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Determinants of Efficient Modulation of Ribosomal Traffic Jams
Computational and Structural Biotechnology Journal ( IF 6 ) Pub Date : 2021-11-08 , DOI: 10.1016/j.csbj.2021.10.030
Sophie Vinokour 1 , Tamir Tuller 1, 2
Affiliation  

mRNA translation is the process which consumes most of the cellular energy. Thus, this process is under strong evolutionary selection for its optimization and rational optimization or reduction of the translation efficiency can impact the cell growth rate. Algorithms for modulating cell growth rate can have various applications in biotechnology, medicine, and agriculture. In this study, we demonstrate that the analysis of these algorithms can also be used for understanding translation.

We specifically describe and analyze various generic algorithms, based on comprehensive computational models and whole cell simulations of translation, for introducing silent mutations that can either reduce or increase ribosomal traffic jams along the mRNA. As a result, more or less resources are available, for the cell, promoting improved or reduced cells growth-rate, respectively. We then explore the cost of these algorithms' performance, in terms of their computational time, the number of mutations they introduce, the modified genomic region, the effect on local translation rates, and the properties of the modified genes.

Among others, we show that mRNA levels of a gene are much stronger predictors for the effect of its engineering on the ribosomal pool than the ribosomal density of the gene. We also demonstrate that the mutations at the ends of the coding regions have a stronger effect on the ribosomal pool. Furthermore, we report two optimization algorithms that exhibit a tread-off between the number of mutations they introduce and their executing time.

The reported results here are fundamental both for understanding the biophysics and evolution of translation, as well as for developing efficient approaches for its engineering.



中文翻译:

有效调节核糖体交通堵塞的决定因素

mRNA翻译是消耗大部分细胞能量的过程。因此,该过程处于对其优化的强进化选择下,​​并且翻译效率的合理优化或降低会影响细胞生长速率。调节细胞生长速率的算法在生物技术、医学和农业中具有多种应用。在这项研究中,我们证明了对这些算法的分析也可以用于理解翻译。

我们基于综合计算模型和翻译的全细胞模拟,专门描述和分析了各种通用算法,用于引入沉默突变,这些突变可以减少或增加 mRNA 上的核糖体交通拥堵。结果,或多或少的资源可用于细胞,分别促进提高或降低的细胞生长速率。然后,我们探讨了这些算法的性能成本,包括计算时间、引入的突变数量、修改后的基因组区域、对局部翻译率的影响以及修改后基因的特性。

其中,我们表明基因的 mRNA 水平比基因的核糖体密度更能预测其工程对核糖体库的影响。我们还证明编码区末端的突变对核糖体库有更强的影响。此外,我们报告了两种优化算法,它们在它们引入的突变数量与其执行时间之间表现出平衡。

此处报告的结果对于理解翻译的生物物理学和进化以及为其工程开发有效方法都至关重要。

更新日期:2021-11-08
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