Toward Identification of Markers for Brain‐Derived Extracellular Vesicles in Cerebrospinal Fluid: A Large‐Scale, Unbiased Analysis Using Proximity Extension Assays - Maia Norman; Adnan Shami‐shah; Sydney C. D'Amaddio; Benjamin G. Travis; Dmitry Ter‐Ovanesyan; Tyler J. Dougan; David R. Walt (Journal of Extracellular Vesicles)
ABSTRACT Extracellular vesicles (EVs) captured in biofluids have opened a new frontier for liquid biopsies. To enrich for vesicles coming from a particular cell type or tumour, scientists utilize antibodies to transmembrane proteins that are relatively unique to the cell type of interest. However, recent evidence has called into question the basic assumption that all transmembrane proteins measured in biofluids are, in fact, EV‐associated. To identify both candidate markers for brain‐derived EV immunocapture and cargo proteins to validate the EVs’ cell of origin, we conducted an unbiased Olink screen, measuring 5416 unique proteins in cerebrospinal fluid after size exclusion chromatography. We identified proteins that demonstrated a clear EV fractionation pattern and created a searchable dataset of candidate EV‐associated markers—both proteins that are cell type‐specific within the brain, and proteins found across multiple cell types for use as general EV markers. We further implemented the DeepTMHMM deep learning model to differentiate predicted cytosolic, transmembrane, and external proteins and found that intriguingly, only 10% of the predicted transmembrane proteins have a clear EV fractionation pattern based on our stringent criteria. This dataset further bolsters the critical importance of verifying EV association of candidate proteins using methods such as size exclusion chromatography before downstream use of the targets for EV analysis.