Cecal Microbial Succession and Its Apparent Association with Nutrient Metabolism in Broiler Chickens

Abstract

The chicken gut microbiota plays an influential role in nutrient absorption and metabolism. A clear picture of microbiota succession can enhance host nutrition and disease resistance. This study investigated the cecal microbiota succession of broilers between 3 and 42 days after hatching using 16S rRNA gene sequencing and analyzed its potential association with intestinal nutrient metabolism. Microbiota structure differed significantly at different time points depending on the microbiota alpha-diversity or beta-diversity. Proteobacteria and Bacteroidetes promoted succession on days 3 to 7 and days 28 to 35, respectively. Firmicutes and Tenericutes maintained homeostasis on days 7 to 28 and days 35 to 42. Shigella, [Ruminococcus], Erysipelotrichaceae_Clostridium, and Coprobacillus promoted succession on days 3 to 7; Faecalibacterium modified microbial composition on days 7 to 14; Faecalibacterium and Bacteroides regulated microbial structure from days 21 to 28. The microbiota structure was relatively stable on days 14 to 21 and days 28 to 35. Spearman's correlation analysis indicated a positive correlation between Lactobacillus and villus height and crypt depth (P < 0.01). Faecalibacterium and Shigella were correlated with propionate, butyrate, and valerate concentrations (P < 0.01). Ruminococcus was correlated with sodium-glucose cotransporters 1 and cationic amino acid transporter 1 expression (P < 0.05). Erysipelotrichaceae_Clostridium and Shigella were positively correlated with serum levels of total cholesterol, tryglucerides, and high- and low-density lipoprotein cholesterol (P < 0.01). Bacteroides, Parabacteroides, Lactobacillus, and Shigella were correlated with serum VB6 levels (P < 0.01). Bacteroides, Erysipelotrichaceae_Clostridium, and Coprobacillus were correlated with the moisture content of cecal contents (P < 0.05). The identification of the microbiota in correlation with nutrient metabolism will promote microbial nutrition through microbiota intervention or nutritional regulation. IMPORTANCE The poultry industry has become a global leader in livestock farming over the past few decades. Poultry production has a large consumer market as an integrated industry producing high-protein foods. Establishing the association between microbiota and nutrient metabolism processes provides fresh insights for precise nutrient regulation. This study aimed to describe the development of cecal microbiota in broiler chickens throughout the production cycle and to assess the correlation of nutrient metabolism phenotypes with temporal changes in the microbiota. The results suggested that changes in cecal microbes with age partly explain changes in gut nutrient metabolic processes, and numerous microbes were significantly associated with the processes. Therefore, this study attempts to further find efficient ways of improving poultry production. One is to promote nutrient metabolism by identifying potential candidates for probiotics, and another is to foster the dominant colonization of the microbiota by regulating nutrient metabolism.

Keywords: broiler chickens; cecal microbiota; developmental stage; nutrient metabolism; temporal colonization.

FIG 1

Succession pattern of bacterial taxa in the ceca of broiler chickens. (A) PCoA plots based on the weighted UniFrac distance. (B) Phylum level microbial composition. (C) Shared genera and dominant genera with age.

FIG 2

Pattern of microbiota colonization in various taxonomic levels. (A) Microbial taxa with the same change trends in relative abundance with age (two or more levels are the same at phylum, class, order, family, and genus levels). The heatmap color (blue to red, corresponding to low to high) represents the row z-score of the relative abundance values. The y axis was clustered according to the microbiota with taxonomic affiliation. (B) LEfSe-derived taxonomic cladogram. The default parameters were LDA score >2 and P < 0.05.

FIG 3

Functional prediction was based on 16S rRNA gene taxonomic inference in PICRUST2 using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. (A) PCoA of the KEGG Orthology (KO) genes. A Bray-Curtis distance matrix combined with PCoA was used for functional difference analysis. (B to D) The pathways of carbohydrate metabolism, amino acid metabolism, and lipid metabolism are based on KEGG level 2. (E and F) The pathways of vitamin B₆ metabolism and vasopressin-regulated water reabsorption are based on KEGG level 3.

FIG 4

Determination of cecum morphology, SCFAs, glucose and amino acid transporters, serum lipid metabolites, serum VB6, and moisture of contents. (A) VH, CD, and VH:CD of the cecum. (B) Cecal concentrations of acetate, propionate, isobutyrate, butyrate, isovalerate, and valerate. (C) mRNA expression of rBAT, CAT1, CAT4, y⁺LAT2, and SGLT1 in the cecal mucosa. (D) Serum levels of TG, TC, HDL-C, and LDL-C. (E) Serum VB6 levels. (F) Moisture content of cecal contents. Abbreviations: SCFAs, short-chain fatty acids; VH, villus height; CD, crypt depth; VH:CD, villus height/crypt depth ratio; SGLT1, sodium-glucose cotransporters 1; y⁺LAT2, y⁺L amino acid transporter-2; rBAT, related to b^0,+, neutral and basic amino acid transport protein; CAT1, cationic amino acid transporter 1; CAT4, cationic amino acid transporter 4; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; VB6, vitamin B₆. Significantly different values are indicated by different letters (lowercase letters, P < 0.05; uppercase letters, P < 0.01).

FIG 5

Heatmap showing Spearman correlations between predominant genera in the cecum and cecum morphology, SCFAs, glucose, and amino acid transporters, serum lipid metabolites, serum VB6, and moisture of contents. Red indicates a positive correlation; blue indicates a negative correlation. Abbreviations: SCFAs, short-chain fatty acids; VH, villus height; CD, crypt depth; VH:CD, villus height: crypt depth; SGLT1, sodium-glucose cotransporters 1; y⁺LAT2, y⁺L amino acid transporter-2; rBAT, related to b^0,+, neutral and basic amino acid transport protein; CAT1, cationic amino acid transporter 1; CAT4, cationic amino acid transporter 4; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; VB6, vitamin B₆. *, 0.01 < P ≤ 0.05; **, P ≤ 0.01.