RESUMEN
Heat stress (HS) damages livestock by adversely affecting physiological and immunological functions. However, fundamental understanding of the metabolic and immunological mechanisms in animals under HS remains elusive, particularly in steers. To understand the changes on metabolic and immune responses in steers under HS condition, we performed RNA-sequencing and proton nuclear magnetic resonance spectroscopy-based metabolomics on HS-free (THI value: 64.92 ± 0.56) and HS-exposed (THI value: 79.13 ± 0.56) Jersey steer (n = 8, body weight: 559.67 ± 32.72 kg). This study clarifies the metabolic changes in 3 biofluids (rumen fluid, serum, and urine) and the immune responses observed in the peripheral blood mononuclear cells of HS-exposed steers. This integrated approach allowed the discovery of HS-sensitive metabolic and immunological pathways. The metabolomic analysis indicated that HS-exposed steers showed potential HS biomarkers such as isocitrate, formate, creatine, and riboflavin (P < 0.05). Among them, there were several integrative metabolic pathways between rumen fluid and serum. Furthermore, HS altered mRNA expression and immune-related signaling pathways. A meta-analysis revealed that HS decreased riboflavin metabolism and the expression of glyoxylate and dicarboxylate metabolism-related genes. Moreover, metabolic pathways, such as the hypoxia-inducible factor-1 signaling pathway, were downregulated in immune cells by HS (P < 0.05). These findings, along with the datasets of pathways and phenotypic differences as potential biomarkers in steers, can support more in-depth research to elucidate the inter-related metabolic and immunological pathways. This would help suggest new strategies to ameliorate the effects of HS, including disease susceptibility and metabolic disorders, in Jersey steers.
RESUMEN
Previous studies have focused on the rumen microbiome and enteric methane (CH4) emissions in dairy cows, yet little is known about steers, especially steers of dairy breeds. In the present study, we comparatively examined the rumen microbiota, fermentation characteristics, and CH4 emissions from six non-cannulated Holstein (710.33 ± 43.02 kg) and six Jersey (559.67 ± 32.72 kg) steers. The steers were fed the same total mixed ration (TMR) for 30 days. After 25 days of adaptation to the diet, CH4 emissions were measured using GreenFeed for three consecutive days, and rumen fluid samples were collected on last day using stomach tubing before feeding (0 h) and 6 h after feeding. CH4 production (g/d/animal), CH4 yield (g/kg DMI), and CH4 intensity (g/kg BW0.75) were higher in the Jersey steers than in the Holstein steers. The lowest pH value was recorded at 6 h after feeding. The Jersey steers had lower rumen pH and a higher concentration of ammonia-nitrogen (NH3-N). The Jersey steers had a numerically higher molar proportion of acetate than the Holstein steers, but the opposite was true for that of propionate. Metataxonomic analysis of the rumen microbiota showed that the two breeds had similar species richness, Shannon, and inverse Simpson diversity indexes. Principal coordinates analysis showed that the overall rumen microbiota was different between the two breeds. Both breeds were dominated by Prevotella ruminicola, and its highest relative abundance was observed 6 h after feeding. The genera Ethanoligenens, Succinivibrio, and the species Ethanoligenens harbinense, Succinivibrio dextrinosolvens, Prevotella micans, Prevotella copri, Prevotella oris, Prevotella baroniae, and Treponema succinifaciens were more abundant in Holstein steers while the genera Capnocytophaga, Lachnoclostridium, Barnesiella, Oscillibacter, Galbibacter, and the species Capnocytophaga cynodegmi, Galbibacter mesophilus, Barnesiella intestinihominis, Prevotella shahii, and Oscillibacter ruminantium in the Jersey steers. The Jersey steers were dominated by Methanobrevibacter millerae while the Holstein steers by Methanobrevibacter olleyae. The overall results suggest that sampling hour has little influence on the rumen microbiota; however, breeds of steers can affect the assemblage of the rumen microbiota and different mitigation strategies may be needed to effectively manipulate the rumen microbiota and mitigate enteric CH4 emissions from these steers.