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Review
. 2022;4(6):1304-1333.
doi: 10.1007/s42765-022-00179-y. Epub 2022 Aug 8.

Visual Detection of COVID-19 from Materials Aspect

Affiliations
Review

Visual Detection of COVID-19 from Materials Aspect

Gang Wang et al. Adv Fiber Mater. 2022.

Abstract

Abstract: In the recent COVID-19 pandemic, World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses. Several diagnostic methods, such as reverse transcription-polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA), have been applied based on the mechanism of specific recognition and binding of the probes to viruses or viral antigens. Although the remarkable progress, these methods still suffer from inadequate cellular materials or errors in the detection and sampling procedure of nasopharyngeal/oropharyngeal swab collection. Therefore, developing accurate, ultrafast, and visualized detection calls for more advanced materials and technology urgently to fight against the epidemic. In this review, we first summarize the current methodologies for SARS-CoV-2 diagnosis. Then, recent representative examples are introduced based on various output signals (e.g., colorimetric, fluorometric, electronic, acoustic). Finally, we discuss the limitations of the methods and provide our perspectives on priorities for future test development.

Keywords: COVID-19; Materials aspects; Rapid and high-throughput detection; Virus diagnosis; Visual detection.

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Conflict of interest statement

Conflict of interestThere are no conflicts of interest.

Figures

Fig. 1
Fig. 1
Scheme of various categories of COVID-19 diagnostic methods
Fig. 2
Fig. 2
Structure of SARS-CoV-2 and its replication process: a Scheme of SARS-CoV-2 structure; b transmission electron microscope images of SARS-CoV-2 virion; c the replicated process of SARS-CoV-2 in host cell. a, b Adapted with permission from Refs. [, 17], Copyright 2021 Wiley-VCH. c is adapted with permission from Ref. [15], Copyright 2021 Elsevier
Fig. 3
Fig. 3
Genome organization of SARS and SARS-like CoVs. Adapted with permission from Ref. [22] Copyright 2022 Springer Nature
Fig. 4
Fig. 4
Schematic diagram of RT-qPCR: a sample collection, b reverse transcription, c separation, d duplication, and e end of cycle. Reprinted with permission from Ref. [29], Copyright 2022 NHGRI
Fig. 5
Fig. 5
Schematic diagram of LAMP. LAMP uses a set of 4–6 primers that recognize 6–8 different sequences of target DNA. Synthesis is initiated by strand-displacing DNA polymerase, and two of the primers form loop structures, which is helpful for the subsequent rounds of amplification. Adapted with permission from Ref. [36], Copyright 2015 Elsevier
Fig. 6
Fig. 6
Schematic diagram of SHERLOCK. Adapted with permission from Ref. [43], Copyright 2020 Springer Nature
Fig. 7
Fig. 7
Schematic conception and dipstick assay of the LFIA test strips. Adapted with permission from Ref. [49], Copyright 2021 MDPI
Fig. 8
Fig. 8
Scheme of antigen-detection strip. Adapted with permission from Ref. [57], Copyright 2022 Elsevier
Fig. 9
Fig. 9
a Mechanism of CRISP-Cas12a biosensor and the freeze-dried reactions. SARS-CoV-2 RNA is released from lysis and target gene amplifies at room temperature and then Cas12a results in the cleavage of fluorescent ssDNA probes. The fluorescent outcome of the reaction was purified by the LFA and confirmed the positive result of COVID-19 diagnosis. b The bundle of fibers modified with CRISP-Cas12a biosensor. c Schematic diagram of the SARS-CoV-2 sensor. Puncture of the water reservoir initiated flow through aerosol region and freeze-dried reactions. Subsequently, viral particles collected from respiration in aerosol region downstream integrated into a µPAD device. The visual output is displayed by an LFA strip. d Image of a face mask integrated a SARS-CoV-2 sensor. Adapted with permission from ref. [68], Copyright 2021 Springer Nature
Fig. 10
Fig. 10
COVID-19 diagnosis was performed by chromatic change of solution. Anti-gene sequence of SARS-CoV-2 was modified on the surface of gold nanoparticles. When the gold nanoparticles were added into viral extraction solution, SARS-CoV-2 target gene would combine with anti-gene resulting in the agglomeration of Au nanoparticles and showing chromatic change from violet to blue. Adapted with permission from Ref. [69], Copyright 2020 American Chemical Society
Fig. 11
Fig. 11
Schematic illustration displays the synthesized procedures of MAA/Co2+ (up) and fabrication process of label-free chemiluminescent immunoassay for the rapid detection of the N protein (down). Adapted with permission from Ref. [71], Copyright 2021 American Chemical Society
Fig. 12
Fig. 12
Schematic illustration of the nanozyme chemiluminescence paper test for SARS-CoV-2 S-RBD antigen. Adapted with permission from Ref. [72], Copyright 2021 Elsevier
Fig. 13
Fig. 13
SERS-based detection mechanism for SARS-CoV-2 assay. a Structure diagram of the fishing mode device (AgAN-Au-AptRBD-N-M-Au). b Operating mechanism of the anti-SARS-CoV-2 IgM/IgG via the SERS-LFIA strip. a Reproduced with permission from Ref. [82], Copyright 2020 American Chemical Society; b Reproduced with permission from Ref. [83], Copyright 2021 Elsevier
Fig. 14
Fig. 14
Electrochemical biosensors for SARS-CoV-2 detection. a Graphene based electrochemical platform with AuNPs capped with ssDNA probes for the detection of SARS-CoV-2 virions. b The sketch-map of the test chip. c The configuration of a MolEMS g-FET and its sensing mechanism. a Reproduced with permission from Ref. [94], Copyright 2020 American Chemical Society; b reproduced with permission from ref. [95], Copyright 2021 Wiley-VCH; c reproduced with permission from Ref. [96], Copyright 2022 Springer Nature
Fig. 15
Fig. 15
Workflow of MS-based test for COVID-19 diagnosis. Reproduced with permission from Ref. [100], Copyright 2020 American Chemical Society
Fig. 16
Fig. 16
Schematic showing the COVID-19 diagnostic method based on a crowdsourced cough sound database and artificial intelligence cough test. Reproduced with permission from Ref. [120], Copyright 2020 University of California
Fig. 17
Fig. 17
Keywords network relationships related to COVID-19 research. Reproduced with permission from Ref. [126], Copyright 2022 Springer Nature
Fig. 18
Fig. 18
Smartphone-based biosensors for COVID-19 virus visual detection. a Schematic showing the smartphone-based electrochemical biosensors based on the supersandwich-type recognition strategy for RNA detection of COVID-19 virus [137]. b Digital image of a portable smartphone-based biosensor based on miniaturized electrochemical immunosensor made of laser-scribed graphene (LSG) and three-dimensional gold nanostructures (AuNS) for rapid POC COVID-19 diagnosis [138]. c Images acquired from a smartphone camera showing the improved signal-to-noise ratio due to the presence of modified agarose beads illuminated by a 450 nm laser diode [139]. d Digital image showing a smartphone camera was used to capture the capillary flow video of the tested samples. a Reproduced with permission from Ref. [137], Copyright 2021 Elsevier. b is reproduced with permission from Ref. [138], Copyright 2021 American Chemical Society. c Reproduced with permission from ref. [139], Copyright 2021 Royal Chemical Society. d Reproduced with permission from Ref. [129], Copyright 2022 Elsevier
Fig. 19
Fig. 19
The common challenges in the development of COVID-19 diagnostic techniques
Fig. 20
Fig. 20
Prospects of the COVID-19 diagnostic methods

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