Emerging Biosensors to Detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Review

被引:45
作者
Lim, Wei Yin [1 ]
Lan, Boon Leong [1 ]
Ramakrishnan, Narayanan [1 ]
机构
[1] Monash Univ Malaysia, Sch Engn & Adv Engn Platform, Elect & Comp Syst Engn, Bandar Sunway 47500, Selangor, Malaysia
来源
BIOSENSORS-BASEL | 2021年 / 11卷 / 11期
关键词
biosensor; COVID-19; diagnosis; SARS-CoV-2; surface plasmon resonance; field-effect transistor; electrochemical; a point-of-care device; FIELD-EFFECT-TRANSISTOR; LABEL-FREE; ELECTROCHEMICAL BIOSENSORS; RAPID DETECTION; RESONANCE; ANTIBODIES; SENSOR; SENSITIVITY; CHALLENGES; BIOMARKER;
D O I
10.3390/bios11110434
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Coronavirus disease (COVID-19) is a global health crisis caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard test for diagnosing COVID-19. Although it is highly accurate, this lab test requires highly-trained personnel and the turn-around time is long. Rapid and inexpensive immuno-diagnostic tests (antigen or antibody test) are available, but these point of care (POC) tests are not as accurate as the RT-PCR test. Biosensors are promising alternatives to these rapid POC tests. Here we review three types of recently developed biosensors for SARS-CoV-2 detection: surface plasmon resonance (SPR)-based, electrochemical and field-effect transistor (FET)-based biosensors. We explain the sensing principles and discuss the advantages and limitations of these sensors. The accuracies of these sensors need to be improved before they could be translated into POC devices for commercial use. We suggest potential biorecognition elements with highly selective target-analyte binding that could be explored to increase the true negative detection rate. To increase the true positive detection rate, we suggest two-dimensional materials and nanomaterials that could be used to modify the sensor surface to increase the sensitivity of the sensor.
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页数:26
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