176 Metagenomic analysis of the influence of thymol on rumen microbial metabolic pathways and enzyme profiles in beef steers.

Abstract Essential oils (EO) have potential to reduce methanogenesis and modify rumen functioning. However, bioactive compounds in EO are not standardized, often leading to inconsistencies in research; these inconsistencies can be addressed by supplementing known amounts of the bioactive compounds, terpenes and terpenoids. As terpenes modulate rumen function through antimicrobial activities, efficacious doses that do not negatively affect microbes should be established. The objective of this research was to determine the impact of increasing thymol doses on rumen microbial genomic potential through whole genome shotgun sequencing. Four ruminally cannulated steers were used in a 4×4 Latin Square design with four 28-d periods. Steers received one of four treatments: 0 (CON), 120 (120-T), 240 (240-T), and 480 (480-T) mg thymol/kg forage intake, delivered on alfalfa cubes in addition to ad libitum forage. Rumen contents were collected on d-14 of each period, the liquid fraction was retained, and DNA was extracted. Raw sequence reads were generated using the Illumina NovaSeq (2×150) platform and underwent a bioinformatics pipeline including quality control, contig assembly, and coding sequence (CDS) identification and annotation; 50,479,118 contigs coding for 68,879,836 CDS were identified. Data were assessed for orthogonal contrasts using R statistical software. There were no linear or quadratic effects of thymol dose on Carbohydrate-Active Enzyme (CAZyme) family representation. For analysis of Clusters of Orthologous Groups (COG) of proteins, there was a quadratic effect (P=0.03) on the functional classification of predicted proteins involved in RNA processing and modification such that CON had the lowest relative abundance (0.049%), which increased through 120-T (0.055%) and plateaued for 240-T and 480-T (both 0.062%). There were also statistical trends (P≤0.09) for treatment to quadratically impact the functional classification categories coenzyme transport and metabolism (peak for CON at 3.5%), extracellular structures (peak for 240-T at 0.003%), and cytosketelon (peak for 240-T at 0.05%). Although not affected by treatment, the most abundant classification was function unknown, averaging 24% across treatment. Genes encoding methyl-coenzyme M reductase (MCR), an enzyme that catalyzes the final step in methanogenesis, were detected across all treatments. For CON, MCR genes were detected at 23.8% relative distribution, which was upregulated for 120-T and 480-T (both 27.9%) and downregulated for 240-T (20.5%). The pmoA gene, which encodes a subunit of an enzyme that catalyzes methane oxidation, had 29.3% relative distribution for CON, was downregulated for 120-T (22.0%) and 480-T (9.8%), and was upregulated for 240-T (39.0%). These data suggest that providing thymol at 240 mg/kg intake may have anti-methanogenic potential as MCR genes were downregulated and pmoA genes were upregulated. As we did not detect compelling treatment differences for CAZymes or COGs, it is likely that proteins with undefined functional classification are responsible for modulating methane metabolic pathways that were affected by thymol.