Ruminal resistome of dairy cattle is individualized and the resistotypes are associated with milking traits

Abstract

Background: Antimicrobial resistance is one of the most urgent threat to global public health, as it can lead to high morbidity, mortality, and medical costs for humans and livestock animals. In ruminants, the rumen microbiome carries a large number of antimicrobial resistance genes (ARGs), which could disseminate to the environment through saliva, or through the flow of rumen microbial biomass to the hindgut and released through feces. The occurrence and distribution of ARGs in rumen microbes has been reported, revealing the effects of external stimuli (e.g., antimicrobial administrations and diet ingredients) on the antimicrobial resistance in the rumen. However, the host effect on the ruminal resistome and their interactions remain largely unknown. Here, we investigated the ruminal resistome and its relationship with host feed intake and milk protein yield using metagenomic sequencing.

Results: The ruminal resistome conferred resistance to 26 classes of antimicrobials, with genes encoding resistance to tetracycline being the most predominant. The ARG-containing contigs were assigned to bacterial taxonomy, and the majority of highly abundant bacterial genera were resistant to at least one antimicrobial, while the abundances of ARG-containing bacterial genera showed distinct variations. Although the ruminal resistome is not co-varied with host feed intake, it could be potentially linked to milk protein yield in dairy cows. Results showed that host feed intake did not affect the alpha or beta diversity of the ruminal resistome or the abundances of ARGs, while the Shannon index (R² = 0.63, P < 0.01) and richness (R² = 0.67, P < 0.01) of the ruminal resistome were highly correlated with milk protein yield. A total of 128 significantly different ARGs (FDR < 0.05) were identified in the high- and low-milk protein yield dairy cows. We found four ruminal resistotypes that are driven by specific ARGs and associated with milk protein yield. Particularly, cows with low milk protein yield are classified into the same ruminal resistotype and featured by high-abundance ARGs, including mfd and sav1866.

Conclusions: The current study uncovered the prevalence of ARGs in the rumen of a cohort of lactating dairy cows. The ruminal resistome is not co-varied with host feed intake, while it could be potentially linked to milk protein yield in dairy cows. Our results provide fundamental knowledge on the prevalence, mechanisms and impact factors of antimicrobial resistance in dairy cattle and are important for both the dairy industry and other food animal antimicrobial resistance control strategies.

Keywords: Dairy cattle; Metagenomics; Microbiome; Resistome; Rumen.

Fig. 1

Composition of ruminal resistome in dairy cows. a Abundances of ARGs (antimicrobial resistance genes) per branch. ABS, Antimicrobial Biosynthesis; AT, Antimicrobial Target; AS, Antimicrobial Sensitive; AR, Antimicrobial Resistance. b Ruminal resistome composition summarized at the antimicrobial-class level

Fig. 2

Antimicrobial resistance mechanisms in the rumen microbiome. The rumen microbiome in dairy cows exhibited broad antimicrobial resistance mechanisms classified in 7 categories. The classes of antimicrobials observed in the category of each mechanism are presented

Fig. 3

The predicted bacterial taxa of the ruminal resistome and the relative abundances of related resistance genes. a Composition of observed bacterial taxa predicted by the ruminal resistome summarized at the phylum and family levels. b Distributions of ARGs in the phyla of predicted rumen bacteria. The top 10 phyla are displayed, with the remaining bacterial phyla included in the “others” category. The distributions of the ARGs are presented as coloured boxes, with the top 20 resistance genes listed. ARGs: antimicrobial resistance genes

Fig. 4

Ruminal resistome profiles of cows with different feed intake and cows with different milking traits. Spearman’s rank correlations between Shannon index (a) and Chao 1 richness (b) of ARGs and dry matter intake. c Biplot of the redundancy analysis showed relationships between ARGs and dry matter intake. The top 10 most abundant ARGs were used in this analysis. HDMI, cows with the highest dry matter intake (n = 10); LDMI, cows with the lowest dry matter intake (n = 10). d Heatmap of the abundances of the top 20 ARGs in each sample. The abundances (CPM, counts per million) of ARGs were log10- transformed. The cows were clustered and coloured by different groups (green, high intake; red, low intake). The animals used in the above analysis were all selected from study 1. Spearman’s rank correlations between Shannon index (e) and Chao 1 richness (f) of ARGs and milk protein yield. The animals used were selected from study 2. R² = correlation coefficient. ARGs: antimicrobial resistance genes

Fig. 5

Distributions of ARGs annotated to bacterial taxa in the rumen of cows with different milk protein yield. The proportion of ARG contigs annotated to the top 10 most abundant bacterial phyla (a) and top 20 most abundant bacterial genera (b) are shown in the bar plots. ARGs: antimicrobial resistance genes

Fig. 6

Distinguishable ruminal resistome between high- and low-milk protein yield dairy cows. a The clustering of ARGs obtained from dairy cows with high and low milk protein yield based on Bray-Curtis dissimilarity. b Biplot of the redundancy analysis showed relationships between ARGs and milk protein content (MP), milk yield (MY), and milk protein yield (MPY). The top 10 most abundant ARGs were used in this analysis and are indicated by green arrows. c Significantly different ARGs categorized by antimicrobial classes. Each antimicrobial class was represented by an individual colour in the external circle of the plot. The numbers of significantly higher ARGs in each group belonging to each antimicrobial class are shown in the plot. ARGs: antimicrobial resistance genes

Fig. 7

Co-occurrence network of abundant bacterial genera and ARGs. Abundant bacterial genera (top 10) and ARGs (top 20) of animals in study 2 were selected and used in the co-occurrence analysis. Only strong positive relationships (coefficient > 0.5 and P < 0.05) were displayed in the network

Fig. 8

Stratification of the ruminal resistome composition in study 2. a The principal coordinate analysis of the ruminal resistome showed four resistance types (resistotypes) among the 16 dairy cows. b The significantly different ARGs among the four resistotypes tested by LDA effective size analysis, with LDA > 2 being considered significantly different. Differential ARGs among the four ruminal resistotypes were only found to be enriched in Type1 and Type4. The heatmap shows the abundances (log10-transformed reads per million) of each differential ARG. * Represents the ARGs that were also found to be significantly different between high- and low-milk protein yield groups. ARGs: antimicrobial resistance genes