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Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

  • Fudan University
  • National Institute for Research and Development of Isotopic and Molecular Technologies
  • Tongji University

Research output: Contribution to journalReview articlepeer-review

232   Link opens in a new tab Citations (SciVal)

Abstract

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Original languageEnglish
Pages (from-to)11593-11634
Number of pages42
JournalNanoscale
Volume13
Issue number27
Early online date6 Jul 2021
DOIs
Publication statusPublished - 21 Jul 2021

Bibliographical note

Funding Information:
N. E. Dina wishes to acknowledge a grant from the Ministry of Research, Innovation and Digitization, CNCS/CCCDI - UEFISCDI, project number PN-III-P1-1.1-PD-2016-0475 within PNCDI III and the financial support through the Core Program, Project No. PN 19 35 02 01. Liwu Zhang acknowledges support from the National Natural Science Foundation of China (No. 21677037 and 21976030) and the Natural Science Foundation of Shanghai (No. 17ZR1440200 and No. 19ZR1471200). V. K. V. acknowledges support from the Royal Society through the University Research Fellowships. V. K. V. and L. Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICAR1201088).

Funding Information:
N. E. Dina wishes to acknowledge a grant from the Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI, project number PN-III-P1-1.1-PD-2016-0475 within PNCDI III and the financial support through the Core Program, Project No. PN 19 35 02 01. Liwu Zhang acknowledges support from the National Natural Science Foundation of China (No. 21677037 and 21976030) and the Natural Science Foundation of Shanghai (No. 17ZR1440200 and No. 19ZR1471200). V. K. V. acknowledges support from the Royal Society through the University Research Fellowships. V. K. V. and L. Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICA\R1 \201088).

Funding

N. E. Dina wishes to acknowledge a grant from the Ministry of Research, Innovation and Digitization, CNCS/CCCDI - UEFISCDI, project number PN-III-P1-1.1-PD-2016-0475 within PNCDI III and the financial support through the Core Program, Project No. PN 19 35 02 01. Liwu Zhang acknowledges support from the National Natural Science Foundation of China (No. 21677037 and 21976030) and the Natural Science Foundation of Shanghai (No. 17ZR1440200 and No. 19ZR1471200). V. K. V. acknowledges support from the Royal Society through the University Research Fellowships. V. K. V. and L. Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICAR1201088). N. E. Dina wishes to acknowledge a grant from the Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI, project number PN-III-P1-1.1-PD-2016-0475 within PNCDI III and the financial support through the Core Program, Project No. PN 19 35 02 01. Liwu Zhang acknowledges support from the National Natural Science Foundation of China (No. 21677037 and 21976030) and the Natural Science Foundation of Shanghai (No. 17ZR1440200 and No. 19ZR1471200). V. K. V. acknowledges support from the Royal Society through the University Research Fellowships. V. K. V. and L. Z. acknowledge the International Collaboration Awards 2020 of the Royal Society (No. ICA\R1 \201088).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • General Materials Science

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