Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Paterna, Spain.
PLoS Comput Biol. 2022 May 6;18(5):e1010087. doi: 10.1371/journal.pcbi.1010087. eCollection 2022 May.
Gene expression is inherently stochastic and pervasively regulated. While substantial work combining theory and experiments has been carried out to study how noise propagates through transcriptional regulations, the stochastic behavior of genes regulated at the level of translation is poorly understood. Here, we engineered a synthetic genetic system in which a target gene is down-regulated by a protein translation factor, which in turn is regulated transcriptionally. By monitoring both the expression of the regulator and the regulated gene at the single-cell level, we quantified the stochasticity of the system. We found that with a protein translation factor a tight repression can be achieved in single cells, noise propagation from gene to gene is buffered, and the regulated gene is sensitive in a nonlinear way to global perturbations in translation. A suitable mathematical model was instrumental to predict the transfer functions of the system. We also showed that a Gamma distribution parameterized with mesoscopic parameters, such as the mean expression and coefficient of variation, provides a deep analytical explanation about the system, displaying enough versatility to capture the cell-to-cell variability in genes regulated both transcriptionally and translationally. Overall, these results contribute to enlarge our understanding on stochastic gene expression, at the same time they provide design principles for synthetic biology.
基因表达本质上是随机的且普遍受到调控。虽然已经有大量的理论与实验相结合的工作来研究噪声如何在转录调控中传播,但基因在翻译水平上的随机调控行为仍知之甚少。在这里,我们构建了一个合成遗传系统,其中靶基因受蛋白质翻译因子的下调,而该因子又受到转录调控。通过在单细胞水平上同时监测调节剂和被调节基因的表达,我们量化了该系统的随机性。我们发现,通过使用蛋白质翻译因子,可以在单细胞中实现紧密的抑制,从基因到基因的噪声传播得到缓冲,并且被调节的基因对全局翻译扰动以非线性方式敏感。一个合适的数学模型对于预测系统的传递函数非常重要。我们还表明,用介观参数(如平均表达和变异系数)参数化的伽马分布为系统提供了深入的分析解释,具有足够的通用性,可以捕捉到转录和翻译调控的基因的细胞间变异性。总的来说,这些结果有助于扩大我们对随机基因表达的理解,同时为合成生物学提供了设计原则。