AUTHOR=Soltis Macey P. , Henniger Madison T. , Egert-McLean Amanda M. , Voy Brynn H. , Moorey Sarah E. , Schnieder Liesel G. , Shepherd Elizabeth A. , Christopher Courtney , Campagna Shawn R. , Smith Joe S. , Mulon Pierre-Yves , Anderson David E. , Myer Phillip R. TITLE=Rumen biogeographical regions and their impact on microbial and metabolome variation JOURNAL=Frontiers in Animal Science VOLUME=4 YEAR=2023 URL=https://www.frontiersin.org/journals/animal-science/articles/10.3389/fanim.2023.1154463 DOI=10.3389/fanim.2023.1154463 ISSN=2673-6225 ABSTRACT=

The rumen microbiome is a complex microbial network critical to the health and nutrition of its host, due to their inherent ability to convert low-quality feedstuffs into energy. In rumen microbiome studies, samples from the ventral sac are most often collected because of the ease of access and repeatability. However, anatomical musculature demarcates the rumen into five sacs (biogeographical regions), which may support distinct microbial communities. The distinction among the microbes may generate functional variation among the rumen microbiome, thus, specialized tasks within different sacs. The objective of this study was to determine the rumen liquid metabolome and epimural, planktonic, and fiber-adherent bacterial communities among each rumen biogeographical region. It was hypothesized that differences in bacterial species and metabolome would occur due to differing anatomy and physiology associated with the respective regions. To assess this variation, epithelial and content microbial-associated communities were evaluated, as well as the metabolites among various rumen biogeographical regions. A total of 17 cannulated Angus cows were utilized to examine the fiber-adherent (solid fraction), planktonic (liquid fraction), and epimural microbial communities from the cranial, dorsal, caudodorsal blind, caudoventral blind, and ventral sacs. Metagenomic DNA was extracted and sequenced from the hypervariable V4 region of the 16S rRNA gene. Reads were processed using packages ‘phyloseq’ and ‘dada2’ in R. Untargeted metabolomics were conducted on rumen liquid from each sac using UHPLC-HRMS and analyzed in MetaboAnalyst 5.0. An analysis of variance (ANOVA) revealed 13 significant differentially abundant metabolites with pairwise comparisons against the five rumen sacs (P < 0.05). Within the bacterial communities, neither alpha nor beta diversity determined significance against the rumen sacs (P > 0.05), although there was significance against the fraction types (P < 0.05). Utilizing multivariable association analysis with MaAslin2, there were significant differential abundances found in fraction type × location (P < 0.05). Knowledge of similarities among fiber-adherent microbial communities provides evidence that single sac sampling is sufficient for this fraction. However, future projects focusing on either planktonic or epimural fractions may need to consider multiple rumen sac sampling to obtain the most comprehensive analysis of the rumen. Defining these variabilities, especially among the rumen epimural microbiome, are critical to define host-microbiome interactions.