Nanotechnology-Based Approaches for the Detection of SARS-CoV-2 - Gupta, Ritika; Sagar, Poonam; Priyadarshi, Nitesh; Kaul, Sunaina; Sandhir, Rajat; Rishi, Vikas; Singhal, Nitin Kumar (Frontiers in Nanotechnology, 2020)
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a pandemic has been validated as an extreme clinical calamity and has affected several socio-economic activities globally. Proven transmission of this virus occurs through airborne droplets from an infected person. The recent upsurge in the number of infected individuals has already exceeded the number of intensive care beds available to patients. These extraordinary circumstances have elicited the need for the development of diagnostic tools for the detection of the virus and, hence, prevent the spread of the disease. Early diagnosis and effective immediate treatment can reduce and prevent an increase in the number of cases. Conventional methods of detection such as quantitative real-time polymerase chain reaction and chest computed tomography scans have been used extensively for diagnostic purposes. However, these present several challenges, including prolonged assay requirements, labor-intensive testing, low sensitivity, and unavailability of these resources in remote locations. Such challenges urgently require fast, sensitive, and accurate diagnostic techniques for the timely detection and treatment of coronavirus disease 2019 (COVID-19) infections. Point-of-care biosensors that include paper- and chip-based diagnostic systems are rapid, cost-effective, and user friendly. In this article nanotechnology-based potential biosensors for SARS-CoV-2 diagnosis are discussed with particular emphasis on a lateral flow assay, a surface-enhanced Raman scattering-based biosensor, a localized surface plasmon resonance-based biosensor, Förster resonance energy transfer, an electrochemical biosensor, and artificial intelligence-based biosensors. Several biomolecules, such as nucleic acids, antibodies/enzymes, or aptamers, can serve as potential detection molecules on an appropriate platform, such as graphene oxide, nanoparticles, or quantum dots. An effective biosensor can be developed by using appropriate combinations of nanomaterials and technologies.