Issue 26, 2024

A proximity ligation hybridization triggered structure-switching based signal amplification strategy for sensitive and accurate exosome detection

Abstract

Exosomes have significant functions in intercellular communication, as well as in tumor migration and invasion. Nevertheless, the precise identification of exosomes poses a significant obstacle due to their low abundance in biofluids and potential disruption caused by free protein molecules, such as CD63 protein. In this study, we have developed a signal amplification method for precise detection of exosomes using a proximity ligation hybridization triggered structure-switching approach. The method involves the dual-recognition of exosomes by two probes: an aptamer probe that recognizes the exosomal surface protein CD63 (L1 probe), and a cholesterol probe that targets the biolipid layer of the exosomes (L2 probe). Based on the dual-recognition of exosomes, we have successfully developed an accurate and sensitive approach that integrates the proximity ligation hybridization technique with a structure-switching based signal cycle. This approach allows for the simultaneous analysis of two biomarkers, enabling both quantification and tracing of exosomes without the need for enzymes. Eventually, the proposed method exhibits a wide detection range of 5 orders of magnitude and a low limit of detection of 36 particles per μL, making it suitable for a wide range of applications in the fields of biological science, biomedical engineering, and personalized medicine.

Graphical abstract: A proximity ligation hybridization triggered structure-switching based signal amplification strategy for sensitive and accurate exosome detection

Supplementary files

Article information

Article type
Paper
Submitted
06 May 2024
Accepted
02 Jun 2024
First published
03 Jun 2024

Anal. Methods, 2024,16, 4262-4267

A proximity ligation hybridization triggered structure-switching based signal amplification strategy for sensitive and accurate exosome detection

W. Yang, J. Yang, N. Zhou and Y. Wang, Anal. Methods, 2024, 16, 4262 DOI: 10.1039/D4AY00829D

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