Profiling Protein Citrullination in Extracellular Vesicles by Single‐Molecule Detection Using Direct Stochastic Optical Reconstruction Microscopy

TL;DR

This study uses advanced microscopy to detect citrullinated proteins in different types of extracellular vesicles, offering new insights for liquid biopsy tools.

Contribution

A Bayesian framework is introduced to model EV cargoes and their subtypes using super-resolution imaging.

Findings

Citrullinated proteins are found both inside and on the surface of extracellular vesicles.

Pan-Cit staining is higher in TT-bound EVs, while CitH3 is higher in PS-bound EVs.

The Bayesian framework improves the analysis of EV subtypes and their cargo distribution.

Abstract

Extracellular vesicles (EVs) are critical in cellular communication and pathological biomarkers. Post‐translationally deiminated/citrullinated proteins are reported in EV cargoes by LC–MS/MS but it is unknown in which EV sub‐types they are exported, as part of EVs' intraluminal cargo or on the EV surface. Here, dSTORM super‐resolution microscopy is used to co‐localise total citrullinated proteins (pan‐Cit), and citrullinated histone H3 (CitH3) to EV subtypes of three cancer cell lines, captured by tetraspanin trio (TT) or phosphatidylserine (PS). Permeabilised and non‐permeabilised EVs are analysed with a Bayesian framework using beta‐distributed posteriors for binomial outcomes. Pan‐Cit and CitH3 labelling is confirmed in EVs as intraluminal cargo and on the EV surface, with higher levels detected in the permeabilized EVs. Pan‐Cit staining is higher in TT‐bound EVs, but CitH3 staining higher in PS‐bound EVs. This study expands the landscape of EV‐associated post‐translational modifications with translational potential for EV‐citrullinome based liquid biopsy tools.

This study identifies post‐translationally citrullinated/deiminated protein cargoes co‐localised to EV subtypes, using super resolution microscopy and dSTORM imaging. The findings expand current understanding of post‐translational modifications in EV‐mediated cellular communication. The Bayesian framework presented here provides a new tool for modelling EV cargoes to EV subtypes, aiding the development of refined EV‐based liquid biopsy tools.

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