Suppr超能文献

翻译速度决定了工程化抑制 tRNA 对致病性无义突变的疗效。

Translation velocity determines the efficacy of engineered suppressor tRNAs on pathogenic nonsense mutations.

机构信息

Institute of Biochemistry and Molecular Biology, University of Hamburg, 20146, Hamburg, Germany.

Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA, 30322, USA.

出版信息

Nat Commun. 2024 Apr 5;15(1):2957. doi: 10.1038/s41467-024-47258-9.

Abstract

Nonsense mutations - the underlying cause of approximately 11% of all genetic diseases - prematurely terminate protein synthesis by mutating a sense codon to a premature stop or termination codon (PTC). An emerging therapeutic strategy to suppress nonsense defects is to engineer sense-codon decoding tRNAs to readthrough and restore translation at PTCs. However, the readthrough efficiency of the engineered suppressor tRNAs (sup-tRNAs) largely varies in a tissue- and sequence context-dependent manner and has not yet yielded optimal clinical efficacy for many nonsense mutations. Here, we systematically analyze the suppression efficacy at various pathogenic nonsense mutations. We discover that the translation velocity of the sequence upstream of PTCs modulates the sup-tRNA readthrough efficacy. The PTCs most refractory to suppression are embedded in a sequence context translated with an abrupt reversal of the translation speed leading to ribosomal collisions. Moreover, modeling translation velocity using Ribo-seq data can accurately predict the suppression efficacy at PTCs. These results reveal previously unknown molecular signatures contributing to genotype-phenotype relationships and treatment-response heterogeneity, and provide the framework for the development of personalized tRNA-based gene therapies.

摘要

无义突变——约占所有遗传疾病的 11%的根本原因——通过将有意义的密码子突变为过早的终止或终止密码子(PTC),从而提前终止蛋白质合成。一种新兴的治疗无义缺陷的策略是设计能通读并在 PTC 处恢复翻译的有意义密码子解码 tRNA。然而,工程化的抑制 tRNA(sup-tRNA)的通读效率在很大程度上取决于组织和序列上下文,并且对于许多无义突变,其尚未产生最佳的临床疗效。在这里,我们系统地分析了各种致病性无义突变的抑制效果。我们发现,PTC 上游序列的翻译速度调节 sup-tRNA 的通读效率。对抑制最具抵抗力的 PTC 嵌入到翻译速度突然反转的序列中,导致核糖体碰撞。此外,使用 Ribo-seq 数据模拟翻译速度可以准确预测 PTC 处的抑制效果。这些结果揭示了导致基因型-表型关系和治疗反应异质性的未知分子特征,并为基于 tRNA 的个性化基因治疗的发展提供了框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc40/10997658/5cd3a77f2107/41467_2024_47258_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验