Literature DB >> 23871375

Investigating the effect of two methane-mitigating diets on the rumen microbiome using massively parallel sequencing.

E M Ross1, P J Moate, L Marett, B G Cocks, B J Hayes.   

Abstract

Variation in the composition of microorganisms in the rumen (the rumen microbiome) of dairy cattle (Bos taurus) is of great interest because of possible links to methane emission levels. Feed additives are one method being investigated to reduce enteric methane production by dairy cattle. Here we report the effect of 2 methane-mitigating feed additives (grapemarc and a combination of lipids and tannin) on rumen microbiome profiles of Holstein dairy cattle. We used untargeted (shotgun) massively parallel sequencing of microbes present in rumen fluid to generate quantitative rumen microbiome profiles. We observed large effects of the feed additives on the rumen microbiome profiles using multiple approaches, including linear mixed modeling, hierarchical clustering, and metagenomic predictions. The effect on the fecal microbiome profiles was not detectable using hierarchical clustering, but was significant in the linear mixed model and when metagenomic predictions were used, suggesting a more subtle effect of the diets on the lower gastrointestinal microbiome. A differential representation analysis (analogous to differential expression in RNA sequencing) showed significant overlap in the contigs (which are genome fragments representing different microorganism species) that were differentially represented between experiments. These similarities suggest that, despite the different additives used, the 2 diets assessed in this investigation altered the microbiomes of the samples in similar ways. Contigs that were differentially represented in both experiments were tested for associations with methane production in an independent set of animals. These animals were not treated with a methane-mitigating diet, but did show substantial natural variation in methane emission levels. The contigs that were significantly differentially represented in response to both dietary additives showed a significant enrichment for associations with methane production. This suggests that these methane-mitigating diets have altered the rumen microbiome toward naturally low methane-emitting microbial profiles. The contig sequences are predominantly new and include Faecalibacterium spp. The contigs we have identified here are potential biomarkers for low-methane-emitting cattle.
Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  methane; microbiome; rumen metagenome; sequencing

Mesh:

Substances:

Year:  2013        PMID: 23871375     DOI: 10.3168/jds.2013-6766

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  23 in total

1.  Prepartum and postpartum rumen fluid microbiomes: characterization and correlation with production traits in dairy cows.

Authors:  Fabio S Lima; Georgios Oikonomou; Svetlana F Lima; Marcela L S Bicalho; Erika K Ganda; Jose C de Oliveira Filho; Gustavo Lorenzo; Plamen Trojacanec; Rodrigo C Bicalhoa
Journal:  Appl Environ Microbiol       Date:  2015-02       Impact factor: 4.792

2.  Bacterial community composition and fermentation patterns in the rumen of sika deer (Cervus nippon) fed three different diets.

Authors:  Zhipeng Li; André-Denis G Wright; Hanlu Liu; Kun Bao; Tietao Zhang; Kaiying Wang; Xuezhe Cui; Fuhe Yang; Zhigang Zhang; Guangyu Li
Journal:  Microb Ecol       Date:  2014-09-25       Impact factor: 4.552

3.  Genomic predictions for enteric methane production are improved by metabolome and microbiome data in sheep (Ovis aries).

Authors:  Elizabeth M Ross; Ben J Hayes; David Tucker; Jude Bond; Stuart E Denman; Victor Hutton Oddy
Journal:  J Anim Sci       Date:  2020-10-01       Impact factor: 3.159

4.  Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle.

Authors:  Elizabeth M Ross; Peter J Moate; Leah C Marett; Ben G Cocks; Ben J Hayes
Journal:  PLoS One       Date:  2013-09-04       Impact factor: 3.240

5.  Response of the Rumen Microbiota of Sika Deer (Cervus nippon) Fed Different Concentrations of Tannin Rich Plants.

Authors:  Zhipeng Li; André-Denis G Wright; Hanlu Liu; Zhongyuan Fan; Fuhe Yang; Zhigang Zhang; Guangyu Li
Journal:  PLoS One       Date:  2015-05-08       Impact factor: 3.240

6.  Metagenomics of rumen bacteriophage from thirteen lactating dairy cattle.

Authors:  Elizabeth M Ross; Steve Petrovski; Peter J Moate; Ben J Hayes
Journal:  BMC Microbiol       Date:  2013-11-01       Impact factor: 3.605

Review 7.  High-throughput Methods Redefine the Rumen Microbiome and Its Relationship with Nutrition and Metabolism.

Authors:  Joshua C McCann; Tryon A Wickersham; Juan J Loor
Journal:  Bioinform Biol Insights       Date:  2014-06-08

8.  Two different bacterial community types are linked with the low-methane emission trait in sheep.

Authors:  Sandra Kittelmann; Cesar S Pinares-Patiño; Henning Seedorf; Michelle R Kirk; Siva Ganesh; John C McEwan; Peter H Janssen
Journal:  PLoS One       Date:  2014-07-31       Impact factor: 3.240

9.  Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics.

Authors:  Viktor Jonsson; Tobias Österlund; Olle Nerman; Erik Kristiansson
Journal:  BMC Genomics       Date:  2016-01-25       Impact factor: 3.969

10.  The rumen microbial metagenome associated with high methane production in cattle.

Authors:  R John Wallace; John A Rooke; Nest McKain; Carol-Anne Duthie; Jimmy J Hyslop; David W Ross; Anthony Waterhouse; Mick Watson; Rainer Roehe
Journal:  BMC Genomics       Date:  2015-10-23       Impact factor: 3.969

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