Abstract
Background:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global health crisis, emphasizing the urgent need for accurate and rapid diagnostic tools. Modern molecular biology technologies, including CRISPR-Cas systems, provide highly efficient strategies for viral detection. Bioinformatic pipelines are essential for identifying conserved genomic regions and enabling rational single-guide RNA (sgRNA) design.
Methods:
This study aimed to design specific sgRNAs targeting the spike gene of SARS-CoV-2 isolates from Iranian patients using the SHERLOCK diagnostic platform. Complete genomes of the RefSeq virus and 470 SARS-CoV-2 isolates, representing all variants of concern (VOCs) detected in Iran, were retrieved from the NCBI and GISAID databases. Multiple sequence alignment with ClustalW identified conserved sequences within the receptor-binding domain (RBD) that differ from the RBD of SARS-CoV and MERS-CoV RefSeq genomes. Based on these regions, sgRNAs and isothermal amplification primers were designed using ADAPT, OLIGO7, and the UCSC Genome Browser to maximize diagnostic sensitivity and specificity. Secondary and tertiary structures of sgRNA-target complexes were analyzed via RNAfold and RNAup to select the most efficient sgRNA–amplicon combination.
Results:
Twenty-two–nucleotide sgRNA candidates were initially selected based on sequence alignment, showing high similarity to the SARS-CoV-2 RefSeq and low homology to SARS-CoV and MERS-CoV genomes. Analyses of secondary structures, RNA–RNA interactions, and free energy identified 6 sgRNAs with favorable 2-dimensional conformations and strong interaction profiles. Among these, the sgRNA1–Amplicon2 sequence exhibited the most stable 3-dimensional structure and a molecular docking score of −309.67, indicating high sensitivity and specificity for viral detection.
Conclusion:
This study successfully designed an sgRNA with high sensitivity and specificity for rapid SARS-CoV-2 detection using the CRISPR-Cas13a system, informed by genomic analysis of Iranian isolates. The proposed approach provides an efficient framework for the rapid design and deployment of CRISPR-based diagnostic tools applicable to diverse viral pathogens.
Keywords
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Supplementary Material
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