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如何为特定应用找到合适的 RNA 感应 CRISPR-Cas 系统。

How to Find the Right RNA-Sensing CRISPR-Cas System for an Application.

机构信息

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.

出版信息

Biosensors (Basel). 2022 Jan 19;12(2):53. doi: 10.3390/bios12020053.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf86/8869480/62161aa4e27b/biosensors-12-00053-g001.jpg

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