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敏感,直接检测非编码的目标之外的基编辑器在主细胞中解和编辑

Tong Wang¹, Selin Jessa², Georgi K Marinov²

¹Department of Pathology, Stanford University, Stanford, CA, USA.

bioRxiv : the preprint server for biology

|October 3, 2025

概括

一个新的测序试验,beCasKAS,精确量化基编辑器非目标DNA变化. 这个工具可以识别更多的潜在网站,并帮助优化基因编辑应用程序的基础编辑器安全性.

科学领域:

分子生物学分子生物学
基因编辑技术的技术
基因组学就是基因组学.

背景情况:

基编辑器能够实现精确的DNA核酸变化,但很难量化它们的非目标活动.
基础编辑人员的非目标编辑对治疗应用构成重大挑战.

研究的目的:

开发和验证一种新的在纤维素测序试验 (beCasKAS),用于同时测量Cas9-介导解和除氨酶编辑.
在人类T细胞中全面识别和描述基编辑器的目标外站点.
评估mRNA剂量对基编辑器目标外配置的影响.
将beCasKAS与深度学习模型集成,用于对非目标编辑的风险分层.

主要方法:

开发beCasKAS,这是一个直接测序试验,可以丰富Cas9依赖R循环的编辑前.
在初级人类T细胞中应用beCasKAS,使用mRNA编码的ABE8e和ABE8e-SpRY基编辑器.
优化mRNA剂量以减轻非目标活性.
将beCasKAS与基本分辨率深度学习模型相结合.

主要成果:

与现有方法相比,beCasKAS试验发现了超过460倍的潜在非目标地点.
ABE8e和PAMless ABE8e-SpRY基准编辑器表现出明显的目标外的配置文件.
通过优化mRNA剂量,非目标活性被显著减轻.
深度学习模型成功地基于表观遗传失调潜力的风险分层非目标编辑.

结论:

beCasKAS提供了一种灵敏和简单的方法来量化基础编辑器在目标上和目标之外的活动.
这些发现可以更好地优化基础编辑器策略,以提高安全性和有效性.
这种工具对于提升基础编辑技术的治疗潜力至关重要.

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