Dietary wet fermented Brewer's grains modulate hepatic metabolism in pullets

Abstract

This study was conducted to evaluate the effects of wet-fermented brewer's grains (WFBG) on liver metabolism in pullets. A total of 120 female 84-d-old pullets (575.2 ± 4.3 g) were randomly allocated into 2 treatments (0% and 20% WFBG) with 6 replicates per group and 10 birds per replicate in this 28-d experiment. Birds fed 20% WFBG had higher (P < 0.05) superoxide dismutase (SOD) level and lower (P < 0.05) malondialdehyde (MDA) content in the liver compared with the control group. In total, 324 liver differentially-expressed metabolites (DEMs) including 208 up-regulated DEMs and 116 down-regulated DEMs were identified and considered to be related with WFBG. Pathway analysis revealed that these DEMs were mainly involved in 64 metabolic pathways including metabolic pathways metabolism, glycerophospholipid (GP) metabolism, linoleic acid (LA) metabolism, arachidonic acid metabolism (ARA), and alpha-linolenic acid metabolism. Furthermore, untargeted metabolomic analyses uncovered 18 common up-regulated DEMs and 8 common down-regulated DEMs in GP, LA and ARA metabolism in the 20% WFBG group (P < 0.05), such as lysophosphatidylcholine (LPC(18:0/0:0), LPC(0:0/20:4)), lysophosphatidylethanolamine (LPE(22:6/0:0)), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine. Overall, the inclusion of 20% WFBG in the diets of pullets led to alterations in liver metabolism.

Keywords: Liver health; Metabolomics; Pullet; Wet-fermented Brewer’s grains.

Fig. 1

Liver metabolome analysis. (A) PCA-DA score plots derived from UHPLC-MS/MS. PC1 represents the first principal component, PC2 represents the second principal component, and the percentage represents the explanatory power of the principal component on the dataset; Each point in the figure represents a sample, samples in the same group are represented by the same color. (B) PLS-DA of the liver metabolites from the control and 20% WFBG groups (R2 X = 0.289, R2 Y = 0.981, Q2 = 0.620). (C) OPLS-DA of the liver metabolites from the control and 20% WFBG groups (R2 X = 0.383, R2 Y = 0.998, and Q2 = 0.478). R2 X and R2 Y indicate the fraction of the variables explained by the model, and the Q2 shows the predictive abilities of the model.

Fig. 2

Hierarchical cluster analysis. Heat map representation of metabolites that differed significantly between liver samples of two groups. Each block represents the abundance of one metabolite from one sample. CKL control group; LM, 20% WFBG group.

Fig. 3

Volcanic map and pathway analysis of identified liver metabolites related to WFBG. (A) Volcanic map in the control and 20% WFBG groups (adjusted P-value < 0.05 and Fold Change (FC) > 1.2, or FC < 0.833). Volcano plot representing the significant variables in the discrimination of liver metabolites from two groups. Gray, unchanged metabolites. Red, up-regulated metabolites. Green, down-regulated metabolites. (B) The KEGG pathways of DEMs from the control and 20% WFBG group. Advanced bubble chart shows the enrichment of DEMs in signaling pathways. The x-axis represents the rich factor (rich factor = number of DEMs enriched in the pathway/number of all metabolites in the background metabolites set). The y-axis represents the enriched pathway. Size of the bubble represents the number of DEMs enriched in the pathway, and the color represents enrichment significance.

Fig. 4

Concentrations of liver metabolites involved in GP metabolism (A), LA metabolism (B), and ARA metabolism (C) by untargeted analysis. Abbreviations: GP, Glycerophosphate, ARA, arachidonic acid. * P < 0.05, compared with the control group. CKL, control group; LM, 20% WFBG group.

Fig. 4

Concentrations of liver metabolites involved in GP metabolism (A), LA metabolism (B), and ARA metabolism (C) by untargeted analysis. Abbreviations: GP, Glycerophosphate, ARA, arachidonic acid. * P < 0.05, compared with the control group. CKL, control group; LM, 20% WFBG group.