清脆的
基因组编辑
计算生物学
Cas9
基因组
核糖核蛋白
计算机科学
生物
核糖核酸
遗传学
基因
作者
Tao Wan,Dong Niu,Chuanbin Wu,Fu‐Jian Xu,George M. Church,Ping Yuan
标识
DOI:10.1016/j.mattod.2018.12.003
摘要
Clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein (CRISPR/Cas)-based genome editing has recently emerged as a new potential therapeutic tool for disease modeling and therapy in a wide range of biomedical fields. A comprehensive overview of the latest studies on different non-viral delivery materials for the delivery of CRISPR-Cas system is presented, including lipid nanoparticles, polymeric materials, hydrogels, gold nanoparticles, graphene oxide (GO), metal–organic frameworks, cell-penetrating peptide (CPP), black phosphorus nanosheet, and DNA nanostructure. Clustered regularly interspaced short palindromic repeat (CRISPR)/associated protein (CRISPR/Cas) system is an adaptable immune mechanism used by many bacteria to protect themselves from invading nucleic acids, and it has been recently exploited as an efficient tool for site-specific, programmable genome editing in both single cells and whole organisms with a precise manner. CRISPR/Cas system has been shown its great potentials for a wide range of biomedical applications, such as transcriptional control, epigenetic modification, genome-wide screening and chromosomal imaging, and treatment of genetic disorders. Despite these excitements, the shortage of delivery materials that can deliver genome editing tools (including plasmid DNA, mRNA, and ribonucleoprotein) represents one of the major challenges for successful CRISPR/Cas-based genome editing. This review seeks to provide a comprehensive overview of different types of carriers ranging from classic drug delivery materials to advanced drug delivery systems that can transport CRISPR/Cas systems and mediate genome editing at the targeted loci. The challenges and future prospects of the delivery materials for optimizing the CRISPR delivery system for clinical translations are also highlighted.
科研通智能强力驱动
Strongly Powered by AbleSci AI