Capturing nascent extracellular vesicles by metabolic glycan labeling-assisted microfluidics

Qiuyue Wu, Wencheng Wang, Chi Zhang, Zhenlong You, Yinyan Zeng, Yinzhu Lu, Suhui Zhang, Xingrui Li, Chaoyong Yang and Yanling Song ()
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Qiuyue Wu: Xiamen University
Wencheng Wang: Xiamen University
Chi Zhang: Xiamen University
Zhenlong You: Xiamen University
Yinyan Zeng: Xiamen University
Yinzhu Lu: Xiamen University
Suhui Zhang: Xiamen University
Xingrui Li: Xiamen University
Chaoyong Yang: Xiamen University
Yanling Song: Xiamen University

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: Abstract Extracellular vesicle (EV) secretion is a dynamic process crucial to cellular communication. Temporally sorting EVs, i.e., separating the newly-produced ones from the pre-existing, can allow not only deep understanding of EV dynamics, but also the discovery of potential EV biomarkers that are related to disease progression or responsible to drug intervention. However, the high similarity between the nascent and pre-existing EVs makes temporal separation extremely challenging. Here, by co-translational introduction of azido groups to act as a timestamp for click chemistry labelling, we develop a microfluidic-based strategy to enable selective isolation of nascent EVs stimulated by an external cue. In two mouse models of anti-PD-L1 immunotherapy, we demonstrate the strategy’s feasibility and reveal the high positive correlation of nascent PD-L1+ EV level to tumor volume, suggesting an important role of nascent EVs in response to immunotherapy in cancer treatment.

Date: 2023
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DOI: 10.1038/s41467-023-42248-9

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