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. 2015 Oct 9:5:14567.
doi: 10.1038/srep14567.

Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Collaborators, Affiliations

Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Gemma Henderson et al. Sci Rep. .

Erratum in

Abstract

Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific.

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Conflict of interest statement

The AgResearch component of this study was funded by the New Zealand Government via the Ministry for Primary Industries (MPI) as part of MPI’s support for the Global Research Alliance on Agricultural Greenhouse Gases. The publication of the data reported here is at the discretion of MPI. MPI did not control which data were presented or how these data were interpreted within this paper. This does not alter the authors’ adherence to all the Scientific Reports policies on sharing data and materials. Material transfer agreements, limiting the use of samples to this study, are in place between AgResearch and Global Rumen Census Collaborators from The University of Alberta (Canada), The Department of Agriculture, Fisheries and Forestry (Queensland, Australia), The University of Aberdeen (Scotland), and The National Institute of Livestock and Grassland Science (Japan). There are no patents, products in development or marketed products to declare. No competing interests were declared by Global Rumen Census Collaborators.

Figures

Figure 1
Figure 1. Origins of samples and their bacterial and archaeal community compositions in different regions.
Numbers below pie charts represent the number of samples for which data were obtained. The most abundant bacteria and archaea are named in clockwise order starting at the top of the pie chart. Further details of samples and community composition are given in Supplementary Tables 1, 2, 3, and 4 and Supplementary Data 1. Mmc. Methanomassiliicoccales. The map was sourced from Wikimedia Commons (http://commons.wikimedia.org/wiki/File:BlankMap-World-v2.png, original uploader Roke, accessed May 2013). Pie charts were produced in Microsoft Excel and the composite image generated with Microsoft PowerPoint and Adobe Illustrator. https://creativecommons.org/licenses/by-sa/3.0/deed.en
Figure 2
Figure 2. Dominant bacterial and archaeal operational taxonomic units (OTUs).
Similarities (Supplementary Tables 8 and 9) of the 50 most abundant and 50 most prevalent bacterial (77 unique OTUs, (a,b) and archaeal (64 unique OTUs, c,d) OTUs to the most closely related type (a,c) and cultured (b,d) strains are plotted together with prevalence and abundance data. Background shading indicates nominal within-species (dark grey), within-genus (mid grey) and below genus (light grey) similarities. Prevalence indicates the percentage of samples that an OTU occurs in. The size of each circle indicates the mean abundance of each OTU (Supplementary Tables 8 and 9). Bacterial OTU abundances were multiplied by a factor of 15 relative to archaeal OTUs. Mbb. Methanobrevibacter.
Figure 3
Figure 3. Effect of host species and dietary forage to concentrate ratios on microbial communities.
Diets were grouped (Supplementary Table 7) as forage-dominated (F), mixed forage-concentrate (50–70% forage, FC), mixed concentrate-forage (50–70% concentrate, CF), or concentrate-dominated (C). (a) Discriminant analysis of microbial communities in samples (represented by points coloured by animal and diet) revealed that both host and diet determined community composition. (b) Bi-plot that shows microbial groups (identified by colours) underlying the separation of samples in panel (a). Several bacterial groups strongly discriminate the samples by host and diet, indicated by their presence towards the outside of the bi-plot. Archaeal and protozoal groups are less discriminatory, and so are clustered nearer the centre. (c) The heatmap shows that bacterial abundances are differentially associated with diet and host (colour key shows the association score; see Supplementary Figs 3–5 for additional data). (d) Unclassified Veillonellaceae, and (e) Fibrobacter are examples of bacteria that caused bovines and caprids to cluster separately from other species in the heat map. The number of samples in each category is given in parentheses in panels (c–e). *indicates unclassified bacteria within an order or family.
Figure 4
Figure 4. Associations between bacteria and archaea.
The network is based on association scores computed via regularised canonical correlation analysis with an absolute association score greater than 0.15. The colour of the lines indicates the strength of the association. The sizes of the diamonds and circles indicate the mean average abundance and microbial groups are identified by numbers (Supplementary Tables 1 and 3). Mbb. Methanobrevibacter, Mmc. Methanomassiliicoccales, *indicates unclassified bacteria within a family.

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