4.7 Article

Evaluation of EV Storage Buffer for Efficient Preservation of Engineered Extracellular Vesicles

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出版社

MDPI
DOI: 10.3390/ijms241612841

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extracellular vesicles; storage buffer; preservation; engineered extracellular vesicles

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Extracellular vesicles (EVs) serve as mediators of intercellular communication by transporting molecules between cells, and have potential clinical applications in diagnostics and therapeutics. However, standardized storage conditions for EVs are lacking, leading to challenges in clinical applications and potential misinterpretation of findings. This study aims to optimize the storage conditions of EVs and characterize them under different experimental conditions and models, reporting a highly efficient EV storage buffer that can protect their molecular cargo.
Extracellular vesicles (EVs), detectable in all bodily fluids, mediate intercellular communication by transporting molecules between cells. The capacity of EVs to transport molecules between distant organs has drawn interest for clinical applications in diagnostics and therapeutics. Although EVs hold potential for nucleic-acid-based and other molecular therapeutics, the lack of standardized technologies, including isolation, characterization, and storage, leaves many challenges for clinical applications, potentially resulting in misinterpretation of crucial findings. Previously, several groups demonstrated the problems of commonly used storage methods that distort EV integrity. This work aims to evaluate the process to optimize the storage conditions of EVs and then characterize them according to the experimental conditions and the models used previously. Our study reports a highly efficient EV storage condition, focusing on EV capacity to protect their molecular cargo from biological, chemical, and mechanical damage. Compared with commonly used EV storage conditions, our EV storage buffer leads to less size and particle number variation at both 4 degrees C and -80 degrees C, enhancing the ability to protect EVs while maintaining targeting functionality.

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