Computational Bioscience Research Center (CBRC), Biological and Environmental Science and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
Centre de Biologie Structurale (CBS), INSERM, CNRS, Université de Montpellier, F-34090 Montpellier, France.
Biosensors (Basel). 2022 Jan 19;12(2):53. doi: 10.3390/bios12020053.
CRISPR-Cas systems have a great and still largely untapped potential for applications, in particular, for RNA biosensing. However, there is currently no systematic guide on selecting the most appropriate RNA-targeting CRISPR-Cas system for a given application among thousands of potential candidates. We provide an overview of the currently described Cas effector systems and review existing Cas-based RNA detection methods. We then propose a set of systematic selection criteria for selecting CRISPR-Cas candidates for new applications. Using this approach, we identify four candidates for RNA.
CRISPR-Cas 系统在应用方面具有巨大且尚未充分开发的潜力，特别是在 RNA 生物传感方面。然而，目前在成千上万的潜在候选者中，尚无针对特定应用选择最合适的靶向 RNA 的 CRISPR-Cas 系统的系统指南。我们概述了当前描述的 Cas 效应子系统，并回顾了现有的基于 Cas 的 RNA 检测方法。然后，我们提出了一套用于为新应用选择 CRISPR-Cas 候选者的系统选择标准。使用这种方法，我们确定了四个候选者用于 RNA。
