Predicting cell type-specific extracellular vesicle biology using an organism-wide single cell transcriptomic atlas - insights from the Tabula Muris

Abstract

Extracellular vesicles (EVs) like exosomes are functional nanoparticles trafficked between cells and found in every biofluid. An incomplete understanding of which cells, from which tissues, are trafficking EVs in vivo has limited our ability to use EVs as biomarkers and therapeutics. However, recent discoveries have linked EV secretion to expression of genes and proteins responsible for EV biogenesis and found as cargo, which suggests that emerging "cell atlas" datasets could be used to begin understanding EV biology at the level of the organism and possibly in rare cell populations. To explore this possibility, here we analyzed 67 genes that are directly implicated in EV biogenesis and secretion, or carried as cargo, in [~]44,000 cells obtained from 117 cell populations of the Tabula Muris. We found that the most abundant proteins found as EV cargo (tetraspanins and syndecans) were also the most abundant EV genes expressed across all cell populations, but the expression of these genes varied greatly among cell populations. Expression variance analysis also identified dynamic and constitutively expressed genes with implications for EV secretion. Finally, we used EV gene co-expression analysis to define cell population-specific transcriptional networks. Our analysis is the first, to our knowledge, to predict tissue- and cell type-specific EV biology at the level of the organism and in rare cell populations. As such, we expect this resource to be the first of many valuable tools for predicting the endogenous impact of specific cell populations on EV function in health and disease.