Rumen Bacteria and Serum Metabolites Predictive of Feed Efficiency Phenotypes in Beef Cattle

Brooke A Clemmons,Dallas R Donohoe,Phillip R Myer,James Gaffney,Joshua B Powers,Shawn R Campagna,Brynn H Voy,Mallory M Embree,Cameron Martino

doi:10.1038/s41598-019-55978-y

Brooke A Clemmons, Dallas R Donohoe + Show 7 more

Open Access

https://doi.org/10.1038/s41598-019-55978-y

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Abstract

The rumen microbiome is critical to nutrient utilization and feed efficiency in cattle. Consequently, the objective of this study was to identify microbial and biochemical factors in Angus steers affecting divergences in feed efficiency using 16S amplicon sequencing and untargeted metabolomics. Based on calculated average residual feed intake (RFI), steers were divided into high- and low-RFI groups. Features were ranked in relation to RFI through supervised machine learning on microbial and metabolite compositions. Residual feed intake was associated with several features of the bacterial community in the rumen. Decreased bacterial α- (P = 0.03) and β- diversity (P < 0.001) was associated with Low-RFI steers. RFI was associated with several serum metabolites. Low-RFI steers had greater abundances of pantothenate (P = 0.02) based on fold change (high/low RFI). Machine learning on RFI was predictive of both rumen bacterial composition and serum metabolomic signature (AUC ≥ 0.7). Log-ratio proportions of the bacterial classes Flavobacteriia over Fusobacteriia were enriched in low-RFI steers (F = 6.8, P = 0.01). Reductions in Fusobacteriia and/or greater proportions of pantothenate-producing bacteria, such as Flavobacteriia, may result in improved nutrient utilization in low-RFI steers. Flavobacteriia and Pantothenate may potentially serve as novel biomarkers to predict or evaluate feed efficiency in Angus steers.

Highlights

Rumen microbes produce metabolites that are released into the rumen lumen and can be absorbed through the rumen epithelium or through the epithelium in the lower gastrointestinal tract[4]
In order to address these critical knowledge gaps, we used a combination of microbial genomics, metabolomics, and bioinformatics to further define variations in feed efficiency as determined by the divergence in residual feed intake (RFI)
The rumen microbiome contributes significantly to the breakdown of low-quality feedstuffs, such as forages, and may be responsible for much of the variation observed in ruminant feed efficiency phenotypes[10]

Summary

Introduction

Rumen microbes produce metabolites that are released into the rumen lumen and can be absorbed through the rumen epithelium or through the epithelium in the lower gastrointestinal tract[4]. Associations between the rumen microbiome and physiological changes in the host have been identified[8,9], the mechanisms driving these changes are still unknown and whether foundational, or keystone, species are responsible for the divergences in feed efficiency and other phenotypes. In order to address these critical knowledge gaps, we used a combination of microbial genomics, metabolomics, and bioinformatics to further define variations in feed efficiency as determined by the divergence in residual feed intake (RFI). Determination of the complex associations and networks between the rumen microbiome, host metabolome, and differences in host phenotype can be facilitated by novel utilization of bioinformatics and machine learning to discover physiological patterns and microbial factors. We analyzed the relationships among RFI, the rumen bacterial community, and the serum metabolome

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