Protein Pattern Formation

Frey, Erwin; Halatek, Jacob; Kretschmer, Simon; Schwille, Petra

doi:10.1007/978-3-030-00630-3_10

Cited by 31 publications

(35 citation statements)

References 96 publications

(152 reference statements)

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“…Intracellular pattern-forming systems are often based on reaction–diffusion networks ( 46 , 47 ). Their underlying nonlinearities render these networks sensitive to even small variations in system parameters, such as reaction rates and the (approximately constant) concentrations.…”

Section: Discussionmentioning

confidence: 99%

MinE conformational switching confers robustness on self-organized Min protein patterns

Denk

Kretschmer

Halatek

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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118

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SignificanceMany fundamental cellular processes are spatially regulated by self-organized protein patterns, which are often based on nucleotide-binding proteins that switch their nucleotide state upon interaction with a second, activating protein. For reliable function, these protein patterns must be robust against parameter changes, although the basis for such robustness is generally elusive. Here we take a combined theoretical and experimental approach to the Escherichia coli Min system, a paradigmatic system for protein self-organization. By mathematical modeling and in vitro reconstitution of mutant proteins, we demonstrate that the robustness of pattern formation is dramatically enhanced by an interlinked functional switching of both proteins, rather than one. Such interlinked functional switching could be a generic means of obtaining robustness in biological pattern-forming systems.

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Section: Discussionmentioning

confidence: 99%

MinE conformational switching confers robustness on self-organized Min protein patterns

Denk

Kretschmer

Halatek

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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118

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“…Note that ‘chemical component’ does not refer to a protein species, but to the conformational state of a protein that determines its interactions with specific (conformations of) other proteins. Clearly, protein interaction networks include many conformational states—not just two [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Self-organization principles of intracellular pattern formation

Halatek¹,

Brauns²,

Frey³

2018

Phil. Trans. R. Soc. B

155

188

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Dynamic patterning of specific proteins is essential for the spatio-temporal regulation of many important intracellular processes in prokaryotes, eukaryotes and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article, we review quantitative models for intracellular Min protein patterns in Escherichia coli, Cdc42 polarization in Saccharomyces cerevisiae and the bipolar PAR protein patterns found in Caenorhabditis elegans. By analysing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as ‘activators’, ‘inhibitors’ or ‘substrate depletion’. Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction–diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.This article is part of the theme issue ‘Self-organization in cell biology’.

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“…Such systems either use natural chemotaxis mechanisms to initiate spatial pattern formation of the bacterial density itself Tyson et al (1999), or instead use synthetic bacteria re-engineered to express additional quorum-sensing pathways that spatially coordinate patterns in gene expression (Basu et al 2005;Tabor et al 2009;Grant et al 2016). Other examples are synthetically reconstituted protein interaction systems with bulk-membrane coupling such as the Min system (Loose et al 2008;Kretschmer and Schwille 2016;Frey et al 2018), where molecular interactions (Denk et al 2018;Glock et al 2019), or in vitro system geometries (Wu et al 2016;Brauns et al 2020;, are modified to stimulate changes in the observed protein patterns. Examples of particular contemporary interest include the use of bacterial colonies as exemplars of synthetic multicellular communication and self-organization (Balagaddé et al 2008;Dalchau et al 2012;Payne et al 2013;Grant et al 2016;Karig et al 2018), for example using modified E. coli with engineered quorum-sensing signalling on the surface of an agar plate (Grant et al 2016;Payne et al 2013;Cao et al 2016Cao et al , 2017.…”

Section: Introductionmentioning

confidence: 99%

“…A second class of model considers bulk-surface coupling, where one component is confined to the boundary of the main bulk domain, and reactants flow between the two regions, such as in the case of proteins diffusing in the cytoplasm and binding on the cell membrane (Rätz and Röger 2014;Madzvamuse et al 2015;Spill et al 2016;Cusseddu et al 2018;Paquin-Lefebvre et al 2018;Frey et al 2018). There is substantial recent interest in such models, from very theoretical results on existence and fast reaction-limiting behavior (Rätz 2015;Anguige and Röger 2017;Hausberg and Röger 2018), to spike dynamics (Gomez et al 2018) and a myriad of applications to understanding cell polarity (Thalmeier et al 2016;Kretschmer and Schwille 2016;Geßele et al 2020).…”

Section: Introductionmentioning

confidence: 99%

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Turing Patterning in Stratified Domains

et al. 2020

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Reaction–diffusion processes across layered media arise in several scientific domains such as pattern-forming E. coli on agar substrates, epidermal–mesenchymal coupling in development, and symmetry-breaking in cell polarization. We develop a modeling framework for bilayer reaction–diffusion systems and relate it to a range of existing models. We derive conditions for diffusion-driven instability of a spatially homogeneous equilibrium analogous to the classical conditions for a Turing instability in the simplest nontrivial setting where one domain has a standard reaction–diffusion system, and the other permits only diffusion. Due to the transverse coupling between these two regions, standard techniques for computing eigenfunctions of the Laplacian cannot be applied, and so we propose an alternative method to compute the dispersion relation directly. We compare instability conditions with full numerical simulations to demonstrate impacts of the geometry and coupling parameters on patterning, and explore various experimentally relevant asymptotic regimes. In the regime where the first domain is suitably thin, we recover a simple modulation of the standard Turing conditions, and find that often the broad impact of the diffusion-only domain is to reduce the ability of the system to form patterns. We also demonstrate complex impacts of this coupling on pattern formation. For instance, we exhibit non-monotonicity of pattern-forming instabilities with respect to geometric and coupling parameters, and highlight an instability from a nontrivial interaction between kinetics in one domain and diffusion in the other. These results are valuable for informing design choices in applications such as synthetic engineering of Turing patterns, but also for understanding the role of stratified media in modulating pattern-forming processes in developmental biology and beyond.

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Protein Pattern Formation

Cited by 31 publications

References 96 publications

MinE conformational switching confers robustness on self-organized Min protein patterns

MinE conformational switching confers robustness on self-organized Min protein patterns

Self-organization principles of intracellular pattern formation

Turing Patterning in Stratified Domains

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