Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies
Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/25/21/5209 |
| _version_ | 1797548502973153280 |
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| author | Hyunku Shin Dongkwon Seo Yeonho Choi |
| author_facet | Hyunku Shin Dongkwon Seo Yeonho Choi |
| author_sort | Hyunku Shin |
| collection | DOAJ |
| description | Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-related EVs through their molecular fingerprints. In this review, we describe label-free SERS approaches for disease-related EV pattern identification in terms of substrate design and signal analysis strategies. We first describe the general characteristics of EVs and their SERS signals. We then present recent works on applied plasmonic nanostructures to sensitively detect EVs and notable methods to interpret complex spectral data. This review also discusses current challenges and future prospects of label-free SERS-based disease-related EV pattern identification. |
| first_indexed | 2024-03-10T15:00:20Z |
| format | Article |
| id | doaj.art-ed198a46232f45c38a0c43c6460d69dc |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T15:00:20Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-ed198a46232f45c38a0c43c6460d69dc2023-11-20T20:17:23ZengMDPI AGMolecules1420-30492020-11-012521520910.3390/molecules25215209Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis StrategiesHyunku Shin0Dongkwon Seo1Yeonho Choi2Department of Bio-convergence Engineering, Korea University, Seoul 02841, KoreaDepartment of Bio-convergence Engineering, Korea University, Seoul 02841, KoreaDepartment of Bio-convergence Engineering, Korea University, Seoul 02841, KoreaExtracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-related EVs through their molecular fingerprints. In this review, we describe label-free SERS approaches for disease-related EV pattern identification in terms of substrate design and signal analysis strategies. We first describe the general characteristics of EVs and their SERS signals. We then present recent works on applied plasmonic nanostructures to sensitively detect EVs and notable methods to interpret complex spectral data. This review also discusses current challenges and future prospects of label-free SERS-based disease-related EV pattern identification.https://www.mdpi.com/1420-3049/25/21/5209extracellular vesiclessurface-enhanced Raman spectroscopynanostructuressignal analysis |
| spellingShingle | Hyunku Shin Dongkwon Seo Yeonho Choi Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies Molecules extracellular vesicles surface-enhanced Raman spectroscopy nanostructures signal analysis |
| title | Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies |
| title_full | Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies |
| title_fullStr | Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies |
| title_full_unstemmed | Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies |
| title_short | Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies |
| title_sort | extracellular vesicle identification using label free surface enhanced raman spectroscopy detection and signal analysis strategies |
| topic | extracellular vesicles surface-enhanced Raman spectroscopy nanostructures signal analysis |
| url | https://www.mdpi.com/1420-3049/25/21/5209 |
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