A hybrid experimental-modelling study of SOS response-induced filamentation and its effect on bacterial colony growth

细菌对抗生素的耐药性是一个全球性的问题，已经导致许多人死于细菌感染。细菌可以通过DNA损伤诱导的SOS反应介导的突变来进化抗药性，这也导致DNA修复和细胞分裂抑制。虽然已知破坏DNA的抗生素和紫外线辐射可以激活SOS反应，但其他主要不破坏DNA的杀菌抗生素是否能够诱导SOS反应仍未确定。SOS诱导的细胞分裂抑制也会导致细胞形态的改变，因为细胞变得丝状。在一些野生型细胞中，SOS反应是自发诱导的，导致细胞之间的突变和形态的差异。在这个项目中，我们提出了一种混合的实验和建模方法。利用单分子示踪法，我们将通过观察SOS调节因子LexA的浓度动态及其辅酶RecA的表达来检测SOS对不同类型抗生素的反应。然后，我们将使用对Sula表达的测量，该表达受LexA调控，并编码为细胞分裂抑制因子Sula，以产生一个将LexA动态和细胞丝化表型联系起来的数学模型。最后，我们将使用微流体测量大肠杆菌在机械力作用下的弯曲，以及在进行细丝形成时的生长速度，并利用这一点来开发一个基于个体的细菌菌落生长计算模型，该模型实现了细丝形成。然后，我们将使用这个模型，结合标准的微生物学实验，来了解SOS异质性在种群规模上的影响。

Bacterial resistance to antibiotics is a global problem which is already implicated in many deaths by bacterial infection. Bacteria can evolve resistance through mutations mediated by the DNA damage-induced SOS response, which also results in DNA repair and cell division inhibition. Whilst DNA-damaging antibiotics and UV radiation are known to activate the SOS response, it remains unresolved whether other, non-primarily DNA damaging bactericidal antibiotics are capable of inducing the SOS response. SOS-induced cell division inhibition also leads to changes in cell morphology as the cells become filamentous. In some wild type cells, the SOS response is spontaneously induced, leading to variations in mutations and morphology between cells. In this project, we propose a hybrid experimental and modelling approach. Using single molecule tracking, we will examine SOS responses to different kinds of antibiotics by looking at concentration dynamics of the SOS regulator LexA and expression of its coprotease RecA. We will then use measurements of expression of sulA, which is regulated by LexA and codes for the cell division inhibitor SulA, to produce a mathematical model linking LexA dynamics and the cell filamentation phenotype. Finally, we will take measurements of E. coli bending under mechanical forces using microfluidics, and growth rates when undergoing filamentation, and use this to develop an individual-based computational model of bacterial colony growth that implements filamentation. We will then use this model, combined with standard microbiology experiments, to understand the effect of SOS heterogeneity at the population scale.