Illuminating the microbial ‘dark matter’ in obesity: integrated multi-omics approaches to characterize uncultured taxa and their potential metabolic crosstalk with host pathways

Background Obesity is a global health challenge shaped by interactions among host genetics, diet, lifestyle, and gut microbial ecology. Although reference genome catalogues and cultivation approaches have expanded knowledge of the human gut microbiome, many intestinal microorganisms remain uncultured, poorly characterized, or functionally unresolved. These microorganisms are collectively referred to as microbial “dark matter,” a conceptual category rather than a defined taxonomic group encompassing diverse lineages, including members of Patescibacteriota, historically referred to collectively as the Candidate Phyla Radiation (CPR), with Saccharibacteria representing a historically used designation for a lineage within this broader group. Objective This review examines the potential relevance of uncultured and poorly characterized gut microorganisms—collectively referred to here as microbial “dark matter”—to obesity-associated microbial ecology and metabolism. We focus on how integrated multi-omics approaches can identify candidate microbial functions, metabolic interactions, and host-associated pathways, while distinguishing genomic prediction and ecological association from demonstrated activity and causal effects. Particular attention is given to the evidence gaps surrounding microbial metabolite production or transformation by poorly characterized taxa and to experimental strategies required for functional and causal validation. Design We summarize evidence on the ecological characteristics, genome reduction, metabolic dependencies, and potential host–microbe interactions of uncultured microorganisms. We discuss microbial metabolites, including short-chain fatty acids and bile acid derivatives, while distinguishing established microbiome–host mechanisms from functions specifically attributed to uncultured taxa. We also evaluate cultivation, gnotobiotic models, organoids, and microbial engineering for experimental validation. Results Uncultured microorganisms represent an important but incompletely characterized component of the gut ecosystem. Genome-resolved and single-cell approaches have revealed substantial metabolic diversity and ecological dependencies. Some uncultured lineages may participate in carbohydrate metabolism, metabolite exchange, and bile acid transformation. However, direct evidence linking specific uncultured taxa to obesity phenotypes remains limited, with many proposed mechanisms based on genomic prediction, multi-omics associations, or extrapolation from better-characterized microorganisms. Their roles in antibiotic resistance and environmental-stressor responses also remain emerging rather than established mechanisms of obesity. Conclusion Microbial dark matter represents an unresolved dimension of obesity-associated microbiome research. Integrated multi-omics can generate functional hypotheses, but causal attribution requires complementary experimental validation. A function-oriented framework distinguishing established evidence, mechanistic inference, and future hypotheses may provide a rigorous foundation for understanding uncultured components of the gut microbiome.