Metagenomic analysis reveals microbial drivers of heat resistance in dairy cattle

Abstract

Heat stress poses a significant challenge to dairy cattle, leading to adverse physiological effects, reduced milk yield, impaired reproduction performance and economic losses. This study investigates the role of the rumen microbiome in mediating heat resistance in dairy cows. Using the entropy-weighted TOPSIS method, we classified 120 dairy cows into heat-resistant (HR) and heat-sensitive (HS) groups based on physiological and biochemical markers, including rectal temperature (RT), respiratory rate (RR), salivation index (SI) and serum levels of potassium ion (K⁺), heat shock protein 70 (HSP70) and cortisol. Metagenomic sequencing of rumen fluid samples revealed distinct microbial compositions and functional profiles between the two groups. HR cows exhibited a more cohesive and functionally stable microbiome, dominated by taxa such as Ruminococcus flavefaciens and Succiniclasticum, which are key players in fiber degradation and short-chain fatty acid production. Functional analysis highlighted the enrichment of the pentose phosphate pathway (PPP) in HR cows, suggesting a metabolic adaptation that enhances oxidative stress management. In contrast, HS cows showed increased activity in the tricarboxylic acid (TCA) cycle, pyruvate metabolism and other energy-intensive pathways, indicating a higher metabolic burden under heat stress. These findings underscore the critical role of the rumen microbiome in modulating heat resistance and suggest potential microbiome-based strategies for improving dairy cattle resilience to climate change.

Keywords: Ruminococcus flavefaciens; Dairy cattle; Heat resistance; Pentose phosphate pathway; Rumen microbiome.

Fig. 1

A Average daily values of temperature, humidity, and temperature-humidity index (THI) in the cowshed during the experiment. The x-axis represents the time of heat resistance trait measurement; the y-axis represents environmental temperature, relative humidity, and calculated THI recorded by the temperature-humidity data logger. B Changes in average MP, RF, and FT of cows during the thermoneutral condition (TN, May to June) and non-thermoneutral condition (NTN, July to August), MP = milk production; RF = rumination frequency; FT = feeding time. The differences between groups were analyzed using an independent sample t-test, and **** represents P < 0.0001. Error bars indicate the standard error of the mean (SEM). C The effect of the THI on RT, RR, and SI. RT = rectal temperature; RR = respiration rate; SI = salivation index. The 95% confidence and prediction bands are shown. Pearson’s r = Pearson correlation coefficient, where the absolute value indicates the strength of the correlation

Fig. 2

The analysis of physiological and biochemical markers in HR and HS cows. A Rectal temperature, B Respiratory rate, C Salivation index, D serum levels of potassium ion (K⁺), (E) heat shock protein 70 (HSP70) and (F) Cortisol. HR = heat-resistant cows; HS = heat-sensitive cows. * represents P < 0.05, significant difference; **** represents P < 0.0001, extremely significant difference

Fig. 3

A The top 20 phylum level microbial classes of different samples. B Venn diagram showing the composition and relative abundance of rumen microorganisms. C PLS-DA analysis based on taxonomic alignment of rumen archaea, bacteria, fungi, and virus. D Alpha diversity analysis of rumen microbiota in HR and HS cows. Alpha diversity indices include ACE index, Chao1 index, Shannon index, and Simpson index. Different groups are represented by different colors, with the x-axis showing group names and the y-axis showing diversity index values. The numbers above indicate the P-values obtained from the tests, where P < 0.05 indicates significant differences between groups, and P < 0.01 indicates highly significant differences between groups

Fig. 4

Differences in rumen microbial composition between cows with different heat resistance. A The main components of rumen microbes at the phylum level in HR and HS cows; B LEfSe analysis of differential species; C Random forest analysis of microbial differences between groups; D Changes in the expression of lactate-producing bacteria between HS and HR cows

Fig. 5

Visualization of significant differences in KEGG orthologous groups (P < 0.05) assigned to the"Microbial metabolism in diverse environments"pathway between HR and HS cows. Red bold lines indicate pathways enriched with differential KOs

Fig. 6

Changes in the rumen microbial metagenome-encoded carbohydrate-active enzymes (CAZymes) in cows with different heat resistance after exposure to high temperatures. A CAZymes encoded by the rumen microbial metagenome; GH = Glycoside Hydrolases; GT = Glycosyl Transferases; PL = Polysaccharide Lyases; CE = Carbohydrate Esterases; AA = Auxiliary Activities; CBM = Carbohydrate-Binding Modules. B The top 30 most abundant CAZymes family members by relative abundance. C PLS-DA analysis of CAZymes families. D ACE diversity analysis of CAZymes families

Fig. 7

Key microbial and functional correlation analysis based on different heat resistance levels. The rumen microbes and KO functions regulated by heat resistance show significant differences (P < 0.05). The width of the connecting lines indicates the extent to which a particular bacterium contributes to a specific function