The chicken cecal microbiome alters bile acids and riboflavin metabolism that correlate with intramuscular fat content

Abstract

Intramuscular fat (IMF) is a key indicator of chicken meat quality and emerging studies have indicated that the gut microbiome plays a key role in animal fat deposition. However, the potential metabolic mechanism of gut microbiota affecting chicken IMF is still unclear. Fifty-one broiler chickens were collected to identify key cecal bacteria and serum metabolites related to chicken IMF and to explore possible metabolic mechanisms. The results showed that the IMF range of breast muscle of Guizhou local chicken was 1.65 to 4.59%. The complexity and stability of ecological network of cecal microbiota in low-IMF chickens were higher than those in high-IMF chickens. Cecal bacteria positively related to IMF were Alistipes, Synergistes and Subdoligranulum, and negatively related to IMF were Eubacterium_brachy_group, unclassified_f_Lachnospiraceae, unclassified_f_Coriobacteriaceae, GCA-900066575, Faecalicoccus, and so on. Bile acids, phosphatidylethanolamine (Pe) 32:1 and other metabolites were enriched in sera of high-IMF chickens versus low-IMF chickens while riboflavin was enriched in sera of low-IMF chickens. Correlation analysis indicated that specific bacteria including Alistipes promote deposition of IMF in chickens via bile acids while the Eubacterium_brachy group, and Coriobacteriaceae promoted formation of riboflavin, glufosinate, C10-dats (tentative), and cilastatin and were not conducive to the IMF deposition.

Keywords: cecal microbiota; chickens; integrative omics; intramuscular fat; metabolomics.

Figure 1

Experimental flow chart. A total of 51 Guizhou yellow chickens were collected. The intramuscular fat (IMF) content of breast muscle of all chickens was measured. Cecal contents and serum samples were collected for microbial 16S rRNA gene sequencing and non-targeted metabolome detection, respectively. High- and low-IMF chicken groups were established in the experimental cohorts. The differences in the cecal microbiota and metabolome between two groups were compared and the correlation analysis of differential microbes and differential metabolites was conducted.

Figure 2

Relationships between IMF content in chicken breast muscle and gender, body weight and serum cytokines. (A) Distribution of IMF content of male and female chickens (25 males and 26 female). y-axis represents frequency of IMF level; x-axis represents IMF %. (B) Comparison of IMF content in breast muscle of male and female chickens. (C) Correlations of IMF content of breast muscle, body weight and serum cytokine levels. ^*p < 0.05, ^**p < 0.01, and ^***p < 0.001.

Figure 3

The profiles of microbial compositions of cecum at the phylum level. The samples were ordered following the abundance of Bacteroidetes.

Figure 4

The difference of diversity and composition of cecal microbiota between HIG and LIG chickens. Comparison of the α-diversity of cecal microbiota between HIG (n = 16) and LIG (n = 16) with (A) Chao1 index, and (B) Shannon index. (C) Average relative abundance of cecal microbiota at the phylum level in HIC and LIG chickens; (D) PCoA based on Bray–Curtis distance showing the cecal microbiota composition between the two groups. (E) Nine ASVs showing significantly different relative abundance between HIG and LIG. PCoA, Principal coordinate analysis; HIG, chickens with high intramuscular fat content; LIG, chickens with low intramuscular fat content.

Figure 5

Identifying serum metabolites and metabolic pathways that differ between HIG (n = 16) and LIG (n = 16) chickens. OPLS-DA analysis of serum metabolomics profiles showed a clear separation between HIG and LIG chickens both in (A) positive and (B) negative ion modes. Variable importance in projection (VIP >2) scores for the top serum metabolites in (C) positive and (D) negative modes contributing to variation in metabolic profiles of HIG and LIG chickens. The relative abundance of metabolites is indicated by a colored scale from blue to red representing the low and high, respectively. (E) The correlation of five bile acids which are related with IMF. (F) Pathway enrichment analysis of metabolites associated with IMF in chickens. OPLS-DA, orthogonal partial least squares-discriminant analysis; HIG, chickens with high intramuscular fat content; LIG, chickens with low intramuscular fat content. The metabolites are shown in Table 3.

Figure 6

The correlation analysis between differential bacteria and differential serum metabolites. Heatmaps showing the correlations between differential bacteria and differential serum metabolites in (A) positive mode and (B) negative mode. Positive correlations are displayed in brown and negative correlations in blue. ^*p < 0.05, ^**p < 0.01, and ^***p < 0.001.