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Title

Towards the diagnosis of dengue virus and its serotypes using designed CRISPR/Cas13 gRNAs

 

Authors

Archana Prajapati*, AshmitaTandon* & Vikrant Nain#

 

Affiliation

School of Biotechnology, Gautam Buddha University, Greater Noida-201312, Uttar Pradesh, India; #Corresponding author,*Equal contribution

 

Email

Archana Prajapati - E-mail: btphd2018003@gbu.ac.in
Vikrant Nain E-mail: vikrant@gbu.ac.in

 

Article Type

Research Article

 

Date

Received July 2, 2022; Revised August 31, 2022; Accepted August 31, 2022, Published August 31, 2022

 

Abstract

Dengue Virus (DENV) is a mosquito-borne virus that is prevalent in the world's tropical and subtropical regions. Therefore, early detection and surveillance can help in the management of this disease. Current diagnostic methods rely primarily on ELISA, PCR, and RT-PCR, among others, which can only be performed in specialized laboratories and require sophisticated instruments and technical expertise. CRISPR-based technologies on the other hand have field-deployable viral diagnostics capabilities that could be used in the development of point-of-care molecular diagnostics. The first step in the field of CRISPR-based virus diagnosis is to design and screen gRNAs for high efficiency and specificity. In the present study, we employed a bioinformatics approach to design and screen DENV CRISPR/Cas13 gRNAs for conserved and serotype-specific variable genomic regions in the DENV genome. We identified one gRNA sequence specific for each of the lncRNA and NS5 regions and identified one gRNA against each of DENV1, DENV2, DENV3, and DENV4 to distinguish the four DENV serotypes. These CRISPR/Cas13 gRNA sequences will be useful in diagnosing the dengue virus and its serotypes for in vitro validation and diagnostics.

 

Keywords

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), Cas13, Dengue virus, serotypes, diagnosis, gRNA pool, secondary structure, free energy.

 

Citation

Prajapati et al. Bioinformation 18(8): 661-668 (2022)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.