Microbiome analysis characterizes microbial communities in biological or environmental samples by measuring community composition, diversity, taxonomic structure, functional potential, and associations with host or environmental phenotypes. 16S rRNA gene amplicon sequencing is commonly used for bacterial and archaeal taxonomic profiling, while shotgun metagenomics provides higher taxonomic resolution and direct functional information, including microbial genes, pathways, viruses, fungi, and antimicrobial-resistance genes when sequencing depth and host-DNA contamination are adequately controlled. Microbiome results are strongly affected by sample collection, storage, DNA extraction, contamination, sequencing method, reference database, and bioinformatic pipeline; therefore, standardized protocols, negative controls, mock communities, and transparent analysis workflows are required. Unresolved issues include low-biomass contamination, compositional-data bias, inconsistent species-level c
Microbiome Analysis
High-throughput sequencing and bioinformatics technologies enable a comprehensive analysis of the compositional structure and functional characteristics of vast microbial communities in specific environments, such as the human gut or oral cavity. By analyzing microbial diversity and community structure, researchers can precisely identify "disease-associated microbial signatures" linked to conditions like inflammatory bowel disease, metabolic disorders, or psychiatric disorders. Research into interventions for microbial dysbiosis employs techniques to evaluate therapies—such as probiotics, prebiotics, and fecal microbiota transplantation (FMT)—aimed at restoring gut microbial homeostasis. Mastery of microbiome analysis techniques serves as a cornerstone for deciphering the "human second genome" and advancing precision nutritional interventions and personalized targeted therapies.
Related Experimental Schemes
