Department of Physics, University of Washington, Seattle, WA 98195, USA.
Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
Sci Adv. 2024 Aug 23;10(34):eado3095. doi: 10.1126/sciadv.ado3095.
The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model provides insights for principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern gene expression processes, and these principles have broad implications for cellular function.
基因表达的过程本质上是随机的,即使对于生长所必需的基因也是如此。细胞如何在噪声中最大限度地提高适应性?为了回答这个问题,我们构建了一个数学模型来探索代谢负荷和生长鲁棒性之间的权衡。该模型为中心法则调控的原则提供了一些见解:许多基因的最佳蛋白质表达水平远远超过了需要的水平。必需基因的转录水平高于每个细胞周期一个信息分子的下限。基因表达是通过转录和翻译之间的负载平衡来实现的。我们提供的证据表明,这些调控原则都得到了体现。这些结果表明,鲁棒性和代谢负荷决定了控制基因表达过程的全局调控原则,这些原则对细胞功能具有广泛的影响。