Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel.
The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
PLoS Comput Biol. 2020 Jul 10;16(7):e1008038. doi: 10.1371/journal.pcbi.1008038. eCollection 2020 Jul.
The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major translation components in the cell: ribosomes, mRNAs and tRNAs. It also includes, for the first time, fundamental aspects of translation, such as competition for ribosomes and tRNAs at a codon resolution while considering tRNAs wobble interactions and tRNA recycling. The model uses parameters that are tightly inferred from large scale measurements of translation. Furthermore, we demonstrate a robust modelling approach which relies on state-of-the-art practices of translation modelling and also provides a framework for easy generalizations. This novel approach allows simulation of thousands of mRNAs that undergo translation in the same cell with common resources such as ribosomes and tRNAs in feasible time. Based on this model, we demonstrate, for the first time, the direct importance of competition for resources on translation and its accurate modelling. An effective supply-demand ratio (ESDR) measure, which is related to translation factors such as tRNAs, has been devised and utilized to show superior predictive power in complex scenarios of heterologous gene expression. The devised model is not only more accurate than the existing models, but, more importantly, provides a framework for analyzing complex whole cell translation problems and variables that haven't been explored before, making it important in various biomedical fields.
mRNA 翻译模型的重要性已经在许多科学和生物技术领域得到了证明。然而，一个具有密码子分辨率和生物物理动力学的全细胞模型仍然缺乏。我们描述了大肠杆菌翻译的全细胞模型。该模型模拟了细胞中所有主要的翻译成分：核糖体、mRNA 和 tRNA。它还首次包括了翻译的基本方面，如在密码子分辨率上核糖体和 tRNA 的竞争，同时考虑了 tRNA 的摆动相互作用和 tRNA 回收。该模型使用的参数是从大规模翻译测量中严格推断出来的。此外，我们展示了一种稳健的建模方法，该方法依赖于翻译建模的最新实践，并且还提供了一个易于推广的框架。这种新方法允许使用相同的核糖体和 tRNA 等常见资源模拟在同一细胞中翻译的数千个 mRNA，这在可行的时间内是可行的。基于这个模型，我们首次展示了资源竞争对翻译及其准确建模的直接重要性。我们设计并利用了一种有效的供需比（ESDR）度量标准，该标准与 tRNA 等翻译因子有关，在异源基因表达的复杂情况下显示出了卓越的预测能力。所设计的模型不仅比现有模型更准确，而且更重要的是，为分析以前未探索过的复杂全细胞翻译问题和变量提供了一个框架，使其在各种生物医学领域都具有重要意义。
