充电tRNA的可用性驱动最大的蛋白质合成在代码子使用偏差的中间水平
Alexis M Hill1, Kelly To1, Claus O Wilke1
1Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA.
bioRxiv : the preprint server for biology
|July 16, 2025
概括
当tRNA充电受到限制时,将编码子频率与tRNA池匹配是最佳的. 当充电不限制时,使用首选的编码子可以最大限度地提高蛋白质的产生,这解释了基因表达敏感性.
科学领域:
- 分子生物学分子生物学
- 生物物理学的生物物理.
- 计算生物学 计算生物学
背景情况:
- 同义代码子的使用通过影响翻译速度影响蛋白质表达率.
- 现有的翻译模型往往过于简化了tRNA动态,将充电的tRNA视为固定的资源,这可能会限制预测的准确性.
研究的目的:
- 开发一个数学模型的翻译包含明确的tRNA动态和重新充电.
- 为了研究在不同的tRNA可用性下,代使用率和蛋白质表达率之间的关系.
主要方法:
- 基于随机模拟的数学转换模型的推导.
- 系统地探索使用模型对蛋白质表达的子使用效应.
- 用tRNA动态模型增强菌体T7的全细胞模拟.
主要成果:
- 确定当tRNA充电是限制因素时,将编码频率与tRNA池匹配是最佳的.
- 确定使用100%的首选编码子在tRNA充电不限制时是蛋白质生产的最佳选择.
- 证明高表达率可以耗尽罕见的充电tRNA,影响基因表达,如T7主要囊基因所见.
结论:
- 对tRNA动态的准确建模对于理解翻译效率至关重要,尤其是在充电tRNA有限的情况下.
- 对于最佳蛋白质表达的子使用策略取决于tRNA充电系统的特定约束.
- 该模型解释了高度表达的基因,如T7主要囊基因的观察到的敏感性,由于tRNA耗尽而导致的代脱优化.
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