Abstract #W153
Section: Ruminant Nutrition (posters)
Session: Ruminant Nutrition: Ruminal Fermentation and Gas Production
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
Session: Ruminant Nutrition: Ruminal Fermentation and Gas Production
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
# W153
Multi-kingdom microbial shifts and associated functional variation in the rumen of lactating dairy cows: I. Effect of dietary energy source and level.
T. Park*1, L. Ma2, Y. Ma2, X. Zhou2, D. Bu2,3, Z. Yu1, 1Department of Animal Sciences, The Ohio State University, Columbus, OH, 2State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China, 3CAAS-ICRAF Joint Lab on Agroforestry and Sustainable Animal Husbandry, Beijing, China.
Key Words: rumen microbiota, energy level, corn processing method
Multi-kingdom microbial shifts and associated functional variation in the rumen of lactating dairy cows: I. Effect of dietary energy source and level.
T. Park*1, L. Ma2, Y. Ma2, X. Zhou2, D. Bu2,3, Z. Yu1, 1Department of Animal Sciences, The Ohio State University, Columbus, OH, 2State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China, 3CAAS-ICRAF Joint Lab on Agroforestry and Sustainable Animal Husbandry, Beijing, China.
The effects of dietary treatments on the rumen microbiota can vary among the multi-kingdoms of rumen microbes. This study investigated the effect of the source and level of dietary energy on rumen bacteria, methanogens, protozoa and fungi in the rumen of lactating dairy cows. A 2 × 2 factorial design resulted in 4 dietary treatments: low and high energy levels (LE: 1.52–1.53; and HE: 1.71–1.72 Mcal) and 2 energy sources [finely ground corn (GC) and steam-flaked corn (SFC)]. We used a replicated 4 × 4 Latin square design using 8 primiparous Chinese Holstein cows with each period lasting for 21 d. The rumen microbiota was analyzed through sequencing of amplicons of kingdom-specific phylogenetic markers (16S rRNA gene for bacteria and methanogens, 18S rRNA gene for protozoa, and ITSI for fungi) followed with subsequent sequence analysis using the QIIME2 pipeline. GC resulted in a higher prokaryotic (bacterial and methanogen) species richness and phylogenetic diversity than SFC, and for the eukaryotic (protozoa and fungi) microbiota, LE led to significantly higher values of the above measurements than HE. A large number of phyla and genera in all the kingdoms differed in relative abundance between the 2 dietary energy levels, while only Dasytricha and Cryptococcus were differentially abundant between the 2 corn processing methods. Based on the prokaryotic amplicon sequencing variants from all the samples, functional profiles predicted using PICRUSt2 differed significantly between LE and HE. FishTaco analysis identified Selenomonas and Ruminococcus as the potential taxonomic drivers of pyruvate and methane metabolism in LE and HE, respectively, while Butyrivibrio and Coprococcus exhibited the opposite relationship with those functions, particularly in HE. There were strong co-occurrence patterns among the genera of different kingdoms suggesting possible metabolic interactions in the rumen. These results suggest that dietary energy level can significantly affect rumen microbiota across all the kingdoms.
Key Words: rumen microbiota, energy level, corn processing method