Beef cattle metabiomes and their relationships with economically important phenotypes

Abstract Text: The selection and optimization of economically important phenotypes, i.e. feed efficiency, in cattle has long been an effort devoted to host genetics, management, and diet.  Feed costs remain the largest variable cost in beef production, and consequently, the improvement of feed efficiency is of significant economic and environmental importance.  However, the various microbial populations within the gastrointestinal tract as a whole are critical to the overall well-being of the host and need to be examined when determining the interplay between host and non-host factors affecting feed efficiency.  To address this, we examined the microbial communities within the rumen and locations throughout the lower gastrointestinal tract (GIT) from steers differing in feed efficiency. Within two contemporary groups of steers, individual feed intake (FI) and body weight (BW) gain were determined from animals fed the same ration.  Within contemporary group, BW was regressed on FI and the four most extreme steers within each Cartesian quadrant were sampled (n=16/group).  Bacterial 16S rRNA gene amplicons were sequenced from the GIT content using next-generation sequencing technology. Although no differences were detected by bacterial diversity and richness metrics, changes in the relative abundances of microbial populations and operational taxonomic units did reveal differences between feed efficiency groups.  These studies suggest the GIT microbiome differs at the 16S level in cattle that vary in efficiency of weight gain.  It is not clear whether host factors are driving changes in the microbiome or changes in the microbiome are contributing to differences in feed efficiency.  Partially funded by National Institute of Food and Agriculture Grant 2011-68004-30214 National Program for Genetic Improvement of Feed Efficiency in Beef Cattle.  USDA is an equal opportunity provider and employer.

Keywords: feed efficiency, microbiome, 16S rRNA