Stress responses allow cells to adapt to changes in external conditions by activating specific pathways¹. Here we investigate the dynamics of single cells that were subjected to acute stress that is too strong for a regulated response but not lethal. We show that when the growth of bacteria is arrested by acute transient exposure to strong inhibitors, the statistics of their regrowth dynamics can be predicted by a model for the cellular network that ignores most of the details of the underlying molecular interactions. We observed that the same stress, applied either abruptly or gradually, can lead to totally different recovery dynamics. By measuring the regrowth dynamics after stress exposure on thousands of cells, we show that the model can predict the outcome of antibiotic persistence measurements. Our results may account for the ubiquitous antibiotic persistence phenotype², as well as for the difficulty in attempts to link it to specific genes³. More generally, our approach suggests that two different cellular states can be observed under stress: a regulated state, which prepares cells for fast recovery, and a disrupted cellular state due to acute stress, with slow and heterogeneous recovery dynamics. The disrupted state may be described by general properties of large random networks rather than by specific pathway activation. Better understanding of the disrupted state could shed new light on the survival and evolution of cells under stress.

应激反应允许细胞通过激活特定途径来适应外部条件的变化¹. 在这里，我们研究了受到急性压力的单个细胞的动力学，这种压力对于调节反应来说太强了，但不是致命的。我们表明，当细菌的生长因急性短暂暴露于强抑制剂而停止时，其再生动力学的统计数据可以通过忽略基本分子相互作用的大部分细节的细胞网络模型来预测。我们观察到，突然或逐渐施加相同的压力会导致完全不同的恢复动态。通过测量数千个细胞在压力暴露后的再生动力学，我们表明该模型可以预测抗生素持久性测量的结果。我们的结果可能解释了普遍存在的抗生素持久性表型²，以及试图将其与特定基因联系起来的困难³。更一般地说，我们的方法表明，在压力下可以观察到两种不同的细胞状态：一种为细胞快速恢复做准备的调节状态，另一种是由于急性压力导致的细胞状态中断，恢复动态缓慢且不均匀。破坏状态可以通过大型随机网络的一般特性来描述，而不是通过特定的通路激活来描述。更好地了解被破坏的状态可以为细胞在压力下的生存和进化提供新的线索。