This project plans to recruit the aging population (aged over 65 years old) and comprehensively analyze the public database and self-sequencing clinical big data by using 16 srDNA sequencing technology, metagenomic sequencing technology, metabonomics methods and Random Forest (R) prediction model to judge the key bacterial communities and related functional pathways related to aging.Based on the analysis results, the probiotics with the potential to alleviate aging were selected for intervention evaluation of aging population. This topic aims to explore the change process of intestinal flora structure and composition related to aging process.Identify the key intestinal bacteria genera/species/strains associated with aging, and target the pathway and metabolic characteristic spectrum of the key bacterial communities associated with aging;And select and breed specific intestinal bacterial strains related to aging.The aim is to reduce the age-related metabolic abnormalities and chronic inflammation, reduce medical treatment, rationally allocate medical resources, reduce medical costs and improve the quality of life.
This study intends to recruit aging population (over 65 years old). The investigators use 16 SrDNA sequencing technology, genome sequencing technology, metabonomics, random forest forecast model, analysing and selecting specific age-related intestinal flora. The investigators select probiotics slowing down senility. Then the investigators use the probiotics to intervene in the aging population. Finally the investigators observe whether the probiotics can delay aging.