Integrating microbial 16S rRNA sequencing and non-targeted metabolomics to reveal sexual dimorphism of the chicken cecal microbiome and serum metabolome

Abstract

Background: The gut microbiome plays a key role in the formation of livestock and poultry traits via serum metabolites, and empirical evidence has indicated these traits are sex-linked.

Methods: We examined 106 chickens (54 male chickens and 52 female chickens) and analyzed cecal content samples and serum samples by 16S rRNA gene sequencing and non-targeted metabolomics, respectively.

Results: The cecal microbiome of female chickens was more stable and more complex than that of the male chickens. Lactobacillus and Family XIII UCG-001 were enriched in male chickens, while Eubacterium_nodatum_group, Blautia, unclassified_Anaerovoraceae, Romboutsia, Lachnoclostridium, and norank_Muribaculaceae were enriched in female chickens. Thirty-seven differential metabolites were identified in positive mode and 13 in negative mode, showing sex differences. Sphingomyelin metabolites possessed the strongest association with cecal microbes, while 11β-hydroxytestosterone showed a negative correlation with Blautia.

Conclusion: These results support the role of sexual dimorphism of the cecal microbiome and metabolome and implicate specific gender factors associated with production performance in chickens.

Keywords: cecal microbiota; chicken; integrated omics; serum metabolomics; sexual dimorphism.

Figure 1

Experimental design. The experimental cohort comprised of 106 healthy chickens (male chickens n = 54, female chickens n = 52). Cecal content samples were collected at the age of 18 weeks and subjected to 16S rRNA gene sequencing to infer microbial profiles. Concurrent blood samples were collected to measure the non-targeted metabolome. Sexual dimorphism in chickens was explored after data pre-treatment of cecal microbiota and serum metabolome.

Figure 2

Body weights of experimental chickens. Comparison of 18-week-old body weight of chickens between different (A) breeds and (B) sexes. (C) Changes in body weight of experimental chickens from 0 to 18 weeks old. GH, Guizhou yellow chickens; WM, Wumeng Black-Bone chickens. The addition of F or M to breed designations indicates female and male chickens, respectively.

Figure 3

Cecal microbiota composition of experimental chickens depicted by a Sankey diagram.

Figure 4

Sex-associated differences in cecal microbiome composition and diversity. (A) Comparison of the α-diversity (Shannon index) of cecal microbiota based on sex. (B) PCoA based on Bray–Curtis distances for the cecal microbiomes between male and female chickens. (C) Eight genera showing significantly different relative abundance levels between male and female chickens using LEfSe analysis.

Figure 5

Identification of the metabolic signatures between male and female chickens. OPLS-DA of serum metabolomic data in (A) positive and (B) negative mode for male (n = 51, in blue) and female (n = 50, in brown) chickens. Variable importance in projection (VIP > 2) scores for the top serum metabolites in (C) positive and (D) negative mode contributing to variation in metabolic profiles of male and female chickens. The relative abundance of metabolites is indicated by a colored scale from blue to red representing the low and high, respectively. Pathway enrichment analysis based on metabolites associated with (E) male and (F) female chicken.

Figure 6

Correlations between differential serum metabolites and bacterial species. (A) Correlation of three sphingomyelin metabolites. (B) Heatmap depicting correlations between differential serum metabolites (negative mode) and differential bacterial species in difference sex chickens. (C) Heatmap depicting correlations between differential serum metabolites (positive mode) and differential bacterial species. *p < 0.05; **p < 0.01; and ***p < 0.001 were calculated using Spearman’s rank correlation test. Positive (in purple) and negative (in dark green) correlations are indicated.