Optical biosensors for diagnosis of COVID-19: nanomaterial-enabled particle strategies for post pandemic era

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Tekin Y. S., Kul S. M., SAĞDIÇ O., Rodthongkum N., Geiss B., ÖZER T.

Microchimica Acta, vol.191, no.6, 2024 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Review
  • Volume: 191 Issue: 6
  • Publication Date: 2024
  • Doi Number: 10.1007/s00604-024-06373-6
  • Journal Name: Microchimica Acta
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Analytical Abstracts, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Food Science & Technology Abstracts, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Keywords: Biomarkers, COVID-19, Machine learning, Optical detection, SARS-CoV-2, Virus
  • Yıldız Technical University Affiliated: Yes

Abstract

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal–organic frame–based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid–based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios. Graphical Abstract: (Figure presented.)