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SLAS Discov ; 27(6): 331-336, 2022 09.
Article in English | MEDLINE | ID: covidwho-1878377

ABSTRACT

Current methods for the screening of viral infections in clinical settings, such as reverse transcription polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA), are expensive, time-consuming, require trained personnel and sophisticated instruments. Therefore, novel sensors that can save time and cost are required specially in remote areas and developing countries that may lack the advanced scientific infrastructure for this task. In this work, we present a sensitive, and highly specific biosensing approach for the detection of harmful viruses that have cysteine residues within the structure of their cell surface proteins. We utilized new method for the rapid screening of SARS-CoV-2 virus in biological fluids through its S1 protein by surface enhanced Raman spectroscopy (SERS). The protein is captured from aqueous solutions and biological specimens using a target-specific extractor substrate. The structure of the purified protein is then modified to convert it into a bio-thiol by breaking the disulfide bonds and freeing up the sulfhydryl (SH) groups of the cysteine residues. The formed biothiol chemisorbs favourably onto a highly sensitive plasmonic sensor and probed by a handheld Raman device in few seconds. The new method was used to screen the S1 protein in aqueous medium, spiked human blood plasma, mucus, and saliva samples down to 150 fg/L. The label-free SERS biosensing method has strong potential for the fingerprint identification many viruses (e.g. the human immunodeficiency virus, the human polyomavirus, the human papilloma virus, the adeno associated viruses, the enteroviruses) through the cysteine residues of their capsid proteins. The new method can be applied at points of care (POC) in remote areas and developing countries lacking sophisticated scientific infrastructure.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , Cysteine , Gold/chemistry , Humans , Limit of Detection , Membrane Proteins
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