Design of CRISPR-Based Targets for the Development of a Diagnostic Method for SARS-CoV-2: An in Silico Approach
Abraham Peele Karlapudi1, Chinna Venkateswarulu Thirupati1, Krupanidhi Srirrama1, Divyashree Coimbatore Nageswaran2, Indira Mikkili,1, Vijayasai Sai Ayyagari1, Ranganadha Reddy Reddy Aluri1, Yasha Nazir Butt3, Aishwarya Gangadhar41Department of Bio-Technology, Vignan’s Foundation for Science, Technology and Research, India., 2Tango Group International Ltd., United Kingdom., 3Department of Chemistry, Wayne State University, Michigan, USA., 4,
In this present COVID-19 pandemic, rapid detection kits like STOPCovid have been developed for home use in order to detect for the presence of the viral strain, SARS-CoV-2. They are simple and easy to use, and are currently under experimental trials. The STOPCovid kit requires an RNA-sequence specific CRISPR-Cas system. Development of CRISPR-based viral detection kits for COVID-19 requires programmable nucleases, including Cas12 and Cas13. The SARS-CoV-2 spike glycoprotein coding for the S-gene promotes the entry of this novel coronavirus into the cell. The S-gene sequence information has been used to design single guide RNA (sgRNA) to target specific nucleic acid sequence. In the present study, Cas12 nuclease-specific protospacer adjacent motif (PAM) and downstream target sequences were identified from conserved regions of the S-gene receptor binding domain (RBD) using CHOPCHOP and NEB computational tools to design sgRNA. Further, the in silico expression vector was constructed using SnapGene software. The findings of this study will help in designing a CRISPR-based diagnostic kit for the detection of SARS-CoV-2. However, computationally designed sgRNA requires to be tested in vitro for demonstrating its potential and efficiency in the detection of this novel coronavirus. Keywords: CRISPR-Cas12, CHOPCHOP, SARS-CoV-2, sgRNA
Cite This Article
Karlapudi A, Thirupati C, Srirrama K, Nageswaran D, Mikkili, I, Ayyagari V, et al. Design of CRISPR-Based Targets for the Development of a Diagnostic Method for SARS-CoV-2: An in Silico Approach. EJMO. 2020; 4(4): 304-308
Corresponding Author: Chinna Venkateswarulu Thirupati