Small molecule inhibitors of hnRNPA2B1-RNA interactions reveal a predictable sorting of RNA subsets into
Jessica Corsi1, Pouriya Sharbatian Semnani1, Daniele Peroni2
1Laboratory of Biotechnology and Nanomedicine, Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Via Sommarive 9, 38123 Trento, Italy.
Abstract:
Extracellular vesicles (EVs) are cell-secreted membranous particles contributing to intercellular communication. Coding and noncoding RNAs can be detected as EV cargo, and RNA-binding proteins (RBPs), such as hnRNPA2B1, have been circumstantially implicated in EV-RNA sorting mechanisms. However, the contribution of competitive RBP-RNA interactions responsible for RNA-sorting outcomes is still unclear, especially for predicting the EV-RNA content. We designed a reverse proteomic analysis exploiting the EV-RNA to identify intracellular protein binders in vitro. Using cells expressing a recombinant hnRNPA2B1 to normalize competitive interactions, we prioritized a network of heterogeneous nuclear ribonucleoproteins and purine-rich RNA sequences subsequently validated in secreted EV-RNA through short fluorescent RNA oligos. Then, we designed a GGGAG-enriched RNA probe that efficiently interacted with a full-length human hnRNPA2B1 protein. We exploited the interaction to conduct a pharmacological screening and identify inhibitors of the protein-RNA binding. Small molecules were orthogonally validated through biochemical and cell-based approaches. Selected drugs remarkably impacted secreted EV-RNAs and reduced an RNA-dependent, EV-mediated paracrine activation of NF-kB in recipient cells. These results demonstrate the relevance of post-transcriptional mechanisms for EV-RNA sorting and the possibility of predicting the EV-RNA quality for developing innovative strategies targeting discrete paracrine functions.
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