Garcia-Bernardo Javier, Dunlop Mary J
Department of Computer Science, University of Vermont, Burlington, Vermont.
School of Engineering, University of Vermont, Burlington, Vermont.
Biophys J. 2015 Jan 6;108(1):184-93. doi: 10.1016/j.bpj.2014.11.048.
To counter future uncertainty, cells can stochastically express stress response mechanisms to diversify their population and hedge against stress. This approach allows a small subset of the population to survive without the prohibitive cost of constantly expressing resistance machinery at the population level. However, expression of multiple genes in concert is often needed to ensure survival, requiring coordination of infrequent events across many downstream targets. This raises the question of how cells orchestrate the timing of multiple rare events without adding cost. To investigate this, we used a stochastic model to study regulation of downstream target genes by a transcription factor. We compared several upstream regulator profiles, including constant expression, pulsatile dynamics, and noisy expression. We found that pulsatile dynamics and noise are sufficient to coordinate expression of multiple downstream genes. Notably, this is true even when fluctuations in the upstream regulator are far below the dissociation constants of the regulated genes, as with infrequently activated genes. As an example, we simulated the dynamics of the multiple antibiotic resistance activator (MarA) and 40 diverse downstream genes it regulates, determining that low-level dynamics in MarA are sufficient to coordinate expression of resistance mechanisms. We also demonstrated that noise can play a similar coordinating role. Importantly, we found that these benefits are present without a corresponding increase in the population-level cost. Therefore, our model suggests that low-level dynamics or noise in a transcription factor can coordinate expression of multiple stress response mechanisms by engaging them simultaneously without adding to the overall cost.
为应对未来的不确定性,细胞可以随机表达应激反应机制,以使群体多样化并抵御应激。这种方法允许群体中的一小部分细胞存活,而无需在群体水平上持续表达抗性机制所带来的高昂成本。然而,通常需要多个基因协同表达才能确保存活,这就需要协调许多下游靶点上的罕见事件。这就引出了一个问题:细胞如何在不增加成本的情况下协调多个罕见事件的时间安排。为了研究这一问题,我们使用了一个随机模型来研究转录因子对下游靶基因的调控。我们比较了几种上游调节因子的模式,包括恒定表达、脉动动力学和噪声表达。我们发现脉动动力学和噪声足以协调多个下游基因的表达。值得注意的是,即使上游调节因子的波动远低于受调控基因的解离常数,对于不常被激活的基因也是如此,情况依然如此。例如,我们模拟了多重抗生素抗性激活因子(MarA)及其调控的40个不同下游基因的动力学,确定MarA的低水平动力学足以协调抗性机制的表达。我们还证明了噪声可以起到类似的协调作用。重要的是,我们发现这些益处的存在并没有伴随着群体水平成本的相应增加。因此,我们的模型表明,转录因子中的低水平动力学或噪声可以通过同时激活多个应激反应机制来协调它们的表达,而不会增加总体成本。