Holstein and Jersey Steers Differ in Rumen Microbiota and Enteric Methane Emissions Even Fed the Same Total Mixed Ration

Impact of rumen microbiome on cattle carcass traits

Rumen microbes are crucial in the anaerobic fermentation of plant polysaccharides to produce volatile fatty acids. However, limited information exists about the specific microbial species and strains in the rumen that affect carcass traits, and it is unclear whether there is a relationship between rumen metabolic functions and these traits. This study investigated the relationship between the rumen microbiome and carcass traits in beef cattle using 16S rRNA amplicon and shotgun sequencing. Metagenomic sequencing was used to compare the rumen microbiome between high-carcass weight (HW) and low-carcass weight (LW) cattle, and high-marbling (HM) and low-marbling (LM) cattle. Prokaryotic communities in the rumen of HW vs. LW and HM vs. LM were separated using 16S rRNA amplicon sequencing. Notably, shotgun metagenomic sequencing revealed that HW cattle had more methane-producing bacteria and ciliate protozoa, suggesting higher methane emissions. Additionally, variations were observed in the abundances of certain glycoside hydrolases and polysaccharide lyases involved in the ruminal degradation of plant polysaccharides between HW and LW. From our metagenome dataset, 807 non-redundant metagenome-assembled genomes (MAGs) of medium to high quality were obtained. Among these, 309 and 113 MAGs were associated with carcass weight and marbling, respectively.

Understanding the Diversity and Roles of the Ruminal Microbiome

The importance of ruminal microbiota in ruminants is emphasized, not only as a special symbiotic relationship with ruminants but also as an interactive and dynamic ecosystem established by the metabolites of various rumen microorganisms. Rumen microbial community is essential for life maintenance and production as they help decompose and utilize fiber that is difficult to digest, supplying about 70% of the energy needed by the host and 60-85% of the amino acids that reach the small intestine. Bacteria are the most abundant in the rumen, but protozoa, which are relatively large, account for 40-50% of the total microorganisms. However, the composition of these ruminal microbiota is not conserved or constant throughout life and is greatly influenced by the host. It is known that the initial colonization of calves immediately after birth is mainly influenced by the mother, and later changes depending on various factors such as diet, age, gender and breed. The initial rumen microbial community contains aerobic and facultative anaerobic bacteria due to the presence of oxygen, but as age increases, a hypoxic environment is created inside the rumen, and anaerobic bacteria become dominant in the rumen microbial community. As calves grow, taxonomic diversity increases, especially as they begin to consume solid food. Understanding the factors affecting the rumen microbial community and their effects and changes can lead to the early development and stabilization of the microbial community through the control of rumen microorganisms, and is expected to ultimately help improve host productivity and efficiency.

Galbibacter pacificus sp. nov., isolated from surface seawater of the western Pacific Ocean and transfer of Joostella marina to the genus Galbibacter as Galbibacter orientalis nom. nov. and emended description of the genus Galbibacter

Two Gram-stain-negative, non-motile, non-spore-forming, strictly aerobic and rod-shaped bacterial strains, CMA-7T and CAA-3, were isolated from surface seawater samples collected from the western Pacific Ocean. Phylogeny of 16S rRNA gene sequences indicated they were related to the genera Galbibacter and Joostella and shared 95.1, 90.9 and 90.8% sequence similarity with G. mesophilus Mok-17T, J. marina DSM 19592T and G. marinus ck-I2-15T, respectively. Phylogenomic analysis showed that the two strains, together with the members of the genera Galbibacter and Joostella, formed a monophyletic clade that could also be considered a monophyletic taxon. This distinctiveness was supported by amino acid identity and percentage of conserved proteins indices, phenotypic and chemotaxonomic characteristics and comparative genomics analysis. Digital DNA‒DNA hybridization values and average nucleotide identities between the two strains and their closest relatives were 18.0-20.8 % and 77.7-79.3 %, respectively. The principal fatty acids were iso-C15 : 0, iso-C17 : 0 3-OH, iso-C15 : 1 G, Summed Feature 3 (C16 : 1  ω7c/C16 : 1  ω6c or C16 : 1  ω6c/C16 : 1  ω7c), Summed Feature 9 (iso-C17 : 1  ω9c or C16 : 0 10-methyl), and C15 : 0 3-OH. The predominant respiratory quinone was MK-6. The polar lipids were phosphatidylethanolamine, aminolipid, aminophospholipid, phospholipid, phosphoglycolipid, glycolipid and unknown polar lipid. The genomic DNA G+C content of strains CMA-7T and CAA-3 was both 38.4 mol%. Genomic analysis indicated they have the potential to degrade cellulose and chitin. Based on the polyphasic evidence presented in this study, the two strains represent a novel species within the genus Galbibacter, for which the name Galbibacter pacificus sp. nov. is proposed. The type strain is CMA-7T (=MCCC M28999T = KCTC 92588T). Moreover, the transfer of Joostella marina to the genus Galbibacter as Galbibacter orientalis nom. nov. (type strain En5T = KCTC 12518T = DSM 19592T=CGMCC 1.6973T) is also proposed.

Effects of Italian ryegrass silage-based total mixed ration on rumen fermentation, growth performance, blood metabolites, and bacterial communities of growing Hanwoo heifers

This study utilized Italian ryegrass silage (IRGS) - based total mixed ration (TMR) as feedstuff and evaluated its effects on rumen fermentation, growth performance, blood parameters, and bacterial community in growing Hanwoo heifers. Twenty-seven Hanwoo heifers (body weight [BW], 225.11 ± 10.57 kg) were randomly allocated to three experimental diets. Heifers were fed 1 of 3 treatments as follows: TMR with oat, timothy, and alfalfa hay (CON), TMR with 19% of IRGS (L-IRGS), and TMR with 36% of IRGS (H-IRGS). Feeding high levels of IRGS (H-IRGS) and CON TMR to heifers resulted in a greater molar proportion of propionate in the rumen. The impact of different TMR diets on the BW, average daily gain, dry matter intake, and feed conversion ratio of Hanwoo heifers during the growing period did not differ (p > 0.05). Furthermore, the blood metabolites, total protein, albumin, aspartate aminotransferase, glucose, and total cholesterol of the heifers were not affected by the different TMR diets (p > 0.05). In terms of rumen bacterial community composition, 264 operational taxonomic units (OTUs) were observed across the three TMR diets with 240, 239, and 220 OTUs in CON, L-IRGS, and H-IRGS, respectively. IRGS-based diets increased the relative abundances of genera belonging to phylum Bacteroidetes but decreased the abundances of genus belonging to phylum Firmicutes compared with the control. Data showed that Bacteroidetes was the most dominant phylum, while Prevotella ruminicola was the dominant species across the three TMR groups. The relative abundance of Ruminococcus bromii in the rumen increased in heifers fed with high inclusion of IRGS in the TMR (H-IRGS TMR). The relative abundance of R. bromii in the rumen significantly increased when heifers were fed H-IRGS TMR while P. ruminicola increased in both L-IRGS and H-IRGS TMR groups. Results from the current study demonstrate that the inclusion of IRGS in the TMR is comparable with the TMR containing high-quality forage (CON). Thus, a high level of IRGS can be used as a replacement forage ingredient in TMR feeding and had a beneficial effect of possibly modulating the rumen bacterial community toward mainly propionate-producing microorganisms.

Exploring the rumen microbiota of Hu lambs in response to diet with paper mulberry

Paper mulberry (Broussonetia papyrifera), as a new woody forage with high-protein characteristic, is being widely used in ruminant feeding. However, little is known about the comprehensive microbiota picture of whole ruminal niches (liquid, solid, and epithelium) under paper mulberry diet. To gain a better understanding of feeding paper mulberry on the rumen microbiota, the effects of fresh paper mulberry, paper mulberry silage, or a conventional high-protein alfalfa silage on rumen fermentation products and microbiota in rumen niches of Hu lambs were studied. Forty-five Hu lambs were randomly divided into 3 treatments with 15 replicates in each treatment. No significant difference was observed among treatments in the average daily gain (ADG). The fresh paper mulberry treatment had lower (P < 0.05) pH and higher (P < 0.05) total volatile fatty acids (TVFA) compared with silage treatments, but the fermentation parameters did not show significant differences between paper mulberry silage and alfalfa silage treatments. The Shannon index did not show a significant difference (P < 0.05) among treatments except between fresh paper mulberry and alfalfa silage treatment in rumen epithelial niches. Butyrivibrio and Treponema were the predominant genera in the rumen epithelial fraction, while Prevotella and Rikenellaceae_RC9 dominated in both rumen liquid and solid fractions. These results indicated the paper mulberry supplement did not have distinct impact on the microbial diversity and growth performance compared with alfalfa silage, especially for paper mulberry silage, which might help us develop an alternative animal feeding strategy of replacing alfalfa with paper mulberry. KEY POINTS: • Feeding paper mulberry silage did not show significant impact on the growth performance compared with alfalfa silage treatment. • Feeding fresh paper mulberry reduced rumen pH value and increased total volatile fatty acid. • The microbial diversity did not show significant difference among treatments.

Quantifying methane emissions under field conditions under 2 different dairy production scenarios: Low-input versus high-input milk production

Livestock production systems with ruminants play a relevant role in the emission of the greenhouse gas CH₄, which is known to significantly contribute to global warming. Consequently, it is a major societal concern to develop strategies in mitigating such emissions. In addition to breeding toward low-emitting cows, management strategies could also help in reducing greenhouse gas emissions from dairy farms. However, information is required for appropriate decision making. To the best of our knowledge, this is the first study that considers different, already available equations to estimate CH₄ emissions of small-scale dairy farms in the mountain region, which largely differ from large dairy farms in the lowlands concerning management and production. For this study, 2 different production systems, both typical for small-scale dairy farming in mountain regions, were simultaneously run over 3 yr at an experimental farm as follows: (1) a high-input production system, characterized by intensive feeding with high amounts of external concentrates and maize silage, year-round housing, and high yielding Simmental cattle breed, and (2) a low-input production system, characterized by prevailing hay and pasture feeding and silage ban, thus covering most of the energy requirements by forage harvested on-farm and the use of the local Tyrolean Grey cattle breed. Results reveal that feeding management has a significant effect on the amount of CH₄ emissions. The low-input production system produced less CH₄ per cow and per day compared with the high-input production system. However, if calculated per kilogram of milk, the high-input scenario produced proportionally less CH₄ than the low-input one. Findings of this study highlight the potential to assess in a fast and cost-effective way the CH₄ emission in different dairy production systems. This information contributes to the debate about the future of sustainable milk production in mountain regions, where the production of feed resources is climatically constrained, and could be useful for breeding purposes toward lower CH₄-emissions.

- Invited Review - Assessment of the gastrointestinal microbiota using 16S ribosomal RNA gene amplicon sequencing in ruminant nutrition

The gastrointestinal (GI) tract of ruminants contains diverse microbes that ferment various feeds ingested by animals to produce various fermentation products, such as volatile fatty acids. Fermentation products can affect animal performance, health, and well-being. Within the GI microbes, the ruminal microbes are highly diverse, greatly contribute to fermentation, and are the most important in ruminant nutrition. Although traditional cultivation methods provided knowledge of the metabolism of GI microbes, most of the GI microbes could not be cultured on standard culture media. By contrast, amplicon sequencing of 16S rRNA genes can be used to detect unculturable microbes. Using this approach, ruminant nutritionists and microbiologists have conducted a plethora of nutritional studies, many including dietary interventions, to improve fermentation efficiency and nutrient utilization, which has greatly expanded knowledge of the GI microbiota. This review addresses the GI content sampling method, 16S rRNA gene amplicon sequencing, and bioinformatics analysis and then discusses recent studies on the various factors, such as diet, breed, gender, animal performance, and heat stress, that influence the GI microbiota and thereby ruminant nutrition.

Feeding incremental amounts of ground flaxseed: effects on diversity and relative abundance of ruminal microbiota and enteric methane emissions in lactating dairy cows

We evaluated the effects of incremental amounts of ground flaxseed (GFX) on diversity and relative abundance of ruminal microbiota taxa, enteric methane (CH₄) emissions, and urinary excretion of purine derivatives (PD) in lactating dairy cows in a replicated 4 × 4 Latin square design. Twenty mid-lactation Jersey cows were used in the study. Of these 20 cows, 12 were used for ruminal sampling, 16 for enteric CH₄ measurements, and all for spot urine collection. Each period lasted 21 d with 14 d for diet adaptation and 7 d for data and sample collection. Diets were formulated by replacing corn meal and soybean meal with 0%, 5%, 10%, and 15% of GFX in the diet's dry matter. Ruminal fluid samples obtained via stomach tubing were used for DNA extraction. Enteric CH₄ production was measured using the sulfur hexafluoride tracer technique. Diets had no effect on ruminal microbiota diversity. Similarly, the relative abundance of ruminal archaea genera was not affected by diets. In contrast, GFX decreased or increased linearly the relative abundance of Firmicutes (P < 0.01) and Bacteroidetes (P < 0.01), respectively. The relative abundance of the ruminal bacteria Ruminococcus (P < 0.01) and Clostridium (P < 0.01) decreased linearly, and that of Prevotella (P < 0.01) and Pseudobutyrivibrio (P < 0.01) increased linearly with feeding GFX. A tendency for a linear reduction (P = 0.055) in enteric CH₄ production (from 304 to 256 g/d) was observed in cows fed increasing amounts of GFX. However, neither CH₄ yield nor CH₄ intensity was affected by treatments. Diets had no effect on the urinary excretion of uric acid, allantoin, and total PD. Overall, feeding GFX decreased linearly the relative abundance of the ruminal bacterial genera Ruminococcus and Clostridium and enteric CH₄ production, but no change was seen for CH₄ yield and CH₄ intensity, or urinary excretion of total PD, suggesting no detrimental effect of GFX on microbial protein synthesis in the rumen.

Prevotella: A Key Player in Ruminal Metabolism

Ruminants are foregut fermenters that have the remarkable ability of converting plant polymers that are indigestible to humans into assimilable comestibles like meat and milk, which are cornerstones of human nutrition. Ruminants establish a symbiotic relationship with their microbiome, and the latter is the workhorse of carbohydrate fermentation. On the other hand, during carbohydrate fermentation, synthesis of propionate sequesters H, thus reducing its availability for the ultimate production of methane (CH4) by methanogenic archaea. Biochemically, methane is the simplest alkane and represents a downturn in energetic efficiency in ruminants; environmentally, it constitutes a potent greenhouse gas that negatively affects climate change. Prevotella is a very versatile microbe capable of processing a wide range of proteins and polysaccharides, and one of its fermentation products is propionate, a trait that appears conspicuous in P. ruminicola strain 23. Since propionate, but not acetate or butyrate, constitutes an H sink, propionate-producing microbes have the potential to reduce methane production. Accordingly, numerous studies suggest that members of the genus Prevotella have the ability to divert the hydrogen flow in glycolysis away from methanogenesis and in favor of propionic acid production. Intended for a broad audience in microbiology, our review summarizes the biochemistry of carbohydrate fermentation and subsequently discusses the evidence supporting the essential role of Prevotella in lignocellulose processing and its association with reduced methane emissions. We hope this article will serve as an introduction to novice Prevotella researchers and as an update to others more conversant with the topic.

Understanding variability and repeatability of enteric methane production in feedlot cattle

Breeding ruminants for low methane (CH4) emissions can be permanent and cumulative, but requires a better understanding of the variability of CH4 production among animals to accurately assess low-CH4 phenotypes. Our objectives were to: 1) investigate the variation in CH4 production among and within growing beef cattle, 2) identify low-CH4 emitters, and 3) examine relationships between CH4 production and intake, feeding behavior, growth, and rumen fermentation. Crossbred beef heifers (n=77; body weight=450 kg) were allocated to 3 pens and offered a finishing diet of 90% concentrate and 10% silage (dry matter (DM) basis). The study was conducted over 3 consecutive 6-week periods (126 days). GrowSafe bunks measured individual animal DM intake (DMI) and rumen fluid was sampled orally each period. A GreenFeed system measured individual animal emissions for 2 weeks/period. Methane production was calculated by animal within period using visits that were ≥3 min with fluxes compiled into six 4-h blocks corresponding to time of day, and averaged over blocks to obtain an average daily emission for the period. Animals with &lt;12 visits and &lt;5 blocks were omitted for the period and animals with ≥2 periods of complete CH4 data were used in the final analysis (n=52). Animals were ranked based on CH4 yield (g/kg DMI) from low to high, and grouped as Very-low (≤10% of animals), Low (11-25%), Intermediate (26-74%), High (75-89%), and Very high (≥90%) emitters (mean ± SD, 12.6 ± 2.16). The CH4 yield was 16% less (P&lt;0.05) for Very-low compared with Intermediate animals due to lower CH4 production (g/d, P&lt;0.05), with no differences in DMI (P&gt;0.05). However, the period × grouping interaction (P&lt;0.001) for CH4 yield indicated that the ranking of animals changed over time, although there were no extreme changes in rankings. Total VFA concentration decreased as CH4 yield decreased, but molar proportions of VFA remained unchanged, suggesting lower extent of ruminal digestion rather than a shift in fermentation. There were no differences in feeding behavior or average daily gain among groupings (P&gt;0.05). The between-animal coefficient of variation in CH4 yield of 17.3% enabled identification of low CH4-emmitting finishing beef cattle. However, accurate selection of low CH4-emitting animals should be based on repeated CH4 measurements over the production cycle.

Effects of high concentrate rations on ruminal fermentation and microbiota of yaks

Ruminal microflora is closely correlated with the ruminant’s diet. However, information regarding the effect of high concentrate diets on rumen microflora in yaks is lacking. In the current study, 24 healthy male yaks were randomly assigned to two groups, each fed with different diets: less concentrate (LC; concentrate: coarse = 40: 60) and high concentrate (HC; concentrate: coarse = 80: 20) diets. Subsequently, a 21-day feeding trial was performed with the yaks, and rumen fluid samples were collected and compared using 16 s rRNA sequencing. The results showed that NH3-N, total VFA, acetate, butyrate, isobutyrate, and isovalerate were significantly higher in the HC group than that in the LC group (p &lt; 0.05), while microbial diversity and richness were significantly lower in the HC group (p &lt; 0.05). Principal coordinate analysis indicated that rumen microflora was significantly different in LC and HC groups (p &lt; 0.05). In the rumen, phyla Firmicutes and Bacteroidota were the most abundant bacteria, with Firmicutes being more abundant, and Bacteroidota being less abundant in the HC group than those found in the LC group. Christensenellaceae_R-7_group and Prevotella are the highest abundant ones at the genus level. The relative abundance of Acetitomaculum, Ruminococcus, and Candidatus_Saccharimonas were significantly higher in the HC group than that in the LC group (p &lt; 0.05), while the relative abundance of Olsenella was significantly lower in the HC group than in the LC group (p &lt; 0.05). Compared to the LC group, the relative abundance of Prevotella, Ruminococcus, and Candidatus_Saccharimonas was significantly higher in the HC group. The relative abundances of Prevotella, Prevotellaceae_UCG-003, Olsenella, Ruminococcus, Acetitomaculum, Candidatus_Saccharimonas, and NK4A214_group were correlated with ruminal fermentation parameters (p &lt; 0.05). Furthermore, PICRUSt 2 estimation indicated that microbial genes associated with valine, leucine, and isoleucine biosynthesis were overexpressed in the rumen microflora of yaks in the HC group (p &lt; 0.05). Conclusively, our results suggest that high concentrate diets affect the microflora composition and fermentation function in yak rumen. The present findings would provide new insights into the health of yaks under high concentrate feeding conditions and serve as a potent reference for the short-term fattening processes of yaks.

Dietary forage to concentrate ratios impact on yak ruminal microbiota and metabolites

To improve the rumen fermentation function and growth performance of yaks (Bos grunniens), better understanding of the effect of different dietary forage to concentrate ratios on rumen microbiota and metabolites is needed. In the present study, three diets with different dietary forage to concentrate ratios (50:50, 65:35, and 80:20) were fed to 36 housed male yaks. The changes in the distribution of rumen microorganisms and metabolites and the interactions between them were studied by 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC–MS). The diversity and richness of microorganisms in the rumen varied according to diet. The most abundant phyla were Firmicutes and Bacteroidetes. Firmicutes was the most abundant in the C50 group, and the relative abundance of Bacteroidetes was significantly lower in the C65 group than in the C80 group (p < 0.05). The Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, and Methanobrevibacter had the highest relative abundances at the genus level. Among them, Christensenellace_R-7_group had the highest relative abundance in the C50 group. The Rikenellaceae_RC9_gut_group was significantly abundant in the C80 group compared with the C50 group. The Methanobrevibacter content was higher in the C65 group than in the other two groups. Both the concentration and metabolic pathways of rumen metabolites were influenced by the dietary concentrate ratio; lipids, lipid-like molecules, organic acid metabolites, and organic oxide-related metabolites differed between the groups. Significant changes were found for six metabolic pathways, including arginine and proline metabolism; glycine, serine, and threonine metabolism; glyoxylate and dicarboxylate metabolism; arginine biosynthesis; glycerophospholipid metabolism; glycerolipid metabolism; and nitrogen metabolism.

Breed and Season-Specific Methane Conversion Factors Influence Methane Emission Factor for Enteric Methane of Dairy Steers

This study determined the breed and the season-specific methane (CH4) conversion factor (Ym) and the emission factor (EF) for the enteric CH4 of dairy steers. The Ym values for Holstein and Jersey steers at different seasons were calculated using the IPCC 2006 equations by incorporating the input and/or output value of the chemical composition of feed, methane production, methane yield, dry matter intake, and methane energy emission. EFs were categorized into five types depending on the 2019 refinement to the IPCC 2006 Tier 2 equations used. EFA was calculated from Equation 10.21A (New), while other EFs were estimated from the Equation 10.21 which were designated according to the gross energy intake (GEI) and Ym as EFB (GEIi and Ym), EFC (GEIii and Ym), EFD (GEIii and Ym (6.3)), and EFE (GEIii and Ym (4.0)). The calculated overall Ym for Holstein and Jersey steers were 4.90 and 7.49, while the recorded EF of group EFA were 56.44 and 67.42 kg CH4/head/year for Holstein and Jersey steers, respectively. For Holstein steers, EFD was overestimated (75.91 vs. 48.20~58.15), while in Jersey steers, the EFF underestimated the EF (kg CH4/head/year) compared to others (40.15 vs. 63.24~73.28) (p < 0.05). Mixed analysis revealed that the breed influenced EFs of all the EF groups, while the season, and the breed × the season influenced EFs of group EFC, EFD, and EFF. The overall results recommended using the breed-specific Ym for the estimation of the EF for enteric methane in dairy steers.

Fecal microbiome profiles of neonatal dairy calves with varying severities of gastrointestinal disease

Gastrointestinal disease (GI) is the most common illness in pre-weaned dairy calves. Studies have associated the fecal microbiome composition with health status, but it remains unclear how the microbiome changes across different levels of GI disease and breeds. Our objective was to associate the clinical symptoms of GI disease with the fecal microbiome. Fecal samples were collected from calves (n = 167) of different breeds (Holstein, Jersey, Jersey-cross and beef-cross) from 4-21 d of age. Daily clinical evaluations assessed health status. Calves with loose or watery feces were diagnosed with diarrhea and classified as bright-sick (BS) or depressed-sick (DS) according to behavior. Calves with normal or semiformed feces and no clinical illness were classified as healthy (H). One hundred and three fecal samples were obtained from consistently healthy calves and 64 samples were from calves with diarrhea (n = 39 BS; n = 25 DS). The V3-V4 region of 16S rRNA gene was sequenced and analyzed. Differences were identified by a linear-mixed effects model with a negative binomial error. DS and Jersey calves had a higher relative abundance of Streptococcus gallolyticus relative to H Holstein calves. In addition, DS calves had a lower relative abundance of Bifidobacterium longum and an enrichment of Escherichia coli. Species of the genus Lactobacillus, such as an unclassified Lactobacillus, Lactobacillus reuteri, and Lactobacillus salivarius were enriched in calves with GI disease. Moreover, we created a model to predict GI disease based on the fecal microbiome composition. The presence of Eggerthella lenta, Bifidobacterium longum, and Collinsella aerofaciens were associated with a healthy clinical outcome. Although lactobacilli are often associated with beneficial probiotic properties, the presence of E. coli and Lactobacillus species had the highest coefficients positively associated with GI disease prediction. Our results indicate that there are differences in the fecal microbiome of calves associated with GI disease severity and breed specificities.

Feeding Systems and Host Breeds Influence Ruminal Fermentation, Methane Production, Microbial Diversity and Metagenomic Gene Abundance

Our previous research revealed the advantages of separate feeding (SF) systems compared to total mixed ration (TMR) in terms of ruminal methane (CH₄) production. The purpose of this experiment was to confirm the advantage of SF as a nutritional strategy for CH₄ mitigation, and to determine the effects of different feeding systems (TMR and SF) on the rumen microbiome and associated metagenome of two different breeds and on CH₄ emissions. We randomly allocated four Holstein (305 ± 29 kg) and four Hanwoo steers (292 ± 24 kg) to two groups; the steers were fed a commercial concentrate with tall fescue (75:25) as TMR or SF, in a crossover design (two successive 22-day periods). Neither feeding systems nor cattle breeds had an effect on the total tract digestibility of nutrients. The TMR feeding system and Hanwoo steers generated significantly more CH₄ (P < 0.05) and had a higher yield [g/d and g/kg dry matter intake (DMI)] compared to the SF system and Holstein steers. A larger rumen acetate:propionate ratio was observed for the TMR than the SF diet (P < 0.05), and for Hanwoo than Holstein steers (P < 0.001), clearly reflecting a shift in the ruminal H₂ sink toward CH₄ production. The linear discriminant analysis (LDA) effect size (LEfSe) revealed a greater abundance (α < 0.05 and LDA > 2.0) of operational taxonomic units (OTUs) related to methanogenesis for Hanwoo steers compared to Holstein steers. Kendall’s correlation analysis revealed wide variation of microbial co-occurrence patterns between feeding systems, indicating differential H₂ thermodynamics in the rumen. A metagenome analysis of rumen microbes revealed the presence of 430 differentially expressed genes, among which 17 and 27 genes exhibited positive and negative associations with CH₄ production, respectively (P < 0.001). A strong interaction between feeding system and breed was observed for microbial and metagenomic abundance. Overall, these results suggest that the TMR feeding system produces more CH₄, and that Hanwoo cattle are higher CH₄ emitters than SF diet and Holstein cattle, respectively. Interestingly, host-associated microbial interactions differed within each breed depending on the feeding system, which indicated that breed-specific feeding systems should be taken into account for farm management.