Self-organisation as the basis of bacterial chromosomal segregation

• Applicant: Dr. Sean Murray
• Subject Area: Biophysics ; Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics ; Metabolism, Biochemistry and Genetics of Microorganisms
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 439535737

Chromosome replication and segregation are critical processes for all cellular life. Replication of bacterial chromosomes initiates at a unique site called the origin, or ori, and proceeds bi-directionally down each chromosomal arm. In Escherichia coli and other bacteria, the ori is specifically positioned within the cell. In new-born cells, it is found at the cell middle, where replication is initiated. Duplicated ori are subsequently partitioned to opposite quarter positions where they remain for the remainder of the cell cycle. While these dynamics been very well studied, the underlying mechanisms are unknown.We have recently provided a novel explanation based on self-organisation of SMC (Structural Maintenance of Chromosomes) complexes, a ubiquitous family of proteins involved in chromosome organisation. MukBEF, the E. coli SMC forms dynamic clusters inside cells following the pattern of ori, described above. We have proposed that MukBEF is a self-organising and self-positioning system and presented a mathematical model based on stochastic pattern formation. Building on this model, we argue that self-organising MukBEF segregates and positions ori. We have shown that a specific interaction between MukBEF and ori leads to bidirectional attraction, resulting in accurate positioning and partitioning of ori. The latter is an emergent property of the system, arising from the fact that ori do not simply move up the MukBEF gradient but rather interact with it in a non-trivial way. The model is supported by both new and published experimental data.In this project, we aim to unravel the biological and physical mechanism organising the E. coli chromosome. Our first goal is a rigorous quantitative comparison of our spatial stochastic model with time-lapse fluorescence microscopy data. For this, we will develop an image analysis pipeline and a distributed computing and Bayesian inference framework. This will give us the ability to test biophysical hypotheses against the experimental data. We will use this approach to explore the precise nature of the interaction between MukBEF and ori. Lastly, we will examine the positioning and interaction with MukBEF of another important genomic region, the replication terminus, which also plays a role in determining the future division site.By developing the first quantitative model of chromosome segregation in E. coli, this work will provide fundamental biological and physical insights into one of the most fundamental aspects of the bacterial cell cycle. Furthermore, the Bayesian inference approach for comparing imaging data to a spatio-temporal stochastic model will be of interest for the study of other cell biological processes, while the model itself will appeal more broadly to the pattern formation community.

• DFG Programme: Research Grants