综合的翻译分析和STE AI揭示了细胞应激过程中蛋白质生物合成的快速控制
Attila Horvath1, Yoshika Janapala1, Katrina Woodward1
1Division of Genome Sciences and Cancer, The John Curtin School of Medical Research, and The Shine-Dalgarno Centre for RNA Innovation, The Australian National University, Canberra, ACT 2601, Australia.
Nucleic acids research
|May 9, 2024
概括
我们开发了一种新的AI驱动的方法,即随机翻译效率 (STE),以准确测量蛋白质合成速率. 该工具揭示了细胞如何控制翻译的洞察力,并可以推进合成生物学和mRNA疗法.
科学领域:
- 分子生物学分子生物学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 精确量化翻译控制是至关重要的,但具有挑战性.
- 翻译mRNA的核糖体形成多核糖体,并且可以共同定位.
- 了解这些复杂物是解读蛋白质生物合成的关键.
研究的目的:
- 在mRNA上计算模型新的共同局部化的核糖体复合体.
- 开发一个准确和自我规范化的翻译标准.
- 为了研究mRNA翻译动态的快速变化.
主要方法:
- 增强的翻译复杂性配置测序 (eTCP-seq) 与体内交叉链接.
- 共同局部化的核糖体复合体的计算建模.
- 人工智能 (AI) 对核糖体足迹数据的分析.
- 随机转换效率 (STE) 的发展指标.
主要成果:
- 检测与翻译启动和蛋白质生物合成速率相关的长的dysome足迹.
- 识别共定位的核糖体,提供超越延长的洞察力.
- 通过绝对翻译速率,STE AI准确地对mRNA进行排名.
- 在葡萄糖耗尽的情况下,在酵母中展示了STE的实用性.
结论:
- 同定位的核糖体足迹为转化机制和多核糖体动力学提供了丰富的见解.
- STE是一种强大的新指标,用于量化mRNA翻译.
- STE可以帮助识别翻译控制元素和设计合成生物学应用程序.
- 这种方法有助于开发下一代mRNA疗法.
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