Mundt Max, Anders Alexander, Murray Seán M, Sourjik Victor
Max Planck Institute for Terrestrial Microbiology , 35043 Marburg , Germany.
LOEWE Center for Synthetic Microbiology (SYNMIKRO) , 35043 Marburg , Germany.
ACS Synth Biol. 2018 Nov 16;7(11):2618-2626. doi: 10.1021/acssynbio.8b00279. Epub 2018 Oct 24.
Gene expression noise arises from stochastic variation in the synthesis and degradation of mRNA and protein molecules and creates differences in protein numbers across populations of genetically identical cells. Such variability can lead to imprecision and reduced performance of both native and synthetic networks. In principle, gene expression noise can be controlled through the rates of transcription, translation and degradation, such that different combinations of those rates lead to the same protein concentrations but at different noise levels. Here, we present a "noise tuner" which allows orthogonal control over the transcription and the mRNA degradation rates by two different inducer molecules. Combining experiments with theoretical analysis, we show that in this system the noise is largely determined by the transcription rate, whereas the mean expression is determined by both the transcription rate and mRNA stability and can thus be decoupled from the noise. This noise tuner enables 2-fold changes in gene expression noise over a 5-fold range of mean protein levels. We demonstrated the efficacy of the noise tuner in a complex regulatory network by varying gene expression noise in the mating pathway of Saccharomyces cerevisiae, which allowed us to control the output noise and the mutual information transduced through the pathway. The noise tuner thus represents an effective tool of gene expression noise control, both to interrogate noise sensitivity of natural networks and enhance performance of synthetic circuits.
基因表达噪声源于mRNA和蛋白质分子合成与降解过程中的随机变化,并在基因相同的细胞群体中产生蛋白质数量差异。这种变异性会导致天然和合成网络的不精确性以及性能下降。原则上,基因表达噪声可以通过转录、翻译和降解速率来控制,使得这些速率的不同组合会导致相同的蛋白质浓度,但噪声水平不同。在这里,我们展示了一种“噪声调节器”,它允许通过两种不同的诱导分子对转录和mRNA降解速率进行正交控制。结合实验与理论分析,我们表明在这个系统中,噪声在很大程度上由转录速率决定,而平均表达则由转录速率和mRNA稳定性共同决定,因此可以与噪声解耦。这种噪声调节器能够在平均蛋白质水平的5倍范围内使基因表达噪声发生2倍的变化。我们通过改变酿酒酵母交配途径中的基因表达噪声,证明了噪声调节器在复杂调控网络中的有效性,这使我们能够控制输出噪声以及通过该途径转导的互信息。因此,噪声调节器是控制基因表达噪声的有效工具,既可以探究天然网络的噪声敏感性,又可以提高合成电路的性能。