Genome-Resolved Metagenomics of the Chicken Gut Microbiome

Increasing evidence shows that the chicken gastrointestinal microbiota has a major effect on the modulation of metabolic functions and is correlated with economic parameters, such as feed efficiency and health. Some of these effects derive from the capacity of the chicken to digest carbohydrates and produce energy-rich metabolites such as short-chain fatty acids (SCFA) and from host-microbe interactions. In this study, we utilized information from metagenomic assembled genomes (MAGs) from chicken gastrointestinal tract (GIT) samples, with detailed annotation of carbohydrate-active enzymes (CAZymes) and genes involved in SCFA production, to better understand metabolic potential at different ages. Metagenomic sequencing of 751 chicken GIT samples was performed to reconstruct 155 MAGs, representing species which belong to six phyla, primarily Firmicutes followed by Proteobacteria. MAG diversity significantly (p < 0.001) increased with age, with early domination of Lachnospiraceae, followed by other families including Oscillospiraceae. Age-dependent shifts were observed in the abundance of genes involved in CAZyme and SCFA production, exemplified by a significant increase in glycosyltransferases (GTs) and propionic acid production pathways (p < 0.05), and a lower abundance of glycoside hydrolases (GHs) (p < 0.01). Co-occurrence analysis revealed a large cluster highly interconnected by enzymes from GT2_2 and GH3 families, underscoring their importance in the community. Furthermore, several species were identified as interaction hubs, elucidating associations of key microbes and enzymes that more likely drive temporal changes in the chicken gut microbiota, and providing further insights into the structure of the complex microbial community. This study extends prior efforts on the characterization of the chicken GIT microbiome at the taxonomic and functional levels and lays an important foundation toward better understanding the broiler chicken gut microbiome helping in the identification of modulation opportunities to increase animal health and performance.