Advances in Biosensing Technologies for Diagnosis of COVID-19
Abstract
:1. Introduction
2. Conventional Methods for Detecting SARS-CoV-2
3. Principles and Application of Biosensors
4. Biomarkers in COVID-19
4.1. Nucleic Acid-Based Biosensors
4.2. Biosensors for the Detection of Antigens (Proteins)
4.3. Biosensors for the Detection of Antibodies
5. Currently Applied Biomarker Detection Methods in COVID-19 Diagnosis
6. Other Biomarkers for COVID-19 Diagnosis
7. Artificial Intelligence (AI) and Internet of Things (IoT) in COVID-19 Detection
8. Challenges and Future Prospective
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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SARS-CoV-2 Target | Detection Method | Readout | LOD | Assay Time | Sensitivity and Specificity | Reference |
Nucleic acid-based biosensors | ||||||
SARS-CoV-2 RNA | DNA caped Au Nanoparticles | Visual | 0.18 ng/L | 10 | - | [37] |
Rdrp1, rdrp2, E, N (n1, n2 and n3) genes | RT-PCR | Fluorescence | - | <90 min | 94% 100% | [36] |
SRAS-CoV-2 RNA (N-Gene) | Swab-to RT-LAMP | Visual | - | - | 97.5% 99.7% | [39] |
RdRp gene | RT-LAMP | Visual | - | 30 min | 95.74% 99.95% | [40] |
SEAS-CoV-2 RNA | Microfluidic-integrated lateral flow recombinase polymerase amplification (MI-IF-RPA) | Visual | 1 copy/µL | 30 min | 97% 100% | [45] |
SARS-CoV-2 RNA | Microfluid integrated LAMP-RPA | Fluorescence | 10 copies | 60 min | 95.83% 94.12% | [46] |
SARS-CoV-2 N-Gene | Reverse transcription recombinase-aided amplification coupled with lateral flow dipstick (RT-RAA/LFD) | Visual | 1 copy/µL | 30 min | 100% 100% | [49] |
SARS-CoV-2 Orf1ab Gene | Reverse transcription recombinase-aided amplification (RT-RAA) | Fluorescence | 0.48/L | 25 min | - 100% | [50] |
ORF1ab gene | CRISPR/Cas9-mediated triple-line lateral flow assay (TL-LFA) integrated with (RT-RPA) | Visual | 100 copies/25 µL | 60 min | - | [60] |
Viral protein-based biosensors | ||||||
S-protein antigen | BERA (bioelectric recognition immunoassay) | Electric biosensor Electrical Signal | 1 fg/mL | - | - | [71] |
S-protein antigen | Electrochemical technique | Electrical Signal | 19 ng/mL | - | - | [72] |
S-protein antigen | Graphene field effect transistor (GrFET) | Sensitive graphene field effect transistor | 0.2 pM | 2 min | - | [73] |
N-protein antigen | Molecularly imprinted polymers (MIPs) | Electrical Signal | 15 fM | - | - | [74] |
N-protein antigen | Electrochemical technique | Electrical Signal | 8 ng/mL | - | - | [72] |
N-protein antigen | Optical technique | Visual | <100 copies/mL | - | - | [75] |
N-protein antigen | Electrochemical | Square wave voltammetry | 0.4 pg/mL | - | [76] | |
Antibody-based biosensors | ||||||
S-protein antibody | Label-free paper-based electrochemical biosensor | Electrochemical Signal | 10.1 ng/mL | 13 min | - | [77] |
Antibodies | Lateral flow immunoassay (LFIA) | Visual | - | 15 min | 88.6% 90.63% | [78] |
Neutralizing antibodies | Optic-biolayer interferometry | - | 10 ng/mL | 7.5–13 min | - | [79] |
Neutralizing antibodies | 100 ng/mL | Visual | 100 ng/mL | - | - | [80] |
S-protein antibody | Fluorophore conjugated Janus emulsion particle | Optical Image and Fluorescence | 200 ng/mL | 120 min | - | [81] |
S-protein antibody | Opto-microfluidic sensing device | LSPR | 0.08 ng/mL | 30 min | - | [82] |
S-protein antibody | Electrochemical (differential pulse voltammetry) | Electrochemical Signal | 0.3 fg/mL | 20 min | - | [83] |
Biological Component | Diagnostic Approach | Method of Detection | Reaction Time | Advantages | Disadvantages |
Imaging for medical diagnosis | X-ray/CT scan | Chest | 1 h | More sensitive to the status of the disease’s infection and organ damage. Combined with RT-PCR enhance the sensitivity | Unable to differentiate between different viral-mediated pneumonia. Equipment is expensive, needs well-trained expert to operate |
Serological parameters | Rapid antibody test (IgG and IgM) | IgG and IgM levels in serum | 20–30 min | Rapid, identification of specific viral infection | Less sensitivity and specificity. False positive. Unstable, not suitable to storage for long time |
Viral genome | Nucleic acid Amplification/Sequencing | RNA amplification (RT-PCR)Genome sequencing (NGS) RT-LAMP, CRISPER | 5–6 h ~2 days 1–2 hrs | Gold standard for viral detection, High selectivity and specificity. High accuracy High selectivity and specificity | Expensive, laborious, time-consuming, needs trained technicians. Unable to detect postinfection stage Probability for contamination, false positive. Primer design is complicated |
Viral proteins | Viral (S, N, E, and M) Proteins | Lateral flow immunoassay | 20–30 min | Fast and low cost, no need of sample pretreatment, moderate specificity and sensitivity, easy to execute. Immunity against the infection | No information about the early infection stage. Long time storage at room temperature is not possible. Possibility of false positive |
Optical, electrochemical, and microfluidic biosensors | 2–20 min | Fast and low cost, no need for sample pretreatment, multiple sample analysis, high specificity and sensitivity, easy to execute. Can be integrated with any platform | Needs more attention to obtain accurate results. Adsorption of nonspecific molecules on the electrode. Autofluorescence from nonspecific biomolecules. Miniaturizing, scaling up, and commercialization is challenging |
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Alsalameh, S.; Alnajjar, K.; Makhzoum, T.; Al Eman, N.; Shakir, I.; Mir, T.A.; Alkattan, K.; Chinnappan, R.; Yaqinuddin, A. Advances in Biosensing Technologies for Diagnosis of COVID-19. Biosensors 2022, 12, 898. https://doi.org/10.3390/bios12100898
Alsalameh S, Alnajjar K, Makhzoum T, Al Eman N, Shakir I, Mir TA, Alkattan K, Chinnappan R, Yaqinuddin A. Advances in Biosensing Technologies for Diagnosis of COVID-19. Biosensors. 2022; 12(10):898. https://doi.org/10.3390/bios12100898
Chicago/Turabian StyleAlsalameh, Sulaiman, Khalid Alnajjar, Tariq Makhzoum, Noor Al Eman, Ismail Shakir, Tanveer Ahmad Mir, Khaled Alkattan, Raja Chinnappan, and Ahmed Yaqinuddin. 2022. "Advances in Biosensing Technologies for Diagnosis of COVID-19" Biosensors 12, no. 10: 898. https://doi.org/10.3390/bios12100898
APA StyleAlsalameh, S., Alnajjar, K., Makhzoum, T., Al Eman, N., Shakir, I., Mir, T. A., Alkattan, K., Chinnappan, R., & Yaqinuddin, A. (2022). Advances in Biosensing Technologies for Diagnosis of COVID-19. Biosensors, 12(10), 898. https://doi.org/10.3390/bios12100898