Center Finding in E. coli and the Role of Mathematical Modeling: Past, Present and Future

Murray, Séan; Howard, Martin

doi:10.1016/j.jmb.2019.01.017

Cited by 8 publications

(7 citation statements)

References 67 publications

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“…Thus, if the MukBEF focus is off-centre (in the case of a single focus), it experiences a differential in the incoming fluxes from either side, resulting in movement toward the equilibrium position (the centre). This flux-balance mechanism was first described in the context of plasmid positioning (Ietswaart et al, 2014; Murray and Howard, 2019; Sugawara and Kaneko, 2011) but is valid quite generally. Note that in this model, the chromosome is not modelled explicitly.…”

Section: Resultsmentioning

confidence: 99%

Self-organised segregation of bacterial chromosomal origins

Hofmann

Mäkelä

Sherratt

et al. 2019

eLife

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The chromosomal replication origin region (ori) of characterised bacteria is dynamically positioned throughout the cell cycle. In slowly growing Escherichia coli, ori is maintained at mid-cell from birth until its replication, after which newly replicated sister oris move to opposite quarter positions. Here, we provide an explanation for ori positioning based on the self-organisation of the Structural Maintenance of Chromosomes complex, MukBEF, which forms dynamically positioned clusters on the chromosome. We propose that a non-trivial feedback between the self-organising gradient of MukBEF complexes and the oris leads to accurate ori positioning. We find excellent agreement with quantitative experimental measurements and confirm key predictions. Specifically, we show that oris exhibit biased motion towards MukBEF clusters, rather than mid-cell. Our findings suggest that MukBEF and oris act together as a self-organising system in chromosome organisation-segregation and introduces protein self-organisation as an important consideration for future studies of chromosome dynamics.

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Section: Resultsmentioning

confidence: 99%

Self-organised segregation of bacterial chromosomal origins

Hofmann

Mäkelä

Sherratt

et al. 2019

eLife

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“…MinE, in the form of a MinE ring, associates to the membrane bound MinCD, causing its detachment from the membrane and giving rise to a spatiotemporal dynamic pole-to-pole oscillation of MinCDE, which is highest at the cell poles and lowest at the midcell. This gradient of the FtsZ inhibitor MinC ultimately restricts Z-ring formation at the correct midcell location (reviewed in [185]). B. subtilis does not contain a MinE homolog and instead possesses a coiled-coil protein called DivIVA, which localizes to areas of negative curvature-the cell poles or the division site of constricting cells-and recruits MinCD through a linker protein called MinJ.…”

Section: Z-ring-all In One Placementioning

confidence: 99%

Structural Determinants and Their Role in Cyanobacterial Morphogenesis

Springstein

Nürnberg

Weiss

et al. 2020

Life

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Cells have to erect and sustain an organized and dynamically adaptable structure for an efficient mode of operation that allows drastic morphological changes during cell growth and cell division. These manifold tasks are complied by the so-called cytoskeleton and its associated proteins. In bacteria, FtsZ and MreB, the bacterial homologs to tubulin and actin, respectively, as well as coiled-coil-rich proteins of intermediate filament (IF)-like function to fulfil these tasks. Despite generally being characterized as Gram-negative, cyanobacteria have a remarkably thick peptidoglycan layer and possess Gram-positive-specific cell division proteins such as SepF and DivIVA-like proteins, besides Gram-negative and cyanobacterial-specific cell division proteins like MinE, SepI, ZipN (Ftn2) and ZipS (Ftn6). The diversity of cellular morphologies and cell growth strategies in cyanobacteria could therefore be the result of additional unidentified structural determinants such as cytoskeletal proteins. In this article, we review the current advances in the understanding of the cyanobacterial cell shape, cell division and cell growth.

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“…Generalization to account for the effect of membrane diffusion is straightforward by changing variables from c to the 'mass-redistribution potential' η := c + (D m /D c )m [39]. Equation (7), has a simple geometric interpretation as shown in Fig. 3b,c.…”

Section: B Limit Of Slow Mass Exchangementioning

confidence: 99%

“…The term in the brackets in Eq. (7) expresses the difference between the nullcline (solid, black line) and its mirror image (dashed gray line) reflected at the point n. Depending on the nullcline slope at n, the resulting dynamics ∂ t ∆n, indicated by the blue arrows, is qualitatively different. For a positive slope, ∂ n c * (n)| n > 0, following a small perturbation from the "homogeneous" state ∆n = 0 the system returns to the ∆n = 0; see Fig.…”

Section: B Limit Of Slow Mass Exchangementioning

confidence: 99%

“…The spatial intracellular organization of proteins by reactions (protein-protein interactions) and diffusion has received growing attention in recent years; for recent reviews see Refs. [1][2][3][4][5][6][7][8]. Gaining intuition and theoretical insight into the spatiotemporal protein dynamics remains challenging owing to the complexity arising from the spatial coupling and nonlinear reaction terms.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Diffusive coupling of two well-mixed compartments elucidates elementary principles of protein-based pattern formation

Brauns,

Halatek,

Frey

2020

Preprint

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Spatial organization of proteins in cells is important for many biological functions. In general, the nonlinear, spatially coupled models for protein-pattern formation are only accessible to numerical simulations, which has limited insight into the general underlying principles. To overcome this limitation, we adopt the setting of two diffusively coupled, well-mixed compartments that represents the elementary feature of any pattern-an interface. For intracellular systems, the total numbers of proteins are conserved on the relevant timescale of pattern formation. Thus, the essential dynamics is the redistribution of the globally conserved mass densities between the two compartments. We present a phase-portrait analysis in the phase-space of the redistributed masses that provides insights on the physical mechanisms underlying pattern formation. We demonstrate this approach for several paradigmatic model systems. In particular, we show that the pole-to-pole Min oscillations in Escherichia coli are relaxation oscillations of the MinD polarity orientation. This reveals a close relation between cell polarity oscillatory patterns in cells. Critically, our findings suggest that the design principles of intracellular pattern formation are found in characteristic features in these phase portraits (nullclines and fixed points) rather than the topology of the protein-interaction networks.

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Center Finding in E. coli and the Role of Mathematical Modeling: Past, Present and Future

Cited by 8 publications

References 67 publications

Self-organised segregation of bacterial chromosomal origins

Self-organised segregation of bacterial chromosomal origins

Structural Determinants and Their Role in Cyanobacterial Morphogenesis

Diffusive coupling of two well-mixed compartments elucidates elementary principles of protein-based pattern formation

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