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Extracellular vesicle cross-linking coupled with solid-phase purification facilitates discovery of ribonucleoprotein complexes assembled on EV RNAs.

Dhyani, R.; Clarke, S.; Kuroda, M.; Sanada, Y.; Gorum, M.; Barman, B.; Weaver, A.; Nakamura, T.; Ascano, M.

2026-10-06 cancer biology
10.64898/2026.10.03.756357 bioRxiv
Show abstract

Extracellular vesicles (EVs) are fundamental mediators of intercellular communication that transfer macromolecular cargo, including proteins and RNAs, to functionally reprogram recipient cells. However, the molecular processes by which transferred ribonucleoprotein (RNP) complexes engage recipient host machinery to influence cellular behavior are poorly understood, primarily due to a dearth of methods capable of tracking these post-transfer interactions. To address this gap, we developed two complementary chemical biology platforms: EV-CLASP and EV(r)-CLASP. While EV-CLASP maps the native, intra-vesicular RNP landscape packaged within the EV, EV(r)-CLASP captures post-transfer dynamics by identifying the host proteins that directly associate with EV-derived RNAs following cellular uptake. Both approaches leverage metabolic labeling and photo-crosslinking for high-specificity recovery. Donor cells are cultured with 4-thiouridine (4SU) to biosynthetically label newly synthesized RNAs during EV biogenesis. Purified EVs can be crosslinked using 365 nm UV light to capture intra-vesicular RNP composition. Alternatively, 4SU-labeled EVs can be delivered to recipient cells and subsequently crosslinked to identify the primary physical interactions formed within the recipient-cell environment. Crosslinked RNP complexes are isolated under stringent conditions using solid-phase reversible beads to minimize background, followed by quantitative mass spectrometry for protein identification. Together, EV-CLASP and EV(r)-CLASP provide a robust, versatile framework for defining the dynamic RNP assemblies that facilitate extracellular RNA communication, offering a powerful toolkit to uncover novel RNA-associated regulatory networks, therapeutic targets, and biomarkers across diverse biological and disease contexts.

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