scholarly journals Mechanistic mathematical model of polarity in yeast

2012 ◽  
Vol 23 (10) ◽  
pp. 1998-2013 ◽  
Author(s):  
Natasha S. Savage ◽  
Anita T. Layton ◽  
Daniel J. Lew
Keyword(s):  
Cell Polarity ◽  
Positive Feedback ◽  
Reaction Diffusion ◽  
Feedback Loops ◽  
The Other ◽  
Fluorescence Recovery ◽  
Modeling Framework ◽  
Combined Model ◽  
Feedback Mechanisms ◽  
Vesicle Traffic

The establishment of cell polarity involves positive-feedback mechanisms that concentrate polarity regulators, including the conserved GTPase Cdc42p, at the “front” of the polarized cell. Previous studies in yeast suggested the presence of two parallel positive-feedback loops, one operating as a diffusion-based system, and the other involving actin-directed trafficking of Cdc42p on vesicles. F-actin (and hence directed vesicle traffic) speeds fluorescence recovery of Cdc42p after photobleaching, suggesting that vesicle traffic of Cdc42p contributes to polarization. We present a mathematical modeling framework that combines previously developed mechanistic reaction-diffusion and vesicle-trafficking models. Surprisingly, the combined model recapitulated the observed effect of vesicle traffic on Cdc42p dynamics even when the vesicles did not carry significant amounts of Cdc42p. Vesicle traffic reduced the concentration of Cdc42p at the front, so that fluorescence recovery mediated by Cdc42p flux from the cytoplasm took less time to replenish the bleached pool. Simulations in which Cdc42p was concentrated into vesicles or depleted from vesicles yielded almost identical predictions, because Cdc42p flux from the cytoplasm was dominant. These findings indicate that vesicle-mediated delivery of Cdc42p is not required to explain the observed Cdc42p dynamics, and raise the question of whether such Cdc42p traffic actually contributes to polarity establishment.

scholarly journals Establishment of a robust single axis of cell polarity by coupling multiple positive feedback loops

2013 ◽  
Vol 4 (1) ◽  
Author(s):  
Tina Freisinger ◽  
Ben Klünder ◽  
Jared Johnson ◽  
Nikola Müller ◽  
Garwin Pichler ◽  
...  
Keyword(s):  
Cell Polarity ◽  
Positive Feedback ◽  
Feedback Loops

scholarly journals Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology based approach

2019 ◽  
Author(s):  
Kishore Hari ◽  
Burhanuddin Sabuwala ◽  
Balaram Vishnu Subramani ◽  
Caterina La Porta ◽  
Stefano Zapperi ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Cancer Cells ◽  
Network Topology ◽  
Positive Feedback ◽  
Regulatory Networks ◽  
Therapy Resistance ◽  
Feedback Loops ◽  
Biochemical Networks ◽  
Modeling Framework ◽  
Wide Range

Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis switch dynamically between different phenotypes, enabling them to adapt to harsh challenges such as overcoming anoikis and evading immune response. This ability, known as phenotypic plasticity, is crucial for the survival of cancer cells during metastasis, as well as acquiring therapy resistance. Various biochemical networks have been identified to contribute to phenotypic plasticity, but how plasticity emerges from the dynamics of these networks remains elusive. Here, we investigated the dynamics of various regulatory networks implicated in Epithelial-Mesenchymal Plasticity (EMP) - an important arm of phenotypic plasticity - through two different mathematical modeling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modeling framework (RACIPE). Results from either framework in terms of phenotypic distributions obtained from a given EMP network are qualitatively similar and suggest that these networks are multi-stable and can give rise to phenotypic plasticity. Neither method requires specific kinetic parameters, thus our results emphasize that EMP can emerge through these networks over a wide range of parameter sets, elucidating the importance of network topology in enabling phenotypic plasticity. Furthermore, we show that the ability of exhibit phenotypic plasticity positively correlates with the number of positive feedback loops. These results pave a way towards an unorthodox network topology-based approach to identify crucial links in a given EMP network that can reduce phenotypic plasticity and possibly inhibit metastasis - by reducing the number of positive feedback loops .

scholarly journals Many roads to symmetry breaking: molecular mechanisms and theoretical models of yeast cell polarity

2017 ◽  
Vol 28 (3) ◽  
pp. 370-380 ◽  
Author(s):  
Andrew B. Goryachev ◽  
Marcin Leda
Keyword(s):  
Symmetry Breaking ◽  
G Protein ◽  
Cell Polarity ◽  
Positive Feedback ◽  
Molecular Mechanisms ◽  
Theoretical Models ◽  
Feedback Loops ◽  
Recent Developments ◽  
Cellular Polarization ◽  
Generic System

Mathematical modeling has been instrumental in identifying common principles of cell polarity across diverse systems. These principles include positive feedback loops that are required to destabilize a spatially uniform state of the cell. The conserved small G-protein Cdc42 is a master regulator of eukaryotic cellular polarization. Here we discuss recent developments in studies of Cdc42 polarization in budding and fission yeasts and demonstrate that models describing symmetry-breaking polarization can be classified into six minimal classes based on the structure of positive feedback loops that activate and localize Cdc42. Owing to their generic system-independent nature, these model classes are also likely to be relevant for the G-protein–based symmetry-breaking systems of higher eukaryotes. We review experimental evidence pro et contra different theoretically plausible models and conclude that several parallel and non–mutually exclusive mechanisms are likely involved in cellular polarization of yeasts. This potential redundancy needs to be taken into consideration when interpreting the results of recent cell-rewiring studies.

scholarly journals Turing Patterning in Stratified Domains

2020 ◽  
Vol 82 (10) ◽  
Author(s):  
Andrew L. Krause ◽  
Václav Klika ◽  
Jacob Halatek ◽  
Paul K. Grant ◽  
Thomas E. Woolley ◽  
...  
Keyword(s):  
Diffusion Processes ◽  
Reaction Diffusion ◽  
Turing Instability ◽  
Cell Polarization ◽  
The Other ◽  
Modeling Framework ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Coupling Parameters ◽  
Pattern Forming

Abstract 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.

scholarly journals Polarity establishment requires localized activation of Cdc42

2015 ◽  
Vol 211 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Benjamin Woods ◽  
Chun-Chen Kuo ◽  
Chi-Fang Wu ◽  
Trevin R. Zyla ◽  
Daniel J. Lew
Keyword(s):  
Cell Polarity ◽  
Positive Feedback ◽  
Cortical Region ◽  
Local Concentration ◽  
Yeast Saccharomyces Cerevisiae ◽  
Feedback Mechanisms ◽  
Localized Delivery ◽  
Rho Family ◽  
Polarity Establishment ◽  
Guanosine Triphosphatase

Establishment of cell polarity in animal and fungal cells involves localization of the conserved Rho-family guanosine triphosphatase, Cdc42, to the cortical region destined to become the “front” of the cell. The high local concentration of active Cdc42 promotes cytoskeletal polarization through various effectors. Cdc42 accumulation at the front is thought to involve positive feedback, and studies in the budding yeast Saccharomyces cerevisiae have suggested distinct positive feedback mechanisms. One class of mechanisms involves localized activation of Cdc42 at the front, whereas another class involves localized delivery of Cdc42 to the front. Here we show that Cdc42 activation must be localized for successful polarity establishment, supporting local activation rather than local delivery as the dominant mechanism in this system.

scholarly journals FGF2 Translationally Induced by Hypoxia Is Involved in Negative and Positive Feedback Loops with HIF-1α

PLoS ONE ◽  
2008 ◽  
Vol 3 (8) ◽  
pp. e3078 ◽  
Author(s):  
Caroline Conte ◽  
Elodie Riant ◽  
Céline Toutain ◽  
Françoise Pujol ◽  
Jean-François Arnal ◽  
...  
Keyword(s):  
Positive Feedback ◽  
Feedback Loops

scholarly journals Celsr1 and CAMSAP3 differently regulate intercellular and intracellular cilia orientation in oviduct multiciliated cells

2020 ◽  
Author(s):  
Fumiko Matsukawa Usami ◽  
Masaki Arata ◽  
Dongbo Shi ◽  
Sanae Oka ◽  
Yoko Higuchi ◽  
...  
Keyword(s):  
Cell Polarity ◽  
Planar Cell Polarity ◽  
Molecular Mechanisms ◽  
The Other ◽  
Basal Bodies ◽  
Generating Functional ◽  
Tissue Polarity ◽  
Other Hand ◽  
Multiciliated Cells ◽  
Polarity Regulation

SummaryThe molecular mechanisms by which cilia orientation is coordinated within and between multiciliated cells (MCCs) is not fully understood. By observing the orientation of basal bodies (BB) in MCCs of mouse oviducts, here, we show that Celsr1, a planar cell polarity (PCP) factor involved in tissue polarity regulation, is dispensable for determining BB orientation in individual cells, whereas CAMSAP3, a microtubule minus-end regulator, is critical for this process but not for PCP. MCCs exhibit a characteristic BB orientation and microtubule gradient along the tissue axis, and these intracellular polarities were maintained in the cells lacking Celsr1, although the intercellular coordination of the polarities was partly disrupted. On the other hand, CAMSAP3 regulated the assembly of microtubules interconnecting BBs by localizing at the BBs, and its mutation led to disruption of intracellular coordination of BB orientation, but not affecting PCP factor localization. Thus, both Celsr1 and CAMSAP3 are responsible for BB orientation but in distinct ways; and therefore, their cooperation should be critical for generating functional multiciliated tissues.

A BGK MODEL FOR CHEMICAL PROCESSES: THE REACTION-DIFFUSION APPROXIMATION

1994 ◽  
Vol 04 (01) ◽  
pp. 35-47 ◽  
Author(s):  
RENATO SPIGLER ◽  
DAMIÁN H. ZANETTE
Keyword(s):  
Kinetic Model ◽  
Diffusion Approximation ◽  
Reaction Diffusion ◽  
Chemical Processes ◽  
Reaction Diffusion Equations ◽  
The Other ◽  
Diffusion Equations ◽  
Bgk Model ◽  
Chemical Substances ◽  
Chemical Effects

A BGK-type kinetic model is derived for describing the interaction of chemical substances. The ensuing equation is then solved asymptotically on certain space-time scales on which an appreciable interplay between kinetic and chemical effects, or the prevailing of one on the other, can be observed. The description of the interaction at the macroscopic level consists of a hierarchy of reaction-diffusion equations satisfied by the densities. Comparison is made with similar results previously obtained from certain phenomenological models, and illustrative examples are given.

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