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. 2025 Aug;104(8):105275.
doi: 10.1016/j.psj.2025.105275. Epub 2025 May 7.

Multi-omics analyses reveal differences in intestinal flora composition and serum metabolites in Cherry Valley broiler ducks of different body weights

Hongjiao Wang  1 , Long Li  1 , Jinhai Wu  2 , Xuefeng Yuan  3 , Liang Hong  1 , Lei Pu  1 , Shunyi Qin  1 , Liuan Li  1 , Hua Yang  1 , Jianbin Zhang  4
Affiliations

Multi-omics analyses reveal differences in intestinal flora composition and serum metabolites in Cherry Valley broiler ducks of different body weights

Hongjiao Wang et al. Poult Sci. 2025 Aug.

Abstract

Fledgling broiler ducks vary in body weight and growth rate. The aim of this study was to investigate the relationship between serum metabolites and the intestinal microbiota in Cherry Valley broiler ducks with different finishing weights and to reveal differences in their metabolic regulation and microbial composition. Serum and cecum content samples were collected from Cherry Valley broiler ducks of different finishing weights. Metabolites were identified and compared using untargeted metabolomics, 16S rRNA gene sequencing, multivariate statistics and bioinformatics. Six key findings emerged. First, serum biochemical parameters showed that AST and ALT levels were significantly lower in the high weight group (Group H) than in the low weight group (Group L), and serum immunoglobulin IgG levels were significantly higher in group H. Second, the chorionic height to crypt depth ratio of the duodenum was significantly higher in group H than in group L. Third, the gut microbial community diversity or abundance was lower in broiler ducks in group L. Fourth, LEfSe analysis showed that the biomarker for group L was Streptococcus, whereas for group H it was Faecalibacterium. Fifth, a total of 127 differential metabolites were identified (49 up-regulated and 78 down-regulated). Finally, Spearman's correlation analysis showed that Spearman's correlation analyses showed that the Lipid-related serum metabolites were higher in low-body recombinant broiler ducks, mainly Lathosterol, Cholesterol, Cynaratriol and Leukotriene B4. In addition to lipid-associated serum metabolites in high-body recombination, The water-soluble vitamin-like metabolite Pantothenate and the antibiotic-like metabolite Tylosin were high. The cecum microbiota is strongly associated with metabolites, especially Faecalibacterium, unclassified Tannerellaceae, Subdoligranulum, Alistipes, and [Ruminococcus] torques_group, with which it exhibits strong Correlation. Broiler ducks with higher body weights have a better intestinal villous structure, enhanced digestion and absorption, higher levels of immunoglobulin secretion and superior growth performance. Broiler ducks with different body weights differed in plasma metabolites and cecum flora. Spearman's correlation analyses showed that the Correlation between differential metabolites and differential gut microbial genera.

Keywords: Cherry Valley broiler duck; Intestinal microbiota; Serum metabolites; Weight.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1
Figure 1
HE stained intestinal sections at 4x magnification. (A) And (B) duodenal HE stained intestinal sections. (C) And (D) is a HE stained intestinal slice of the jejunum. (E) And (F) is a HE stained intestinal slice of the ileum.
Figure 2
Figure 2
Diversity analysis of the gut microbiota. (A) Venn diagrams of shared or unique ASVs of groups H and L. (B) The Chao1 index, Shannon index, Simpson index and ACE index were used to describe the ɑ diversity of the duck intestinal flora. (C) Principal coordinate analysis (PCoA) based on weighted UniFrac distances for all samples. (D) Non-metric multidimensional scaling analysis (NMDS) (n = 4 per group).
Figure 3
Figure 3
Compositional analysis of the cecum microbiota at the phylum, family and genus levels in Cherry Valley broiler ducks of different body weights. (A) Species composition and relative abundance at the phylum level. (B) Species composition and relative abundance at the family level. (C) Species composition and relative abundance at the genus level.
Figure 4
Figure 4
(A) Evolutionary branching diagram for LEfSe analysis. (B) Histogram of the distribution of LDA values.
Figure 5
Figure 5
Metabolite profiling of serum by untargeted LC-MS/MS metabolomics. (A, B) 3D and 2D plots of PCA analyses between groups H and L (n = 4 per group). (C) Orthogonal partial least squares discriminant analysis (OPLS-DA). The x-axis (t1) represents the predictive component (between-group variance component), the y-axis (to1) represents the orthogonal component (within-group variance component), and the horizontal y-axis percentage represents that component's share of the total variance.The parameters of the model are labelled at the bottom of the figure, including R2X, R2Y, Q2Y, RMSEE (root mean square error), pre (number of predicted components), ort (number of orthogonal components). (D) OPLS-DA model replacement test plot.The x-axis of the figure represents the correlation between the replacement grouping and the original model grouping, the y-axis represents the value of R2Y or Q2Y (where R2Y and Q2Y taken as 1 in the x-axis are the values of the original model), the blue dots and the red dots represent the R2Y and Q2Y of the model after the replacement, respectively, and the two dashed lines are the regression lines fitted to R2Y and Q2Y.If the slope of the Q2Y fitted regression line is positive it means that the model makes sense, and the blue dots are generally located above the red dots it means that the modelling training set and test set are better independent.
Figure 6
Figure 6
Differential metabolite analysis. (A) Differential metabolite volcano plot; (B) Fold change analysis of changes in the expression of significantly different metabolites.
Figure 7
Figure 7
(A) Heat map of differential metabolite clustering; (B) Differential metabolic correlation map.
Figure 8
Figure 8
KEGG pathway enrichment analysis. (A) Differential metabolite KEGG enrichment plot. (B) Differential abundance score plot.
Figure 9
Figure 9
Differential metabolite-differential microbe correlation heat map.
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