Effects of Land Transport Stress on Variations in Ruminal Microbe Diversity and Immune Functions in Different Breeds of Cattle

Abstract

The intensity and specialization of beef cattle production make off-site fattening, and introduce new breeds need transportation to achieve the goals. The present study was aimed to investigate effects of land transport stress on hormones levels, microbial fermentation, microbial composition, immunity and correlation among them among Simmental Crossbred Cattle (SC), Native Yellow Cattle (NY), and Cattle Yak (CY). High-throughput sequencing was used to investigate the rumen microbial diversity. After transport stress cortisol (COR), adrenocorticotropic hormone (ACTH) and pro-inflammatory cytokines IL-6, TNF-α, and IL-1β were increased (p < 0.05) in all groups. Rumen lipopolysaccharide (LPS) was increased (p < 0.05) in SC and CY groups. Total volatile fatty acids were increased (p < 0.05) in all groups. The ruminal microbiota about OTUs, Chao1, and Shannon in SC and CY groups were higher than before transport. Prevotella1 in NY group was higher (p < 0.05) than other groups before transport; after transport Firmicutes and Lactobacillus were increased (p < 0.05) than other groups in CY. Lactobacillus was positively correlated with IL-6 and IL-4. Under transport stress, cattle may suffer from inflammatory response through modulating HPA axis and microbiota metabolite affects the secretion of hormone levels and immune function and breeds factor affect the performance of stress resistance.

Keywords: cattle breeds; high-throughput sequencing; microorganism immunity; rumen bacteria; transport stress.

Figure 1

Principal Coordinate Analysis (PCoA) of rumen bacterial community structures of cattle in NY, SC and CY groups before (A), rumen bacterial community before and after transportation in NY (B), rumen bacterial community before and after transportation in SC (C), rumen bacterial community before and after transportation in CY (D). The PCoA plots were constructed using the weighted UniFrac method.

Figure 1

Principal Coordinate Analysis (PCoA) of rumen bacterial community structures of cattle in NY, SC and CY groups before (A), rumen bacterial community before and after transportation in NY (B), rumen bacterial community before and after transportation in SC (C), rumen bacterial community before and after transportation in CY (D). The PCoA plots were constructed using the weighted UniFrac method.

Figure 2

Venn diagram representation of the shared and exclusive OTUs at the 97% similarity level among the three parts of the rumen bacterial community before (A) and after (B) transportation in NY, SC, and CY groups: between BNY and ANY (C), BCY and ACY (D) and BSC and ASC (E).

Figure 3

Bar plots showing the average relative abundance of bacterial phyla (%) in the rumen at the phylum level (A) and genus level (B). For each breed, B indicates before transport, and A indicates after transport. (For example, the Native Yellow (NY) group includes BNY and ANY, Simmental Crossbred Cattle (SC) group includes BSC and ASC, and Cattle Yak (CY) includes BCY and ACY) and transportation (before vs. after). Data represent the abundance at greater than 0.1% of the community between three beef breeds or between treatment groups (before and after transportation).

Figure 4

LEfSe identified the most differentially abundant taxons in NY, SC, and CY (A) before transport, BNY and ANY (B), BSC and ASC (C), BCY and ACY (D). Taxonomic cladogram obtained from LEfSe analysis of 16 S sequences (relative abundance ≥0.5%). (red) BNY-enriched taxa, (blue) taxa enriched in BSC, (green) taxa enriched in BCY (A), (red) BNY-enriched taxa, (green) taxa enriched in ANY (B), (red) BCY-enriched taxa, (green) taxa enriched in ACY (C), (red) BSC-enriched taxa, (green) taxa enriched in ASC (D). The brightness of each dot is proportional to its effect size. Phylum: p (put “p” in front of the microbes or don’t use italics), class: c(put “c” in front of the microbes and use italics), order: o(put “o” in front of the microbes and use italics), family: f (put “f” in front of the microbes and use italics), genus: g(put “g” in front of the microbes and use italics or not put “g” in front of the microbes but use italics) and species: s (put “s” in front of the microbes and use italics), all data were same.

Figure 5

Correlation between rumen microbiota and cattle physiological variables. Spearman non-parametric Rank correlation matrix between serum index, characteristics of rumen fermentation parameters and microbiota abundance (representing at least 1% of the bacterial community in at least one sample). The red color represents a negative correlation; the blue color represents a positive correlation, and the white color represents no correlation. The OTU count data were subjected to variance stabilizing transformation, then pairwise serum index, characteristics of rumen fermentation parameters. Spearman correlations between bacterial and biological parameters at corresponding were analyzed.