INVESTIGATING THE MOLECULAR MECHANISMS UNDERLYING RNA TRANSPORT IN EXTRACELLULAR VESICLES

Abstract

Extracellular vesicles (EVs) are small particles that are released by almost allcells and mediate cell-cell communication by transferring bioactive molecules such asRNA. RNA cargo of EVs, including coding and non-coding RNAs, can change thebehavior of recipient cells, affecting processes including gene expression,proliferation, and apoptosis. CircRNAs are stable and resistant to degradation andhave been shown to be enriched in EVs. They play key roles in gene regulation andare also emerging as promising biomarkers for disease diagnosis due to their stabilityand disease-specific expression. While microRNAs (miRNAs) are the most wellstudied RNA cargo of EVs, very little is known about the mechanisms of enrichmentof circular RNAs (circRNAs) as well as long linear RNAs. Here, we take acomprehensive genome-wide approach to investigate the role of structuredness andshape along with GC%, size, exon count, and coding potential, in the sorting andenrichment of circular and long linear RNAs into EVs. We developed a model usingthese parameters to predict the likelihood of EV packaging of RNA and it wasvalidated by using single molecule RNA imaging of EV bound RNAs. Furthermore,we found that structuredness could explain the relative enrichment of circRNAs overtheir linear counterparts. These results were validated on existing public databases ofcircular and linear RNAs in EVs. By identifying and analyzing these factors, we wereable to develop models that predict enrichment of linear and circular RNAs in EVs.We combined cis and trans factors that represent RNA sequence elements and RNAbinding protein motifs, respectively, and achieved high performance for predicting RNA enrichment in EVs. Moreover, we developed a web tool, EV RNA CargoEnrichment Prediction Tool (EVRCEPT), that allows users to predicting EVenrichment of input RNA sequence and can help guide the design of therapeutic RNAsto maximize their incorporation in EVs. This work aims to better understand thecomplex mechanisms behind EV-mediated RNA transfer and its impact on cellcommunication in both health and disease. This mechanistic understanding of RNAenrichment in EVs is crucial for engineering EVs with selective RNA cargo.