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      Metagenomic reconstructions of gut microbial metabolism in weanling pigs

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          Abstract

          Background

          The piglets’ transition from milk to solid feed induces a succession of bacterial communities, enhancing the hosts’ ability to harvest energy from dietary carbohydrates. To reconstruct microbial carbohydrate metabolism in weanling pigs, this study combined 16S rRNA gene sequencing ( n = 191) and shotgun metagenomics ( n = 72).

          Results

          Time and wheat content in feed explained most of the variation of the microbiota as assessed by 16S rRNA gene sequencing in weanling pigs. De novo metagenomic binning reconstructed 360 high-quality genomes that represented 11 prokaryotic and 1 archaeal phylum. Analysis of carbohydrate metabolism in these genomes revealed that starch fermentation is carried out by a consortium of Firmicutes expressing extracellular α-(1 → 4)-glucan branching enzyme (GH13) and Bacteroidetes expressing periplasmic neopullulanase (GH13) and α-glucosidase (GH97). Fructans were degraded by extracellular GH32 enzymes from Bacteriodetes and Lactobacillus. Lactose fermentation by β-galactosidases (GH2 and GH42) was identified in Firmicutes. In conclusion, the assembly of 360 high-quality genomes as the first metagenomic reference for swine intestinal microbiota allowed identification of key microbial contributors to degradation of starch, fructans, and lactose.

          Conclusions

          Microbial consortia that are responsible for degradation of these glycans differ substantially from the microbial consortia that degrade the same glycans in humans. Our study thus enables improvement of feeding models with higher feed efficiency and better pathogen control for weanling pigs.

          Electronic supplementary material

          The online version of this article (10.1186/s40168-019-0662-1) contains supplementary material, which is available to authorized users.

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          Most cited references53

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          Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors.

          In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genome-wide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.
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            How glycan metabolism shapes the human gut microbiota.

            Symbiotic microorganisms that reside in the human intestine are adept at foraging glycans and polysaccharides, including those in dietary plants (starch, hemicellulose and pectin), animal-derived cartilage and tissue (glycosaminoglycans and N-linked glycans), and host mucus (O-linked glycans). Fluctuations in the abundance of dietary and endogenous glycans, combined with the immense chemical variation among these molecules, create a dynamic and heterogeneous environment in which gut microorganisms proliferate. In this Review, we describe how glycans shape the composition of the gut microbiota over various periods of time, the mechanisms by which individual microorganisms degrade these glycans, and potential opportunities to intentionally influence this ecosystem for better health and nutrition.
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              HMMER web server: 2015 update

              The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.
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                Author and article information

                Contributors
                086-2787283455 , jszheng@mail.hzau.edu.cn
                + 1 780 492 0774 , mgaenzle@ualberta.ca
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                26 March 2019
                26 March 2019
                2019
                : 7
                : 48
                Affiliations
                [1 ]GRID grid.17089.37, Department of Agricultural, Food and Nutritional Science, , University of Alberta, ; 4-10 Ag/For Centre, Edmonton, Alberta T6G 2P5 Canada
                [2 ]ISNI 0000 0004 1790 4137, GRID grid.35155.37, State Key Lab of Agricultural Microbiology, Hubei Key Laboratory of Agricultural Bioinformatics, , Huazhong Agricultural University, ; Wuhan, 430070 People’s Republic of China
                [3 ]ISNI 0000 0000 8822 034X, GRID grid.411410.1, Hubei University of Technology, College of Bioengineering and Food Science, ; Wuhan, People’s Republic of China
                Author information
                http://orcid.org/0000-0003-0972-928X
                Article
                662
                10.1186/s40168-019-0662-1
                6436221
                30914068
                7a6b8283-5751-4051-88bc-ba330c08affc
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 November 2018
                : 11 March 2019
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                metagenomic,reconstructions,weanling pigs,microbial degradation,lactose,fructan,starch

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