scholarly journals Inferring single-cell behaviour from large-scale epithelial sheet migration patterns

2017 ◽  
Vol 14 (130) ◽  
pp. 20170147 ◽  
Author(s):  
Rachel M. Lee ◽  
Haicen Yue ◽  
Wouter-Jan Rappel ◽  
Wolfgang Losert
Keyword(s):  
Cell Migration ◽  
Large Scale ◽  
Collective Motion ◽  
Individual Cell ◽  
Metastatic Cancer ◽  
Emergent Properties ◽  
Collective Migration ◽  
Cell Behaviour ◽  
Cell Motion ◽  
Insight Into

Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behaviour. The emergent properties of collective migration are receiving increasing attention as collective motion's role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behaviour influences large-scale, multi-cell collective motion remains unclear. In this study, we provide insight into the mechanisms behind collective migration by studying cell migration in a spreading monolayer of epithelial MCF10A cells. We quantify migration using particle image velocimetry and find that cell groups have features of motion that span multiple length scales. Comparing our experimental results to a model of collective cell migration, we find that cell migration within the monolayer can be affected in qualitatively different ways by cell motion at the boundary, yet it is not necessary to introduce leader cells at the boundary or specify other large-scale features to recapitulate this large-scale phenotype in simulations. Instead, in our model, collective motion can be enhanced by increasing the overall activity of the cells or by giving the cells a stronger coupling between their motion and polarity. This suggests that investigating the activity and polarity persistence of individual cells will add insight into the collective migration phenotypes observed during development and disease.

scholarly journals A Force Based Model of Individual Cell Migration With Discrete Attachment Sites and Random Switching Terms

2013 ◽  
Vol 135 (7) ◽  
Author(s):  
J. C. Dallon ◽  
Matthew Scott ◽  
W. V. Smith
Keyword(s):  
Cell Migration ◽  
Individual Cell ◽  
Cell Types ◽  
Cell Binding ◽  
Stochastic Nature ◽  
Attachment Sites ◽  
Random Switching ◽  
Cell Motion ◽  
Cellular Forces ◽  
Insight Into

A force based model of cell migration is presented which gives new insight into the importance of the dynamics of cell binding to the substrate. The main features of the model are the focus on discrete attachment dynamics, the treatment of the cellular forces as springs, and an incorporation of the stochastic nature of the attachment sites. One goal of the model is to capture the effect of the random binding and unbinding of cell attachments on global cell motion. Simulations reveal one of the most important factor influencing cell speed is the duration of the attachment to the substrate. The model captures the correct velocity and force relationships for several cell types.

scholarly journals Rules of collective migration: from the wildebeest to the neural crest

2020 ◽  
Vol 375 (1807) ◽  
pp. 20190387 ◽  
Author(s):  
Adam Shellard ◽  
Roberto Mayor
Keyword(s):  
Neural Crest ◽  
Individual Cell ◽  
Embryonic Stem ◽  
Stem Cell Population ◽  
Scale Analysis ◽  
Collective Migration ◽  
Theme Issue ◽  
Cell Behaviour ◽  
Multi Scale ◽  
Universal Principles

Collective migration, the movement of groups in which individuals affect the behaviour of one another, occurs at practically every scale, from bacteria up to whole species' populations. Universal principles of collective movement can be applied at all levels. In this review, we will describe the rules governing collective motility, with a specific focus on the neural crest, an embryonic stem cell population that undergoes extensive collective migration during development. We will discuss how the underlying principles of individual cell behaviour, and those that emerge from a supracellular scale, can explain collective migration. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

scholarly journals Modelling collective cell motion: are on- and off-lattice models equivalent?

2020 ◽  
Vol 375 (1807) ◽  
pp. 20190378 ◽  
Author(s):  
Josué Manik Nava-Sedeño ◽  
Anja Voß-Böhme ◽  
Haralampos Hatzikirou ◽  
Andreas Deutsch ◽  
Fernando Peruani
Keyword(s):  
Wound Repair ◽  
Collective Motion ◽  
Scale Effects ◽  
Lattice Models ◽  
Population Level ◽  
Collective Migration ◽  
Fruiting Body Formation ◽  
Bacterial Patterns ◽  
Dynamical Description ◽  
Cell Motion

Biological processes, such as embryonic development, wound repair and cancer invasion, or bacterial swarming and fruiting body formation, involve collective motion of cells as a coordinated group. Collective cell motion of eukaryotic cells often includes interactions that result in polar alignment of cell velocities, while bacterial patterns typically show features of apolar velocity alignment. For analysing the population-scale effects of these different alignment mechanisms, various on- and off-lattice agent-based models have been introduced. However, discriminating model-specific artefacts from general features of collective cell motion is challenging. In this work, we focus on equivalence criteria at the population level to compare on- and off-lattice models. In particular, we define prototypic off- and on-lattice models of polar and apolar alignment, and show how to obtain an on-lattice from an off-lattice model of velocity alignment. By characterizing the behaviour and dynamical description of collective migration models at the macroscopic level, we suggest the type of phase transitions and possible patterns in the approximative macroscopic partial differential equation descriptions as informative equivalence criteria between on- and off-lattice models. This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems’.

scholarly journals Bridging the gap between single-cell migration and collective dynamics

2019 ◽  
Author(s):  
Florian Thüroff ◽  
Andriy Goychuk ◽  
Matthias Reiter ◽  
Erwin Frey
Keyword(s):  
Cell Migration ◽  
Collective Motion ◽  
Single Cells ◽  
Cellular Migration ◽  
Coarse Grained ◽  
Collective Migration ◽  
Modeling Framework ◽  
Cell Functions ◽  
Cell Shapes ◽  
The Impact

AbstractA wealth of experimental data relating to the emergence of collective cell migration as one proceeds from the behavioral dynamics of small cohorts of cells to the coordinated migratory response of cells in extended tissues is now available. Integrating these findings into a mechanistic picture of cell migration that is applicable across such a broad range of system sizes constitutes a crucial step towards a better understanding of the basic factors that determine the emergence of collective cell motion. Here we present a cellular-automaton-based modeling framework, which focuses on the integration of high-level cell functions and their concerted effect on cellular migration patterns. In particular, we adopt a top-down approach to incorporate a coarse-grained description of cell polarity and its response to mechanical cues, and address the impact of cell adhesion on collective migration in cell groups. We demonstrate that the model faithfully reproduces typical cell shapes and movements down to the level of single cells, yet is computationally efficient enough to allow for the simulation of (currently) up to 𝒪(104) cells. To develop a mechanistic picture that illuminates the relationship between cell functions and collective migration, we present a detailed study of small groups of cells in confined circular geometries, and discuss the emerging patterns of collective motion in terms of specific cellular properties. Finally, we apply our computational model at the level of extended tissues, and investigate stress and velocity distributions, as well as front morphologies, in expanding cellular sheets.

scholarly journals A Stochastic Model For Protrusion Activity

2018 ◽  
Vol 62 ◽  
pp. 56-67
Author(s):  
Christèle Etchegaray ◽  
Nicolas Meunier
Keyword(s):  
Cell Migration ◽  
Large Scale ◽  
Classical Particle ◽  
Mathematical Framework ◽  
Fundamental Properties ◽  
Structured Population ◽  
Cell Velocity ◽  
Study Population ◽  
Cell Switches ◽  
Cell Motion

In this work we approach cell migration under a large-scale assumption, so that the system reduces to a particle in motion. Unlike classical particle models, the cell displacement results from its internal activity: the cell velocity is a function of the (discrete) protrusive forces exerted by filopodia on the substrate. Cell polarisation ability is modeled in the feedback that the cell motion exerts on the protrusion rates: faster cells form preferentially protrusions in the direction of motion. By using the mathematical framework of structured population processes previously developed to study population dynamics [4], we introduce rigorously the mathematical model and we derive some of its fundamental properties. We perform numerical simulations on this model showing that different types of trajectories may be obtained: Brownian-like, persistent, or intermittent when the cell switches between both previous regimes. We find back the trajectories usually described in the literature for cell migration.

scholarly journals Cell migration guided by long-lived spatial memory

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joseph d’Alessandro ◽  
Alex Barbier--Chebbah ◽  
Victor Cellerin ◽  
Olivier Benichou ◽  
René Marc Mège ◽  
...  
Keyword(s):  
Cell Migration ◽  
Spatial Memory ◽  
Large Scale ◽  
Single Cells ◽  
Environmental Perturbations ◽  
Motile Cells ◽  
Unicellular Organisms ◽  
Biochemical Signals ◽  
The Impact ◽  
Cell Trajectories

AbstractLiving cells actively migrate in their environment to perform key biological functions—from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion, and has been shown to also integrate various chemical or physical extracellular signals. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodelling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells can retrieve their path: by confining motile cells on 1D and 2D micropatterned surfaces, we demonstrate that they leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.

scholarly journals Geo-Spatial Analysis of Population Density and Annual Income to Identify Large-Scale Socio-Demographic Disparities

2021 ◽  
Vol 10 (7) ◽  
pp. 432
Author(s):  
Nicolai Moos ◽  
Carsten Juergens ◽  
Andreas P. Redecker
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Methodological Approach ◽  
Spatial Relationship ◽  
Postal Code ◽  
Annual Income ◽  
Choropleth Maps ◽  
Clustering Approach ◽  
Relationship Of ◽  
Insight Into

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons.

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