The Role of Metabolites in Cell–Cell Communication: A Review of Databases and Computational Tools

Cell–cell communication (CCC) is essential for multicellular organisms, enabling different cell types to coordinate their activities in both physiological and pathological contexts, such as cell growth, proliferation, tumorigenesis, and immune responses. Metabolites represent an important class of signaling molecules, though their signaling roles were long underappreciated. Growing evidence has highlighted the critical involvement of metabolites in CCC, and the advent of single-cell RNA sequencing (scRNA-seq) has enabled high-resolution exploration of CCC events. This review summarizes existing metabolite–sensor databases and computational tools developed to identify metabolite-mediated CCC using scRNA-seq data. Nonetheless, these databases exhibit considerable variability due to lack of unified collection standards. Most computational tools were adapted from methods used for general CCC inference and often estimate metabolite abundance based on the expression of one or several related genes. Therefore, such approaches are not fully suited to capturing metabolite-mediated CCC due to the complexity of interaction mechanisms between metabolites and their sensors. To address these challenges, improved computational methods and refined databases are needed for the reliable inference of metabolite-mediated CCC. This review discusses the current limitations in database construction and method development, and highlights potential directions for future improvement, including the incorporation of spatial omics and artificial intelligence (AI) approaches. Furthermore, the systematic inference and validation of metabolite-mediated CCC will pave the way for the discovery of novel drugs and therapeutic targets.