Model-based Comparison of Cell Density-dependent Cell Migration Strategies

Hatzikirou, Haralampos; Böttger, K.; Deutsch, Andreas

doi:10.1051/mmnp/201510105

Cited by 12 publications

(7 citation statements)

References 21 publications

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“…chemotaxis). BIO-LGCA models have already been used in the study of several biological processes, namely angiogenesis [35], bacterial rippling [36], Turing pattern formation [37], active media [38], epidemiology [39] and various aspects of tumor dynamics [24,40,41,42,43,44,45,46,47], among others. BIO-LGCA models allow multiscale analysis of behaviours emerging at multiple temporal and spatial scales.…”

Section: Discussionmentioning

confidence: 99%

BIO-LGCA: a cellular automaton modelling class for analysing collective cell migration

Deutsch

Nava-Sedeño

Syga

et al. 2020

Preprint

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Collective dynamics in multicellular systems such as biological organs and tissues plays a key role in biological development, regeneration, and pathological conditions. Collective dynamics - understood as population behaviour arising from the interplay of the constituting discrete cells - can be studied with mathematical models. Off- and on-lattice agent-based models allow to analyse the link between individual cell and collective behaviour. Notably, in on-lattice agent-based models known as cellular automata, collective behaviour can not only be analysed through computer simulations, but predicted with mathematical methods. However, classical cellular automaton models fail to replicate key aspects of collective migration, which is a central instance of collective behaviour in multicellular systems. To overcome drawbacks of classical on-lattice models, we introduce a novel on-lattice, agent-based modelling class for collective cell migration, which we call biological lattice-gas cellular automaton (BIO-LGCA). The BIO-LGCA is characterised by synchronous time updates, and the explicit consideration of individual cell velocities. While rules in classical cellular automata are typically chosen ad hoc, we demonstrate that rules for cell-cell and cell-environment interactions in the BIO-LGCA can also be derived from experimental single cell migration data or biophysical laws for individual cell migration. Furthermore, we present elementary BIO-LGCA models of fundamental cell interactions, which may be combined in a modular fashion to model complex multicellular phenomena. Finally, we present a mathematical mean-field analysis of a BIO-LGCA model that allows to predict collective patterns for a particular cell-cell interaction.

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Section: Discussionmentioning

confidence: 99%

BIO-LGCA: a cellular automaton modelling class for analysing collective cell migration

Deutsch

Nava-Sedeño

Syga

et al. 2020

Preprint

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“…Also, once the cell division cycle becomes longer than 24 h due to cell density and contact inhibition, it is difficult to study single cell activity within a colony. 57,58 SCA using micropatterning allows a greater level of control both on experimental design, as well as cellular growth and observation capabilities. Due to the relatively small number of cells (hundreds to a few thousand) in the patterned culture, nutrient consumption was minimal.…”

Section: Discussionmentioning

confidence: 99%

Microstencil-based spatial immobilization of individual cells for single cell analysis

Zaidi

Agrawal

2018

Biomicrofluidics

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Cells exhibit biologically heterogeneous phenotypes, particularly in pathogenic states. To study cell behavior at the single cell level, a variety of micropatterning techniques have been proposed that allow the spatial organization of cells with great control over cell volume, morphology, and intercellular interactions. Among these strategies, microstencil patterning has traditionally been eschewed due to fragility of membranes and lack of control over cell configurations within patterns. Here, we present a simple and reproducible strategy to create robust microstencils and achieve consistent and efficient cell patterns requiring less than 4 μl of cell solution. Polydimethylsiloxane microstencils fabricated with this technique can be used dozens of times over the course of several months with minimal wear or degradation. Characterization of pattern size, cell suspension density, and droplet volume allows on-demand configurations of singlets, doublets, triplets, or multiple cells per individual space. In addition, a novel technique to suppress evaporative convection provides precise and repeatable results, with a twofold increase in patterning efficacy. Selective dual surface modification to create hydrophilic islands on a hydrophobic substrate facilitates a significantly longer and healthier lifespan of cells without crossover of pattern boundaries. The ability to pattern individual cells with or without an extracellular matrix substrate and to control the magnitude of cell-cell contact as well as spread area provides a powerful approach to monitoring cell functions such as proliferation and intercellular signaling.

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“…LGCA models were introduced to investigate various aspects of single and collective cell migration [22,[26][27][28][29]. A sketch of the latticegas model is shown in figure 2b.…”

Section: (B) On-lattice Modelmentioning

confidence: 99%

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

Nava-Sedeño

Voß-Böhme

Hatzikirou

et al. 2020

Phil. Trans. R. Soc. B

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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’.

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Model-based Comparison of Cell Density-dependent Cell Migration Strategies

Cited by 12 publications

References 21 publications

BIO-LGCA: a cellular automaton modelling class for analysing collective cell migration

BIO-LGCA: a cellular automaton modelling class for analysing collective cell migration

Microstencil-based spatial immobilization of individual cells for single cell analysis

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

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