Molecular imaging of extracellular vesicles in vitro via Raman metabolic labelling

通过拉曼代谢标记对细胞外囊泡进行体外分子成像

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作者:Conor C Horgan, Anika Nagelkerke, Thomas E Whittaker, Valeria Nele, Lucia Massi, Ulrike Kauscher, Jelle Penders, Mads S Bergholt, Steve R Hood, Molly M Stevens

Abstract

Extracellular vesicles (EVs) are biologically-derived nanovectors important for intercellular communication and trafficking. As such, EVs show great promise as disease biomarkers and therapeutic drug delivery vehicles. However, despite the rapidly growing interest in EVs, understanding of the biological mechanisms that govern their biogenesis, secretion, and uptake remains poor. Advances in this field have been hampered by both the complex biological origins of EVs, which make them difficult to isolate and identify, and a lack of suitable imaging techniques to properly study their diverse biological roles. Here, we present a new strategy for simultaneous quantitative in vitro imaging and molecular characterisation of EVs in 2D and 3D based on Raman spectroscopy and metabolic labelling. Deuterium, in the form of deuterium oxide (D2O), deuterated choline chloride (d-Chol), or deuterated d-glucose (d-Gluc), is metabolically incorporated into EVs through the growth of parent cells on medium containing one of these compounds. Isolated EVs are thus labelled with deuterium, which acts as a bio-orthogonal Raman-active tag for direct Raman identification of EVs when introduced to unlabelled cell cultures. Metabolic deuterium incorporation demonstrates no apparent adverse effects on EV secretion, marker expression, morphology, or global composition, indicating its capacity for minimally obstructive EV labelling. As such, our metabolic labelling strategy could provide integral insights into EV biocomposition and trafficking. This approach has the potential to enable a deeper understanding of many of the biological mechanisms underpinning EVs, with profound implications for the design of EVs as therapeutic delivery vectors and applications as disease biomarkers.

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