Eukaryotes and prokaryotes exploit the ability of genetically identical cells to exhibit different phenotypes in order to enhance their survival. However, the mechanisms by which cells transition from one phenotype to another remain unclear. Canonical models of this dynamic posit that molecular fluctuations provide the noise that drives the cell out of one stable state and into another. Stochastic processes generated by canonical models should, therefore, be good descriptors of phenotype dynamics and between-state transitions should become more likely at greater noise amplitude, for instance at higher extracellular temperatures. To test these predictions, we observed temporal expression dynamics of the promoter of a flagellum gene, fliC, in a microfluidic device using Salmonella enterica serovar Typhimurium and green fluorescent protein (GFP). Our observations show that while cells can exhibit multistable phenotypes, including stable fliC-OFF and fliC-ON states characterised by low and high GFP levels, respectively, between-state transitions can exhibit oscillatory dynamics whose return statistics do not conform to canonical theories. For example, here the fliC-ON state was more frequent following a temperature increase. To better understand our data we developed different dynamical frameworks to predict fliC expression data. We conclude that a stochastic dynamical system tailored to the genetic network of fliC is better suited to our data than prior theories where dynamical features, like oscillations and pulsing, are driven by inevitable delays in the post-translational regulation of fliC. Thus, while transcriptional noise promotes phenotypic heterogeneity, as we show here, regular features like oscillatory heterogeneity can result from delays that fundamental molecular processes impose upon a cell’s gene regulatory architecture.

中文翻译：

---

延迟遗传振荡产生的动态表型异质性

真核生物和原核生物利用遗传上相同的细胞表现出不同表型的能力来增强其存活率。但是，细胞从一种表型转变为另一种表型的机制仍不清楚。这种动力学的典范模型认为，分子波动会提供将细胞从一种稳定状态转移到另一种稳定状态的噪声。因此，由典范模型产生的随机过程应该是表型动力学的良好描述，并且在更大的噪声幅度下，例如在更高的细胞外温度下，状态之间的转变应该更有可能。为了测试这些预测，我们在使用沙门氏菌的微流控设备中观察了鞭毛基因fliC启动子的时间表达动态。鼠伤寒血清和绿色荧光蛋白（GFP）。我们的观察结果表明，虽然细胞可以表现出多稳态表型，包括分别以低和高GFP水平为特征的稳定的fliC- OFF和fliC- ON状态，但是状态间的转换却可以表现出振荡动力学，其返回统计量不符合规范的理论。例如，在温度升高之后，fliC -ON状态更加频繁。为了更好地理解我们的数据，我们开发了不同的动力学框架来预测fliC表达数据。我们得出的结论是，针对fliC的遗传网络量身定制的随机动力学系统比之前的理论更适合我们的数据，在先前的理论中，fliC的翻译后调控不可避免地受到延迟，从而导致诸如振动和脉冲等动力学特征。因此，虽然转录噪声会促进表型异质性，如我们在此处所示，但基本分子过程强加于细胞基因调控架构的延迟可能会导致诸如振荡异质性等常规特征。