DNA- polymer结构协调了E.大肠杆菌染色体在复制过程中生长缓慢
DNA-polymer architecture orchestrates the segregation and spatio-temporal organization of E. coli chromosomes during replication in slow growth
摘要：
对大肠杆菌染色体分离的机制和驱动力进行了研究。大肠杆菌是其生命周期中了解最少的事件之一。利用限制在圆柱体中的聚合物环之间的熵排斥原理，我们使用蒙特卡罗模拟表明，通过采用一定的DNA-聚合物体系结构，随着复制的进展，分离动力学自发地增强。其次，所选择的聚合物拓扑结构确保其沿细胞轴的自组织，同时分离正在进行中，使得各种染色体基因座在空间上定位。位点位置的时间演化定量地匹配相应的实验报告的结果，包括观察的凝聚时间和TER过渡。此外，使用我们的珠弹簧模型生成的接触图再现了实验Hi-C图的四个宏域。最后，所提出的机制再现了所观察到的普遍动态的姐妹位点分离分离过程中。已经假设和预期SMC蛋白质，例如MukBEF，在细菌-DNA环聚合物之间贡献超过熵排斥，以帮助子DNA在大肠杆菌细胞周期中的分离。我们建议，在沿轮廓的关键位置处的交联（可能由SMC蛋白诱导）足以在合理的时间尺度内提供足够的分离力。蒙特卡罗扩散动力学时间尺度和实时单位之间的映射有助于我们使用实验相关的数字进行建模。
英文摘要：
The mechanism and driving forces of chromosome segregation in the bacterial cell cycle of E. coli is one of the least understood events in its life cycle. Using principles of entropic repulsion between polymer loops confined in a cylinder, we use Monte carlo simulations to show that the segregation dynamics is spontaneously enhanced by the adoption of a certain DNA-polymer architecture as replication progresses. Secondly, the chosen polymer-topology ensures its self-organization along the cell axis while segregation is in progress, such that various chromosomal loci get spatially localized. The time evolution of loci positions quantitatively match the corresponding experimentally reported results, including observation of the cohesion time and the ter-transition. Additionally, the contact map generated using our bead-spring model reproduces the four macro-domains of the experimental Hi-C maps. Lastly, the proposed mechanism reproduces the observed universal dynamics as the sister loci separate during segregation. It was already hypothesized and expected that SMC proteins, e.g. MukBEF contribute over and above entropic repulsion between bacterial-DNA ring-polymers to aid the segregation of daughter DNAs in the E.coli cell cycle. We propose that cross-links (plausibly induced by SMC proteins) at crucial positions along the contour is enough to provide sufficient forces for segregation within reasonable time scales. A mapping between Monte Carlo diffusive dynamics time scales and real time units helps us use experimentally relevant numbers for our modeling.
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