The differential plasma and ruminal metabolic pathways and ruminal bacterial taxa associated with divergent residual body weight gain phenotype in crossbred beef steers

Abstract

We applied ruminal and plasma metabolomics and ruminal 16S rRNA gene sequencing to determine the metabolic pathways and ruminal bacterial taxa associated with divergent residual body weight gain phenotype in crossbred beef steers. A group of 108 crossbred growing beef steers (average BW = 282.87 ± 30 kg) were fed a forage-based diet for a period of 56 d in a confinement dry lot equipped with GrowSafe intake nodes to determine their residual body weight gain (RADG) phenotype. After RADG identification, blood and rumen fluid samples were collected from beef steers with the highest RADG (most efficient; n = 16; 0.76 kg/d) and lowest RADG (least efficient; n = 16; -0.65 kg/d). Quantitative untargeted metabolome analysis of the plasma and rumen fluid samples were conducted using chemical isotope labelling/liquid chromatography-mass spectrometry. Differentially abundant metabolites in each of the plasma and rumen fluid samples between the two groups of beef steers were determined using a false discovery rate (FDR)-adjusted P-values ≤ 0.05 and area under the curve (AUC) > 0.80. Rumen and plasma metabolic pathways that were differentially enriched or depleted (P ≤ 0.05) in beef steers with positive RADG compared to those with negative RADG were determined by the quantitative pathway enrichment analysis. A total of 1,629 metabolites were detected and identified in the plasma of the beef steers; eight metabolites including alanyl-phenylalanine, 8-hydroxyguanosine, and slaframine were differentially abundant (FDR ≤ 0.05; AUC > 0.80) in beef steers with divergent RADG; five metabolic pathways including steroid hormone biosynthesis, thiamine metabolism, propanoate metabolism, pentose phosphate pathway, and butanoate metabolism were enriched (P ≤ 0.05) in beef steers with positive RADG, relative to negative RADG steers. A total of 1,908 metabolites were detected and identified in the rumen of the beef steers; results of the pathway enrichment analysis of all the metabolites revealed no metabolic pathways in the rumen were altered (P > 0.05). The rumen fluid samples were also analyzed using 16S rRNA gene sequencing to assess the bacterial community composition. We compared the rumen bacterial community composition at the genus level using a linear discriminant analysis effect size (LEfSe) to identify the differentially abundant taxa between the two groups of beef steers. The LEfSe results showed greater relative abundance of Bacteroidetes_vadinHA17 and Anaerovibrio in steers with positive RADG compared to the negative RADG group, while steers in the negative RADG group had greater relative abundance of Candidatus_Amoebophilus, Clostridium_sensu_stricto_1, Pseudomonas, Empedobacter, Enterobacter, and Klebsiella compared to the positive RADG group. Our results demonstrate that beef steers with positive or negative RADG exhibit differences in plasma metabolic profiles and some ruminal bacterial taxa which probably explain their divergent feed efficiency phenotypes.

Keywords: feed efficiency; metabolomics; rumen microbiome; steroid hormone.

Figure 1.

Alpha diversity (Chao1 index; P-value = 0.86) of the rumen bacterial community in beef steers with divergent residual body weight gain (RADG) phenotype. .

Figure 2.

Beta diversity (Bray-Curtis-PCoA based on unweighted Unifrac distance) of the rumen bacterial community in beef steers with divergent residual body weight gain (RADG) phenotype (PERMANOVA P-value = 0.22).

Figure 3.

Differentially abundant bacterial taxa at the genus level determined using linear discriminant analysis effect size (LEfSe) analysis in beef steers with divergent residual body weight gain (RADG) phenotype.

Figure 4.

Biomarker analysis of the differentially abundant rumen metabolites in beef steers with with divergent residual body weight gain (RADG) phenotype. Only metabolites with AUC values > 0.80 are shown.

Figure 5.

Pathway enrichment analysis of the rumen fluid metabolome. No metabolic pathways were altered (–log10(P) ≤ 1.3 (equivalent to P ≥ 0.05).

Figure 6.

Biomarker analysis of the differentially abundant plasma metabolites in beef steers with divergent residual body weight gain phenotype. Only metabolites with AUC values > 0.80 are shown.

Figure 7.

Pathway enrichment analysis of the plasma metabolome. Metabolic pathways with –log10(P) ≥ 1.3 (equivalent to P ≤ 0.05) are enriched in positive RADG steers, relative to negative RADG steers.