Non-destructive and efficient method for obtaining miRNA information in cells by artificial extracellular vesicles
In recent years, research has explored the use of microRNA (miRNA) analysis in extracellular vesicles (EVs) as a minimally invasive strategy for the diagnosis and prediction of diseases. This is because miRNAs in EVs partly reflect the miRNA information and cellular status of the origin cells. Howev...
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Published in | Scientific reports Vol. 13; no. 1; p. 22231 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
14.12.2023
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | In recent years, research has explored the use of microRNA (miRNA) analysis in extracellular vesicles (EVs) as a minimally invasive strategy for the diagnosis and prediction of diseases. This is because miRNAs in EVs partly reflect the miRNA information and cellular status of the origin cells. However, not all intracellular miRNAs are internalized into EVs. Therefore, the miRNA information obtained from EVs is limited. To get more miRNA information, we aimed to produce artificial EVs (aEVs) encapsulating Argonaute 2 (Ago2) miRNA-binding protein, which actively incorporate miRNAs within themselves. In this study, we utilized the protein EPN-01, which is capable of releasing aEVs encapsulating it and associated proteins. This system enables us to obtain more miRNA species and increase each miRNA’s yield in the EV fraction. Furthermore, we examined whether miRNAs in the EV fraction using our system reflect the cellular condition. In cells treated with CoCl
2
, a reagent for inducing a hypoxia-mimic state, we detected a change in the level of hypoxia marker miR-210 with aEVs. To the best of our knowledge, this is the first report on a method to increase the yield and variety of endogenous miRNAs in the EV fraction. This approach leads to improved accuracy of cell status assessment using miRNAs in EVs. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-023-48995-5 |