美国麻省理工大学Tyler Jacks课题组的最新研究构建了一种先导编辑器小鼠,用于模拟体内广泛存在的体细胞突变。相关论文发表在2023年5月11日出版的《自然—生物技术》杂志上。
研究人员通过在小鼠中引入Cre诱导的先导编辑器研发了一个体内先导编辑系统。该模型可以快速、精确地重现来自原代组织细胞系和类器官中的各种突变,包括与临床耐药性相关的Kras突变和胰腺癌中常见的Trp53热点突变。通过该系统,研究人员使用脂质纳米颗粒在体内进行体细胞先导编辑,并且通过病毒递送先导编辑向导RNA或原位移植来模拟肺癌和胰腺癌。研究人员相信该模型将加速与癌症相关突变和复杂基因组合的功能研究,而这些研究很难用传统模型完成。
据介绍,基因工程小鼠模型只能模拟小部分诱导人癌症的遗传病变。现有的CRISPR-Cas9模型可以扩大这一部分,但这受到容易出错DNA修复的限制。
附:英文原文
Title: A prime editor mouse to model a broad spectrum of somatic mutations in vivo
Author: Ely, Zackery A., Mathey-Andrews, Nicolas, Naranjo, Santiago, Gould, Samuel I., Mercer, Kim L., Newby, Gregory A., Cabana, Christina M., Rideout, William M., Jaramillo, Grissel Cervantes, Khirallah, Jennifer M., Holland, Katie, Randolph, Peyton B., Freed-Pastor, William A., Davis, Jessie R., Kulstad, Zachary, Westcott, Peter M. K., Lin, Lin, Anzalone, Andrew V., Horton, Brendan L., Pattada, Nimisha B., Shanahan, Sean-Luc, Ye, Zhongfeng, Spranger, Stefani, Xu, Qiaobing, Snchez-Rivera, Francisco J., Liu, David R., Jacks, Tyler
Issue&Volume: 2023-05-11
Abstract: Genetically engineered mouse models only capture a small fraction of the genetic lesions that drive human cancer. Current CRISPR–Cas9 models can expand this fraction but are limited by their reliance on error-prone DNA repair. Here we develop a system for in vivo prime editing by encoding a Cre-inducible prime editor in the mouse germline. This model allows rapid, precise engineering of a wide range of mutations in cell lines and organoids derived from primary tissues, including a clinically relevant Kras mutation associated with drug resistance and Trp53 hotspot mutations commonly observed in pancreatic cancer. With this system, we demonstrate somatic prime editing in vivo using lipid nanoparticles, and we model lung and pancreatic cancer through viral delivery of prime editing guide RNAs or orthotopic transplantation of prime-edited organoids. We believe that this approach will accelerate functional studies of cancer-associated mutations and complex genetic combinations that are challenging to construct with traditional models.
DOI: 10.1038/s41587-023-01783-y