充电tRNA的可用性驱动最大的蛋白质合成在Codon使用偏差的中间水平
Alexis M Hill1, Kelly To1, Claus O Wilke2
1Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA.
Bulletin of mathematical biology
|January 13, 2026
概括
当tRNA充电有限时,优化编码子的使用以匹配tRNA池可以增强蛋白质的产生. 相反,使用首选的编码子最大化蛋白质输出,当tRNA充电不是瓶时.
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:
- 同义代码的使用会影响蛋白质表达率.
- 现有的翻译模型往往忽略了tRNA动态,将充电的tRNA视为固定资源.
- 这种简化可能会限制充电tRNA稀缺时的预测准确性.
研究的目的:
- 开发一个包含明确tRNA动态和重新充电的数学模型.
- 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.
- 解释菌体T7中的子去优化敏感性.
主要方法:
- 导出具有明确tRNA动态的数学翻译模型.
- 对tRNA充电和重新充电系统的随机模拟.
- 使用tRNA动态模型增强菌体T7的全细胞模拟.
主要成果:
- 当tRNA充电受到限制时,将编码子频率与tRNA池相匹配是蛋白质生产的最佳方式.
- 当tRNA充电没有限制时,只使用首选的编码子可以最大限度地提高蛋白质产量.
- T7主要囊基因的高表达率导致稀有充电tRNAs的耗尽,解释了对代码子去优化的敏感性.
结论:
- TRNA动态对于准确建模翻译效率至关重要.
- 子使用优化策略取决于充电tRNAs的可用性.
- 该模型阐明了tRNA枯竭如何影响基因表达和对子偏差的敏感性.
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