of mice consuming a low-MAC diet and harboring a human microbiota are largely reversible within a single generation, however over multiple generations a low-MAC diet results in a progressive loss of diversity, which is not recoverable upon the reintroduction of dietary MACs. To restore the microbiota to its original state requires the administration of missing taxa in combination with dietary MAC consumption. Our data illustrate that taxa driven to low abundance when dietary MACs are scarce are inefficiently transferred to the next generation and are at increased risk of becoming extinct within an isolated population. As more diseases are linked to the Western microbiota and the microbiota is targeted therapeutically, microbiota reprogramming may need to involve strategies that incorporate dietary MACs as well as taxa not currently present in the Western gut.

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          Most cited references8

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          CDD: specific functional annotation with the Conserved Domain Database

          NCBI's Conserved Domain Database (CDD) is a collection of multiple sequence alignments and derived database search models, which represent protein domains conserved in molecular evolution. The collection can be accessed at http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml, and is also part of NCBI's Entrez query and retrieval system, cross-linked to numerous other resources. CDD provides annotation of domain footprints and conserved functional sites on protein sequences. Precalculated domain annotation can be retrieved for protein sequences tracked in NCBI's Entrez system, and CDD's collection of models can be queried with novel protein sequences via the CD-Search service at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi. Starting with the latest version of CDD, v2.14, information from redundant and homologous domain models is summarized at a superfamily level, and domain annotation on proteins is flagged as either ‘specific’ (identifying molecular function with high confidence) or as ‘non-specific’ (identifying superfamily membership only).
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            The gut microbiota of rural papua new guineans: composition, diversity patterns, and ecological processes.

            Although recent research revealed an impact of westernization on diversity and composition of the human gut microbiota, the exact consequences on metacommunity characteristics are insufficiently understood, and the underlying ecological mechanisms have not been elucidated. Here, we have compared the fecal microbiota of adults from two non-industrialized regions in Papua New Guinea (PNG) with that of United States (US) residents. Papua New Guineans harbor communities with greater bacterial diversity, lower inter-individual variation, vastly different abundance profiles, and bacterial lineages undetectable in US residents. A quantification of the ecological processes that govern community assembly identified bacterial dispersal as the dominant process that shapes the microbiome in PNG but not in the US. These findings suggest that the microbiome alterations detected in industrialized societies might arise from modern lifestyle factors limiting bacterial dispersal, which has implications for human health and the development of strategies aimed to redress the impact of westernization.
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              Complex interactions among diet, gastrointestinal transit, and gut microbiota in humanized mice.

              Diet has major effects on the intestinal microbiota, but the exact mechanisms that alter complex microbial communities have been difficult to elucidate. In addition to the direct influence that diet exerts on microbes, changes in microbiota composition and function can alter host functions such as gastrointestinal (GI) transit time, which in turn can further affect the microbiota. We investigated the relationships among diet, GI motility, and the intestinal microbiota using mice that are germ-free (GF) or humanized (ex-GF mice colonized with human fecal microbiota). Analysis of gut motility revealed that humanized mice fed a standard polysaccharide-rich diet had faster GI transit and increased colonic contractility compared with GF mice. Humanized mice with faster transit due to administration of polyethylene glycol or a nonfermentable cellulose-based diet had similar changes in gut microbiota composition, indicating that diet can modify GI transit, which then affects the composition of the microbial community. However, altered transit in mice fed a diet of fermentable fructooligosaccharide indicates that diet can change gut microbial function, which can affect GI transit. Based on studies in humanized mice, diet can affect GI transit through microbiota-dependent or microbiota-independent pathways, depending on the type of dietary change. The effect of the microbiota on transit largely depends on the amount and type (fermentable vs nonfermentable) of polysaccharides present in the diet. These results have implications for disorders that affect GI transit and gut microbial communities, including irritable bowel syndrome and inflammatory bowel disease. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                15 December 2015
                14 January 2016
                14 July 2016
                : 529
                : 7585
                : 212-215
                Affiliations
                [1 ]Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
                [2 ]Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
                [3 ]Department of Molecular Biology, Princeton University, Princeton, NJ 08540
                Author notes
                []Correspondence and requests for materials should be addressed to J.L.S., jsonnenburg@ 123456stanford.edu
                [*]

                These authors contributed equally

                Article
                NIHMS742543
                10.1038/nature16504
                4850918
                26762459
                ade5cfb1-f5d7-4ec6-9faa-63c46d6648ae

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