Cargando…

Exosome-templated nanoplasmonics for multiparametric molecular profiling

Exosomes are nanoscale vesicles distinguished by characteristic biophysical and biomolecular features; current analytical approaches, however, remain univariate. Here, we develop a dedicated platform for multiparametric exosome analysis—through simultaneous biophysical and biomolecular evaluation of...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Xingjie, Zhao, Haitao, Natalia, Auginia, Lim, Carine Z. J., Ho, Nicholas R. Y., Ong, Chin-Ann J., Teo, Melissa C. C., So, Jimmy B. Y., Shao, Huilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202874/
https://www.ncbi.nlm.nih.gov/pubmed/32494726
http://dx.doi.org/10.1126/sciadv.aba2556
Descripción
Sumario:Exosomes are nanoscale vesicles distinguished by characteristic biophysical and biomolecular features; current analytical approaches, however, remain univariate. Here, we develop a dedicated platform for multiparametric exosome analysis—through simultaneous biophysical and biomolecular evaluation of the same vesicles—directly in clinical biofluids. Termed templated plasmonics for exosomes, the technology leverages in situ growth of gold nanoshells on vesicles to achieve multiselectivity. For biophysical selectivity, the nanoshell formation is templated by and tuned to distinguish exosome dimensions. For biomolecular selectivity, the nanoshell plasmonics locally quenches fluorescent probes only if they are target-bound on the same vesicle. The technology thus achieves multiplexed analysis of diverse exosomal biomarkers (e.g., proteins and microRNAs) but remains unresponsive to nonvesicle biomarkers. When implemented on a microfluidic, smartphone-based sensor, the platform is rapid, sensitive, and wash-free. It not only distinguished biomarker organizational states in native clinical samples but also showed that the exosomal subpopulation could more accurately differentiate patient prognosis.