PQG Working Group

We developed MEBOCOST, a computational algorithm for quantitatively inferring metabolite-based intercellular communications using single cell RNA-seq data. MEBOCOST predicted cell-cell communication events for which metabolites, such as lipids, are secreted by one cell (sender cells) and traveled to interact with sensor proteins of another cell (receiver cells). The sensor protein on receiver cell might be cell surface receptor, cell surface transporter, and nuclear receptor. MEBOCOST relies on a curated database of metabolite-sensor partners, which we collected from the literatures and other public sources. Based on scRNA-seq data, MEBOCOST identifies cell-cell metabolite-sensor communications between cell groups, in which metabolite enzymes and sensors were highly expressed in sender and receiver cells, respectively. Applying MEBOCOST on brown adipose tissue (BAT) showed the robustness of predicting known and novel metabolite-based autocrine and paracrine communications. Additionally, MEBOCOST identified a set of intercellular metabolite-sensor communications that was regulated by cold exposure in BAT. Those predicted communicating metabolites and sensors may play important roles in thermogenesis regulation. We believe that MEBOCOST will be useful to numerous researchers to investigate metabolite-based cell-cell communications in many biological and disease models, thus will be useful to remove critical barriers impeding the development of new therapies to target these communications. MEBOCOST is freely available at https://github.com/zhengrongbin/MEBOCOST