Microbial Sciences Institute, West Haven, Connecticut; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut; Howard Hughes Medical Institute, New Haven, Connecticut.
Microbial Sciences Institute, West Haven, Connecticut; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut; Howard Hughes Medical Institute, New Haven, Connecticut; Department of Microbial Pathogenesis, Yale School of Medicine, Yale University, New Haven, Connecticut.
Biophys J. 2018 Apr 10;114(7):1718-1729. doi: 10.1016/j.bpj.2018.02.010.
Genetically identical cells exhibit diverse phenotypes even when experiencing the same environment. This phenomenon in part originates from cell-to-cell variability (noise) in protein expression. Although various kinetic schemes of stochastic transcription initiation are known to affect gene expression noise, how posttranscription initiation events contribute to noise at the protein level remains incompletely understood. To address this question, we developed a stochastic simulation-based model of bacterial gene expression that integrates well-known dependencies between transcription initiation, transcription elongation dynamics, mRNA degradation, and translation. We identified realistic conditions under which mRNA lifetime and transcriptional pauses modulate the protein expression noise initially introduced by the promoter architecture. For instance, we found that the short lifetime of bacterial mRNAs facilitates the production of protein bursts. Conversely, RNA polymerase (RNAP) pausing at specific sites during transcription elongation can attenuate protein bursts by fluidizing the RNAP traffic to the point of erasing the effect of a bursty promoter. Pause-prone sites, if located close to the promoter, can also affect noise indirectly by reducing both transcription and translation initiation due to RNAP and ribosome congestion. Our findings highlight how the interplay between transcription initiation, transcription elongation, translation, and mRNA degradation shapes the distribution in protein numbers. They also have implications for our understanding of gene evolution and suggest combinatorial strategies for modulating phenotypic variability by genetic engineering.
即使在经历相同环境时,遗传上相同的细胞也会表现出不同的表型。这种现象部分源于蛋白质表达中的细胞间变异性(噪声)。尽管已知各种随机转录起始的动力学方案会影响基因表达噪声,但转录起始后事件如何影响蛋白质水平的噪声仍不完全清楚。为了解决这个问题,我们开发了一个基于随机模拟的细菌基因表达模型,该模型整合了转录起始、转录延伸动力学、mRNA 降解和翻译之间的已知依赖性。我们确定了在何种实际条件下,mRNA 寿命和转录暂停会调节最初由启动子结构引入的蛋白质表达噪声。例如,我们发现细菌 mRNA 的短寿命有助于产生蛋白质爆发。相反,RNA 聚合酶(RNAP)在转录延伸过程中在特定位置暂停,可以通过使 RNAP 流量流化来减弱蛋白质爆发,从而消除突发启动子的影响。如果暂停倾向的位点靠近启动子,也可以通过 RNAP 和核糖体拥塞导致转录和翻译起始减少,从而间接影响噪声。我们的研究结果强调了转录起始、转录延伸、翻译和 mRNA 降解之间的相互作用如何塑造蛋白质数量的分布。它们还对我们理解基因进化具有启示意义,并为通过基因工程调节表型可变性提供了组合策略。