Computational Design of gRNAs Targeting Genetic Variants Across HIV-1 Subtypes for CRISPR-Mediated Antiviral Therapy. Academic Article uri icon

Overview

abstract

  • Clustered regularly interspaced short palindromic repeats (CRISPR)-based HIV-1 genome editing has shown promising outcomes in in vitro and in vivo viral infection models. However, existing HIV-1 sequence variants have been shown to reduce CRISPR-mediated efficiency and induce viral escape. Two metrics, global patient coverage and global subtype coverage, were used to identify guide RNA (gRNA) sequences that account for this viral diversity from the perspectives of cross-patient and cross-subtype gRNA design, respectively. Computational evaluation using these parameters and over 3.6 million possible 20-bp sequences resulted in nine lead gRNAs, two of which were previously published. This analysis revealed the benefit and necessity of considering all sequence variants for gRNA design. Of the other seven identified novel gRNAs, two were of note as they targeted interesting functional regions. One was a gRNA predicted to induce structural disruption in the nucleocapsid binding site (Ψ), which holds the potential to stop HIV-1 replication during the viral genome packaging process. The other was a reverse transcriptase (RT)-targeting gRNA that was predicted to cleave the subdomain responsible for dNTP incorporation. CRISPR-mediated sequence edits were predicted to occur on critical residues where HIV-1 has been shown to develop resistance against antiretroviral therapy (ART), which may provide additional evolutionary pressure at the DNA level. Given these observations, consideration of broad-spectrum gRNAs and cross-subtype diversity for gRNA design is not only required for the development of generalizable CRISPR-based HIV-1 therapy, but also helps identify optimal target sites.

publication date

  • March 9, 2021

Research

keywords

  • HIV-1
  • RNA, Guide, Kinetoplastida

Identity

PubMed Central ID

  • PMC7985454

Scopus Document Identifier

  • 85102918616

Digital Object Identifier (DOI)

  • 10.1186/s12977-015-0150-z

PubMed ID

  • 33768011

Additional Document Info

volume

  • 11