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中国生物工程杂志

China Biotechnology
China Biotechnology  2022, Vol. 42 Issue (8): 63-73    DOI: 10.13523/j.cb.2204054
    
SARS-CoV-2 SNV Genotyping Test Technology
WANG Tao-xue1,2,3,LIU Qian1,2,3,QI Hao1,2,3,*()
1. School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
2. Key Laboratory of Systems Bioengineering of Ministry of Education, Tianjin University, Tianjin 300072, China
3. Collaborative Innovation Center of Chemical Science and Engineering, Syn Bio Research Platform, Tianjin University, Tianjin 300072, China
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Abstract  

The global pandemic of the COVID-19 has had a major impact on the entire human society, and human beings are facing challenges such as fiscal stimulus, financial stress, and debt restructuring. Before the emergence of specific therapeutic drugs and methods, large-scale population screening and isolation has become the most effective method for epidemic management. However, the new strain of coronavirus this time has shown a very high genetic variability, with a statistical mutation rate of more than 2.3‰ as of March 31st, 2022. So far, new highly infectious virus strains have been emerging, and the number of mutant strains officially warned by the World Health Organization has reached 7. Therefore, in the next virus prevention and control and research, we not only need to detect SARS-CoV-2, but also need to explore accurate and practical single nucleotide variation (SNV) genotyping techniques, especially for large-scale population screening. It is not only necessary to obtain information on the SRAS-CoV-2, but also to accurately and quickly distinguish variant strains with higher infectivity and virulence. This paper briefly introduces the infection and mutation mechanism of the virus, and focuses on the classification and review of the existing main SARS-CoV-2 SNV genotyping techniques, hoping to provide insight into the development of new detection technologies.



Key wordsCOVID-19      SARS-CoV-2 test      Single nucleotide varication (SNV)     
Received: 21 April 2022      Published: 07 September 2022
ZTFLH:  Q934.9  
Corresponding Authors: Hao QI     E-mail: haoq@tju.edu.cn
Cite this article:

WANG Tao-xue,LIU Qian,QI Hao. SARS-CoV-2 SNV Genotyping Test Technology. China Biotechnology, 2022, 42(8): 63-73.

URL:

https://manu60.magtech.com.cn/biotech/10.13523/j.cb.2204054     OR     https://manu60.magtech.com.cn/biotech/Y2022/V42/I8/63

Fig.1 Schematic diagram of SARS-CoV-2 genome
VOC (variant of concern) VOI (variant of intention) Former VOI (former variant of intention)
Alpha B.1.1.7 Lambda C.37 Epsilon B.1.429
Beta B.1.351 Mu B.1.621 Zeta P.2
Gamma P.1 Eta B.1.525
Delta B.1.617.2 Theta P.3
Omicron B.1.1.529 Iota B.1.526
Omicron BA.2 Kappa B.1.617.1
Table 1 Existing SARS-CoV-2 variants
Fig.2 Schematic diagram of SARS-CoV-2 SNV physicochemical detection technology (a) HRM diagram to identify single nucleotide variation (b) HRM diagram to identify D614G mutation site (c) SERS diagram to identify single nucleotide variation
检测平台 检测位点 分型变体 分型时间 分型特异性 文献
TSP-PCR C251T S84L S/L 3 h 100% NGS [37]
RT-qPCR&TaqMan N501Y 46 min 99.7% NGS [38]
RT-ddPCR Δ69-70 N501Y Δ145 S982A Alpha 2.5 h 100% NGS [39]
RT-LAMP-BART L452R 1 h 95%NGS [40]
RT-PCR&CRISPR-Cas12a K417N∕T L452R∕Q T478K E484K∕Q
N501Y D614G
Alpha Beta
Gamma Delta
30 min 100%NGS [41]
MT-PCR P681R K417T K417N E484K Alpha Beta Gamma
Delta Kappa
4 h 100%NGS [42]
Table 2 Summary of SARS-CoV-2 genotyping detection platforms
ORF 1ab N E
靶标长度/nt 119 99 113
GC含量/% 48 52 41
荧光探针基团 FAM/BHQ1 FAM/TRMRA FAM/BHQ1
保守程度 较为保守 一般保守 保守
高频突变 Y32Y R203K/G204R A32A
检测特异性 较高 较高 较高
检测灵敏度 较高 一般 较高
Table 3 Comparison of RT-qPCR detection targets
检测平台 蛋白质 检测基因 时间 灵敏度 预扩增 文献
DETECTR Cas12a E gene and N gene 30 min 10~100拷贝/μL RT-LAMP [49]
CAS detec Cas12b RNA dependent polymerase 40 min 5拷贝/μL RT-RPA [50]
FELUDA FnCas9 N gene 1 h 110 fmol/L RT-PCR/RPA [51]
AIOD-CRISPR Cas12a N gene 40 min 4.6拷贝/μL RT-RPA [52]
SHERLOCK Cas13 S gene and ORF1ab gene 1 h 10~100拷贝/μL RT-qPCR [53]
CREST Cas13 N gene 1~2 h 10拷贝/μL RT-qPCR [54]
Table 4 CRISPR/Cas detection platforms for SARS-CoV-2
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