Plasma Metabolomic Profiling after Feeding Dried Distiller's Grains with Solubles in Different Cattle Breeds

Abstract

Dried distiller's grains with solubles (DDGS) are rich in nutrients and can enhance animals' growth and immunity. However, there are few reports on the effects of a diet of DDGS on plasma metabolism and the related action pathways in domestic animals. In this study, groups of Guanling yellow cattle (GY) and Guanling crossbred cattle (GC) having a basal diet served as the control groups (GY-CG and GC-CG), and DDGS replacing 25% of the diet of GY and GC served as the replacement groups (GY-RG and GC-RG), with three cattle in each group. Plasma samples were prepared for metabolomic analysis. Based on multivariate statistical and univariate analyses, differential metabolites and metabolic pathways were explored. Twenty-nine significantly different metabolites (p < 0.05) were screened in GY-RG compared with those in GY-CG and were found to be enriched in the metabolic pathways, including choline metabolism in cancer, linolenic acid metabolism, and amino acid metabolism. Nine metabolites showed significant differences (p < 0.05) between GC-RG and GC-CG and were mainly distributed in the metabolic pathways of choline metabolism in cancer, glycerophospholipid metabolism, prostate cancer metabolism, and gonadotropin-releasing hormone (GnRH) secretion. These results suggest that a DDGS diet may promote healthy growth and development of experimental cattle by modulating these metabolic pathways. Our findings not only shed light on the nutritional effects of the DDGS diet and its underlying mechanisms related to metabolism but also provide scientific reference for the feed utilization of DDGS.

Keywords: DDGS; GC; GY; metabolic pathways; plasma metabolome.

Figure 1

PCA and OPLS-DA score plots generated from plasma metabolic profiles. (a) Untargeted analysis in GY-RG and GY-CG. Cumulative fitness (R2 value) of the PCA model was 0.762. (b) Untargeted analysis in GC-RG and GC-CG. Cumulative fitness (R2 value) of the PCA model was 0.758. (c) OPLS-DA score plot of GY-RG and GY-CG, (R2X (cum) = 0.628, R2Y (cum) = 1, Q2 (cum) = 0.805). (d) OPLS-DA score plot of GC-RG and GC-CG, (R2X (cum) = 0.704, R2Y (cum) = 1, Q2 (cum) = 0.88). The PC1 and PC2 values in the figures represent the scores of each sample for principal components one and two, respectively. Each dot, square, or diamond on the plot represents a sample in the corresponding group. (e) OPLS-DA permutation test (200 times) in GY-RG and GY-CG. The results of the permutation test strongly indicate that the original model was valid (R2 intercept = 0.981, Q2 intercept = 0.47) (f) OPLS-DA permutation test (200 times) in GC-RG and GC-CG. The results of the permutation test strongly indicate that the original model was valid (R2 intercept = 0.988, Q2 intercept = 0.51). GY, Guanling yellow cattle; GC, Guanling crossbred cattle; CG, control group (the basal diet group); RG, DDGS 25% concentrate group.

Figure 2

Volcano plots and hierarchical clustering of all detected features. The volcano plot was generated based on metabolites detected by the untargeted analysis in GY-RG vs. GY-CG (a) and GC-RG vs. GC-CG (b). A red dot represents an upregulated metabolite, a blue dot represents a downregulated metabolite, and a grey dot represents a nonregulated metabolite. The horizontal dotted line represents the level of significance (p < 0.05).

Figure 3

Metabolic pathway analysis of the differentially expressed metabolites in GY-RG vs. GY-CG (a) and GC-RG vs. GC-CG (b). In (a,b), the red dotted line indicates a p-value of 0.01, and the blue dotted line indicates a p-value of 0.05. The color of the bar graph from light to dark indicates that the p-value decreases in order, and when the top of the bar is higher than the blue line, a pathway is considered to be significant.