Abstract

We developed MEBOCOST, a computational algorithm for quantitatively inferring metabolite-mediated intercellular communications using single cell RNA-seq data. The algorithm identifies cell-cell communications in which metabolites, such as lipids, are secreted by sender cells and traveled to interact with sensor proteins of receiver cells. The sensor proteins on receiver cell might be cell surface receptors, transporters across the cell membrane, or nuclear receptors. MEBOCOST relies on a comprehensive database of metabolite-sensor partners, which we manually curated from the literatures and other public sources. MEBOCOST defines sender and receiver cells for an extracellular metabolite based on the expression levels of the enzymes and sensors, respectively, thus identifies metabolite-sensor communications between the cells. Applying MEBOCOST to mouse brown adipose tissue (BAT) successfully recaptured known metabolite-mediated cell communications and further identified new communications. Additionally, MEBOCOST identified a set of BAT intercellular metabolite-sensor communications that was regulated by cold exposure of the mice. MEBOCOST will be useful to numerous researchers to investigate metabolite-mediated cell-cell communications in many biological and disease models. The MEBOCOST software is freely available at https://github.com/zhengrongbin/MEBOCOST.