Synthetic microbial communities as novel models to study gut microbiome–host interactions in metabolic diseases

Abstract Synthetic gut microbial communities (SynComs) have emerged as powerful platforms for investigating microbiome–host interactions in metabolic diseases. By enabling precise control over microbial composition, SynComs overcome key limitations of traditional models, such as ecological variability, low reproducibility, and limited mechanistic resolution. Most current SynComs focus on bacterial consortia, although interest in fungal and mixed communities is growing. These defined consortia have been successfully applied to reproduce disease-relevant phenotypes; elucidate microbial contributions to obesity, insulin resistance, and hepatic lipid metabolism; and identify specific taxa or strain-level functions with therapeutic potential. Their versatility spans in vitro systems—including batch fermenters and gut-on-chip devices—as well as in vivo models such as germ-free or gnotobiotic mice. Moreover, the integration of multi-omics technologies and computational modeling has enhanced the predictive capacity and functional insight of studies employing SynComs as experimental models. Despite current challenges—such as reduced ecological complexity and translational gaps—ongoing innovations in microbial culturing, host-relevant model systems, and rational SynCom design are expanding their applicability. This review evaluates the construction, applications, and limitations of SynComs, highlighting their potential to advance microbiome-targeted research and therapeutic development in metabolic disorders.