scholarly journals Classical cadherins control nucleus and centrosome position and cell polarity

2009 ◽  
Vol 185 (5) ◽  
pp. 779-786 ◽  
Author(s):  
Isabelle Dupin ◽  
Emeline Camand ◽  
Sandrine Etienne-Manneville
Keyword(s):  
Cell Polarity ◽  
Control Cell ◽  
Cell Types ◽  
Free Cell ◽  
Cell Polarization ◽  
Cell Interactions ◽  
Spatial Cues ◽  
Cell Contacts ◽  
Classical Cadherins ◽  
Cell Cell

Control of cell polarity is crucial during tissue morphogenesis and renewal, and depends on spatial cues provided by the extracellular environment. Using micropatterned substrates to impose reproducible cell–cell interactions, we show that in the absence of other polarizing cues, cell–cell contacts are the main regulator of nucleus and centrosome positioning, and intracellular polarized organization. In a variety of cell types, including astrocytes, epithelial cells, and endothelial cells, calcium-dependent cadherin-mediated cell–cell interactions induce nucleus and centrosome off-centering toward cell–cell contacts, and promote orientation of the nucleus–centrosome axis toward free cell edges. Nucleus and centrosome off-centering is controlled by N-cadherin through the regulation of cell interactions with the extracellular matrix, whereas the orientation of the nucleus–centrosome axis is determined by the geometry of N-cadherin–mediated contacts. Our results demonstrate that in addition to the specific function of E-cadherin in regulating baso-apical epithelial polarity, classical cadherins control cell polarization in otherwise nonpolarized cells.

scholarly journals Collective cell migration requires suppression of actomyosin at cell–cell contacts mediated by DDR1 and the cell polarity regulators Par3 and Par6

2010 ◽  
Vol 13 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Cristina Hidalgo-Carcedo ◽  
Steven Hooper ◽  
Shahid I. Chaudhry ◽  
Peter Williamson ◽  
Kevin Harrington ◽  
...  
Keyword(s):  
Cell Migration ◽  
Cell Polarity ◽  
Collective Cell Migration ◽  
Cell Contacts ◽  
Cell Cell

oko meduzy mutations affect neuronal patterning in the zebrafish retina and reveal cell-cell interactions of the retinal neuroepithelial sheet

Development ◽  
1999 ◽  
Vol 126 (6) ◽  
pp. 1235-1246 ◽  
Author(s):  
J. Malicki ◽  
W. Driever
Keyword(s):  
Critical Role ◽  
Cell Types ◽  
Cell Interactions ◽  
Retinal Cell ◽  
Wild Type ◽  
Vertebrate Retina ◽  
Neuroepithelial Cells ◽  
Patterning Defect ◽  
Cell Cell

Mutations of the oko meduzy (ome) locus cause drastic neuronal patterning defect in the zebrafish retina. The precise, stratified appearance of the wild-type retina is absent in the mutants. Despite the lack of lamination, at least seven retinal cell types differentiate in oko meduzy. The ome phenotype is already expressed in the retinal neuroepithelium affecting morphology of the neuroepithelial cells. Our experiments indicate that previously unknown cell-cell interactions are involved in development of the retinal neuroepithelial sheet. In genetically mosaic animals, cell-cell interactions are sufficient to rescue the phenotype of oko meduzy retinal neuroepithelial cells. These cell-cell interactions may play a critical role in the patterning events that lead to differentiation of distinct neuronal laminae in the vertebrate retina.

scholarly journals Learning the dynamics of cell–cell interactions in confined cell migration

2021 ◽  
Vol 118 (7) ◽  
pp. e2016602118 ◽  
Author(s):  
David B. Brückner ◽  
Nicolas Arlt ◽  
Alexandra Fink ◽  
Pierre Ronceray ◽  
Joachim O. Rädler ◽  
...  
Keyword(s):  
Cancer Metastasis ◽  
Single Cells ◽  
Cell Types ◽  
Theoretical Description ◽  
Cell Interactions ◽  
Cellular Interaction ◽  
Migration Dynamics ◽  
Interaction Behaviors ◽  
Cell Trajectories ◽  
Cell Cell

The migratory dynamics of cells in physiological processes, ranging from wound healing to cancer metastasis, rely on contact-mediated cell–cell interactions. These interactions play a key role in shaping the stochastic trajectories of migrating cells. While data-driven physical formalisms for the stochastic migration dynamics of single cells have been developed, such a framework for the behavioral dynamics of interacting cells still remains elusive. Here, we monitor stochastic cell trajectories in a minimal experimental cell collider: a dumbbell-shaped micropattern on which pairs of cells perform repeated cellular collisions. We observe different characteristic behaviors, including cells reversing, following, and sliding past each other upon collision. Capitalizing on this large experimental dataset of coupled cell trajectories, we infer an interacting stochastic equation of motion that accurately predicts the observed interaction behaviors. Our approach reveals that interacting noncancerous MCF10A cells can be described by repulsion and friction interactions. In contrast, cancerous MDA-MB-231 cells exhibit attraction and antifriction interactions, promoting the predominant relative sliding behavior observed for these cells. Based on these experimentally inferred interactions, we show how this framework may generalize to provide a unifying theoretical description of the diverse cellular interaction behaviors of distinct cell types.

scholarly journals Predicting global dynamics of spatial microbial communities from local interaction rules

2020 ◽  
Author(s):  
Simon van Vliet ◽  
Christoph Hauert ◽  
Martin Ackermann ◽  
Alma Dal Co
Keyword(s):  
Growth Rate ◽  
Microbial Communities ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Cell Types ◽  
Cell Interactions ◽  
Community Level ◽  
Global Dynamics ◽  
Mathematical Framework ◽  
Cell Cell

AbstractInteractions between cells drive biological processes across all of life, from microbes in the environment to cells in multicellular organisms. Interactions often arise in spatially structured settings, where cells mostly interact with their neighbors. A central question is how the properties of biological systems emerge from local interactions. This question is very relevant in the context of microbial communities, such as biofilms, where cells live close by in space and are connected via a dense network of biochemical interactions. To understand and control the functioning of these communities, it is essential to uncover how community-level properties, such as the community composition, spatial arrangement, and growth rate, arise from these interactions. Here, we develop a mathematical framework that can predict community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our predictions match quantitative measurements from an experimental cross-feeding community. For these cross-feeding communities, the community growth rate is reduced when cells interact only with few neighbors; as a result, some communities can co-exist in a well-mixed system, but not in a spatial one. In general, our framework shows that key molecular parameters underlying the cell-cell interactions (e.g. the uptake and leakage rates of molecules) determine community level properties. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how biological functions arise from interactions between single cells.

scholarly journals Substrate mediated elastic coupling between motile cells modulates inter–cell interactions and enhances cell–cell contact

2021 ◽  
Author(s):  
Subhaya Bose ◽  
Kinjal Dasbiswas ◽  
Arvind Gopinath
Keyword(s):  
Cell Motility ◽  
Single Cells ◽  
Cell Structure ◽  
Control Cell ◽  
Cell Interactions ◽  
Biophysical Model ◽  
Cell Contact ◽  
Motile Cells ◽  
Key Aspects ◽  
Cell Cell

AbstractThe mechanical micro–environment of cells and tissues influences key aspects of cell structure and function including cell motility. For proper tissue development, cells need to migrate, interact with other neighbouring cells and form contacts, each of which require the cell to exert physical forces. Cells are known to exert contractile forces on underlying soft substrates. These stresses result in substrate deformation that can affect migratory behavior of cells as well as provide an avenue for cells to sense each other and coordinate their motion. The role of substrate mechanics, particularly its stiffness, in such biological processesis therefore a subject of active investigation. Recent progress in experimental techniques have enabled key insights into pairwise mechanical interactions that control cell motility when they move on compliant soft substrates. Analysis and modeling of such systemsis however still in its nascent stages. Motivated by the role modeling is expected to play in interpreting, informing and guiding experiments, we build a biophysical model for cell migration and cell–cell interactions. Our focus is on situations highly relevant to tissue engineering and regenerative medicine –when substrate traction stresses induced by motile cells enable substrate deformation and serve as a medium of communication. Using a generalizable agent–basedmodel, we compute key metrics of cell motile behavior such as the number of cell–cell contacts over a given time, dispersion of cell trajectories, and probability of permanent cell contact, and analyze how these depend on a cell motility parameter and on substrate stiffness. Our results provide a framework towards modeling the manner in which cells may sense each other mechanically via the substrate and use this information to generate coordinated movements across much longer length scales. Our results also provide a foundation to analyze experiments on the phenomenon known as durotaxis where single cells move preferentially towards regions of high stiffness on patterned substrates.

scholarly journals Role of cell polarity dynamics and motility in pattern formation due to contact-dependent signalling

2021 ◽  
Vol 18 (175) ◽  
pp. 20200825
Author(s):  
Supriya Bajpai ◽  
Ranganathan Prabhakar ◽  
Raghunath Chelakkot ◽  
Mandar M. Inamdar
Keyword(s):  
Cell Motility ◽  
Cell Polarity ◽  
Collective Motion ◽  
Cell Signalling ◽  
Cell Polarization ◽  
Physical Contact ◽  
Signalling Molecules ◽  
Tightly Coupled ◽  
Spatio Temporal ◽  
Cell Cell

A key challenge in biology is to understand how spatio-temporal patterns and structures arise during the development of an organism. An initial aggregate of spatially uniform cells develops and forms the differentiated structures of a fully developed organism. On the one hand, contact-dependent cell–cell signalling is responsible for generating a large number of complex, self-organized, spatial patterns in the distribution of the signalling molecules. On the other hand, the motility of cells coupled with their polarity can independently lead to collective motion patterns that depend on mechanical parameters influencing tissue deformation, such as cellular elasticity, cell–cell adhesion and active forces generated by actin and myosin dynamics. Although modelling efforts have, thus far, treated cell motility and cell–cell signalling separately, experiments in recent years suggest that these processes could be tightly coupled. Hence, in this paper, we study how the dynamics of cell polarity and migration influence the spatiotemporal patterning of signalling molecules. Such signalling interactions can occur only between cells that are in physical contact, either directly at the junctions of adjacent cells or through cellular protrusional contacts. We present a vertex model which accounts for contact-dependent signalling between adjacent cells and between non-adjacent neighbours through long protrusional contacts that occur along the orientation of cell polarization. We observe a rich variety of spatiotemporal patterns of signalling molecules that is influenced by polarity dynamics of the cells, relative strengths of adjacent and non-adjacent signalling interactions, range of polarized interaction, signalling activation threshold, relative time scales of signalling and polarity orientation, and cell motility. Though our results are developed in the context of Delta–Notch signalling, they are sufficiently general and can be extended to other contact dependent morpho-mechanical dynamics.

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