Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Department of Biology, Stanford University, Stanford, CA, 94305, USA.
Nat Commun. 2023 Jul 31;14(1):4594. doi: 10.1038/s41467-023-40199-9.
Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test.
使合成细胞的工程化成为常规操作需要事先指定每种分子的需求量。目前还缺乏基于物理的方法来估计全细胞合成生物学中所需的分子丰度。在这里,我们使用胶体动力学模拟器来预测 tRNA 丰度如何影响蛋白质合成速率。我们从零开始使用合理的设计和直接 RNA 合成来制作 21 种合成 tRNA 替代物。我们使用进化算法在计算机辅助设计框架内设计翻译系统,这些系统根据 tRNA 丰度的差异预测工作得更快或更慢。我们构建并测试了如此指定的合成系统,并发现预期和观察到的系统之间存在定性一致性。基于第一性原理的建模与自下而上的实验相结合,有助于实现超越修补和测试的分子到细胞规模的合成生物学设计构建工作框架。