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使用增强的ISDra2 TnpB系统和深度学习预测 ωRNAs的有效基因组编辑

Kim Fabiano Marquart^1,2, Nicolas Mathis¹, Amina Mollaysa³

¹Institute of Pharmacology and Toxicology, University of Zurich, Zürich, Switzerland.

|September 23, 2024

概括

研究人员优化了转子子编码的TnpB蛋白质用于哺乳动物基因组编辑,创造了TnpBmax. 一种深度学习模型,TEEP,预测了编辑效率,使得潜在的治疗应用在小鼠体内能够进行高水平的编辑.

科学领域:

分子生物学分子生物学
基因组工程是基因组工程.
生物技术是生物技术.

背景情况:

转子子编码的TnpB蛋白质是紧的第2类V型CRISPR效应器前身.
现有的基因组编辑工具面临大小和准方面的局限性.
来自Deinococcus radiodurans的ISDra2 TnpB是一种有前途的超紧基因组编辑器.

研究的目的:

为了优化ISDra2 TnpB,在哺乳动物细胞中进行增强基因组编辑.
通过开发变体来扩大ISDra2 TnpB的准能力.
创建TnpB编辑效率的预测模型,以指导应用程序.

主要方法:

对哺乳动物细胞的工程Deinococcus radiodurans (ISDra2) TnpB转化为TnpBmax.
开发了具有K76突变的TnpB变体,以改变目标相邻的图案识别.
在10,211个站点生成了大量的编辑效率数据集.
开发了一个深度学习模型 (TEEP) 来预测指导RNA活动.
在小鼠模型中通过腺相关病毒 (AAV) 载体传递TnpBmax.

主要成果:

与野生类型相比,TnpBmax在编辑效率上平均提高了4.4倍.
突变变种扩大了ISDra2 TnpB的准范围.
在指导RNA活性方面,TEEP实现了高预测性能 (r > 0.8).
在体内实现了高的编辑效率:75.3%在小鼠肝脏和65.9%在小鼠大脑.

结论:

优化的TnpBmax和变体提供了增强和扩展的基因组编辑功能.
TEEP模型准确地预测了TnpB编辑效率,促进了工具设计.
通过AAV传递的TnpBmax显示出在研究和治疗中体内基因组编辑的巨大潜力.
这项研究提供了一套工具,用于推进TnpB作为超紧的可编程内核酶.

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