The effect of cell geometry on polarization in budding yeast

Trogdon, Michael; Drawert, Brian; Gómez, Carlos M. Meléndez; Banavar, Samhita P.; Yi, Tongxun; Campàs, Otger; Petzold, Linda R.

doi:10.1371/journal.pcbi.1006241

Cited by 23 publications

(33 citation statements)

References 47 publications

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“…The analytical conditions developed by Rätz and Röger [58] were used as a basis for a comprehensive analysis of the parametric space giving rise to diffusion-driven instability. Lastly, even though three-dimensional simulations of Cdc42-mediated cell polarisation are not novel [17,65], the thorough investigation of the effect of moving in the parametric space on the patterns is.…”

Section: Cell Polarisation Can Be Modelled Through Both Mechanisms Prmentioning

confidence: 99%

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Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability

Borgqvist

Malik

Lundholm

et al. 2020

Preprint

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The GTPase Cdc42 is the master regulator of cell polarisation. During this process the active form of Cdc42 is accumulated at a particular site on the cell membrane called the pole. It is believed that the accumulation of the active Cdc42 resulting in a pole is driven by a combination of activation-inactivation reactions and diffusion. It has been proposed using mathematical modelling that this is the result of diffusion-driven instability, originally proposed by Alan Turing. In this study we develop a 3D bulk-surface model of the dynamics of Cdc42. We show that the model can undergo both classic and nonclassic Turing instability. We thoroughly investigate the parameter space for which this occurs. Using simulations we show that the model can be used to simulate polarisation and to predict a number of relevant quantitative measures, including pole size and time to polarisation. † johborgq@chalmers.se Given the spatial model (6), we now investigate if spatial patterns can emerge through diffusiondriven instability. The underlying idea behind this type of pattern formation was originally formulated by Turing [67], and it entails a switch in stability in the sense of linear stability analysis. More precisely, the phenomena depends on the reaction terms, e.g. f and q, having the capacity to allow for the existence of a stable steady state (u * , v * ) of the homogeneous, i.e. the system neglecting diffusion, ODE-system. Moreover, when diffusion is introduced the same 9 / 21

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Section: Cell Polarisation Can Be Modelled Through Both Mechanisms Prmentioning

confidence: 99%

“…Numerous mathematical models of the dynamics of Cdc42 have been developed [22,61,38,68,18,21,55,14,50,28,66,16,27]. Many of these models can be reduced to a classic activatorinhibitor system focusing on the spatial and temporal dynamics of active and inactive Cdc42.…”

Section: Introductionmentioning

confidence: 99%

Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability

Borgqvist

Malik

Lundholm

et al. 2020

Preprint

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“…The triangular mesh used for the mechanical model, with re-meshing techniques implemented to improve the element regularity, would be used to simulate diffusion-reaction systems of equations describing biochemical signals. Several studies have already studied the connection between biochemical signalling and cell mechanics in mating yeast and tubule formation [39,66,67] . However, understanding of the coupling between the biochemical signaling pathways and cell mechanics for the yeast budding process is still incomplete.…”

Section: Temporal Restoration Of Bud Mechanical Properties Leads To Smentioning

confidence: 99%

Role of combined cell membrane and wall mechanical properties regulated by polarity signals in cell budding

Tsai

Britton

Nematbakhsh

et al. 2020

Preprint

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The budding yeast, Saccharomyces cerevisiae, is a prime biological model to study mechanisms underlying asymmetric growth. Previous studies have shown that, prior to yeast bud emergence, polarization of a conserved small GTPase, Cdc42, must be established. Additionally, hydrolase changes the mechanical properties of the cell wall and plasma membrane with the periplasm between them (cell surface). However, how the surface mechanical properties in the emerging bud are different from the properties of the mother cell and their role in bud formation are not well understood. We hypothesize that the polarized chemical signal alters the local dimensionless ratio of stretching to bending stiffness of the cell surface of the emerging yeast bud. To test this hypothesis, a novel three-dimensional coarse-grained particle-based model has been developed which describes inhomogeneous mechanical properties of the cell surface. Model simulations suggest that regulation of the dimensionless ratio of stretching to bending stiffness of the cell surface is necessary to initiate bud formation . Furthermore, model simulations predict that bud shape depends strongly on the experimentally observed molecular distribution of the polarized signaling molecule Cdc42, while the neck shape of the emerging bud is strongly impacted by the properties of the chitin and septin ring. This 3D model of asymmetric cell growth can also be used for studying viral budding and other vegetative reproduction processes performed via budding.

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“…Intracellular space plays an important role in many biochemical systems operating in the timescales of minutes to hours such as cell signaling [1], division [2], polarization [3], morphogenesis [4] and chemotaxis [5,6]. These systems are regulated by the spatiotemporal dynamics of molecules.…”

Section: Introductionmentioning

confidence: 99%

pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems

Arjunan

Miyauchi

Iwamoto

et al. 2019

Preprint

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Background: Studies using quantitative experimental methods have shown that intracellular spatial distribution of molecules plays a central role in many cellular systems. Spatially resolved computer simulations can integrate quantitative data from these experiments to construct physically accurate models of the systems. Although computationally expensive, microscopic resolution reaction-diffusion simulators, such as Spatiocyte can directly capture intracellular effects comprising diffusion-limited reactions and volume exclusion from crowded molecules by explicitly representing individual diffusing molecules in space. To alleviate the steep computational cost typically associated with the simulation of large or crowded intracellular compartments, we present a parallelized Spatiocyte method called pSpatiocyte. Results: The new high-performance method employs unique parallelization schemes on hexagonal close-packed (HCP) lattice to efficiently exploit the resources of common workstations and large distributed memory parallel computers. We introduce a coordinate system for fast accesses to HCP lattice voxels, a parallelized event scheduler, a parallelized Gillespie's direct-method for unimolecular reactions, and a parallelized event for diffusion and bimolecular reaction processes. We verified the correctness of pSpatiocyte reaction and diffusion processes by comparison to theory. To evaluate the performance of pSpatiocyte, we performed a series of parallelized diffusion runs on the RIKEN K computer. In the case of fine lattice discretization with low voxel occupancy, pSpatiocyte exhibited 74% parallel efficiency and achieved a speedup of 7686 times with 663552 cores compared to the runtime with 64 cores. In the weak scaling performance, pSpatiocyte obtained efficiencies of at least 60% with up to 663552 cores. When executing the Michaelis-Menten benchmark model on an eight-core workstation, pSpatiocyte required 45-and 55-fold shorter runtimes than Smoldyn and the parallel version of ReaDDy, respectively. As a high-performance application example, we study the dual phosphorylation-dephosphorylation cycle of the MAPK system, a typical reaction network motif in cell signaling pathways. Conclusions: pSpatiocyte demonstrates good accuracies, fast runtimes and a significant performance advantage over well-known microscopic particle simulators for large-scale simulations of intracellular reaction-diffusion systems. The source code of pSpatiocyte is available at https://spatiocyte.org.

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The effect of cell geometry on polarization in budding yeast

Cited by 23 publications

References 47 publications

Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability

Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability

Role of combined cell membrane and wall mechanical properties regulated by polarity signals in cell budding

pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems

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