Research Group Leader
Max Planck Institute for Terrestrial Microbiology
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The subcellular positioning of proteins is crucial for many cellular processes. This is often due to passive recruitment mechanisms. On the other hand, active mechanisms have been well-studied in the context of plasmid segregation in bacteria. Active positioning mechanisms are also believed to be responsible for the positioning of the future division site and several cytoplasmic protein clusters. Unlike plasmids however, proteins can be dynamic with rapid turnover. How such dynamic proteins can be organised and positioned was the focus of this work.
We investigated these questions using mathematical modelling and fluorescence microscopy taking the SMC (Structural Maintenance of Chromosomes) complex of Escherichia coli (MukBEF) as a model system. SMC complexes are ubiquitous not just in bacteria but also eukaryotes and are essential for proper chromosome segregation and condensation. It has been observed in several bacteria that fluorescent SMC fusions form a discrete number of fluorescent foci per cell. In both E. coli and Bacillus subtilis, SMC has usually either a single focus localized near mid-cell or two foci localized at approximately quarter positions. However, how these dynamic clusters are positioned has, hitherto, remained unclear. It was similarly not known what causes the length dependent transition from one to two foci.
We developed a mathematical model for the organisation of these dynamic protein clusters in which the properties of the proteins themselves are sufficient to result in self-organisation and regular positioning (Murray & Sourjik, 2017). Mathematically, the model is based on Turing pattern formation. This mechanism is widely applied to multi-cellular developmental biology but very seldom to the intracellular environment of a single cell. This is largely due to the fact that the phase of the pattern produced is not fixed i.e. different initial perturbation can give rise to patterns that are off-set from one another. We overcome this problem by the addition of a flux-balance mechanism that, in combination with stochastic effects, fixes the phase of the Turing pattern so that not only does a pattern form spontaneously due to the dynamics of the system but it is also correctly and dynamically positioned. In essence, the proteins can sense the geometry of the nucleoid and position themselves appropriately. Furthermore, the model predicts that clusters can split naturally as a result of growth.
As there are many examples of phase-fixed protein patterns especially in multi-cellular systems, the principles uncovered are likely to be applicable elsewhere. This is particularly true in developmental systems in which there is no evidence that boundary cells can physically sense their position but yet the system exhibits pattern with only internal peaks.
The swarming rod-shaped bacterium, Myxococcus xanthus, is a model organism for multicellular development. Its direction of movement is determined by the cell’s polarity, which is specified by the localisation of two proteins, a G-protein and its cognate GTPase-activating protein, one at each pole. However, cells are capable of very rapidly switching polarity and hence their direction of movement, with the two polar complexes rapidly switching poles. This is known to be controlled by the Frz chemosensory-like system.
In a collaboration with the lab of Tâm Mignot (CNRS, Marseille), we used mathematical modelling, genetics, and imaging to determine the mechanism behind this control (Guzzo et al. , 2018). While an initial mathematical model was insufficient to fully explain the experimental data, it lead to the discovery of the missing primary Frz output, FrzX, and a revised model of the system as a gated relaxation oscillator. The model is non-trivially consistent with all the available data and made successful predictions. Interestingly, this type of regulatory topology has, to our knowledge, not previously been found in biology. As this system involves a Ras-like GTPase, a family highly conserved throughout all eukaryotes, we expect our results to have application beyond bacteria.