Computational Model for Migration of a Cell Cluster in Three-Dimensional Matrices

Vargas, Diego A.; Zaman, Muhammad H.

doi:10.1007/s10439-011-0290-9

Cited by 8 publications

(8 citation statements)

References 23 publications

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“…(2). This is in line with similar treatments in the literature [10], [52], although local variations of the rheological properties of the ECM and the effect of the geometry of cell clusters on transport cannot be fully captured. Nonetheless, the use of a Stokesian term can still be reasonable, since one can consider that inhomogeneous contributions have been averaged out for the duration of cell movement stages of attachment, protrusion, detachment and traction.…”

Section: Methodssupporting

confidence: 90%

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics

et al. 2013

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Cell migration in healthy and diseased systems is a combination of single and collective cell motion. While single cell motion has received considerable attention, our understanding of collective cell motion remains elusive. A new computational framework for the migration of groups of cells in three dimensions is presented, which focuses on the forces acting at the microscopic scale and the interactions between cells and their extracellular matrix (ECM) environment. Cell-cell adhesion, resistance due to the ECM and the factors regulating the propulsion of each cell through the matrix are considered. In particular, our approach emphasizes the role of receptors that mediate cell-cell and cell-matrix interactions, and examines how variation in their properties induces changes in cellular motion. As an important case study, we analyze two interacting cells. Our results show that the dynamics of cell pairs depends on the magnitude and the stochastic nature of the forces. Stronger intercellular stability is generally promoted by surface receptors that move. We also demonstrate that matrix resistance, cellular stiffness and intensity of adhesion contribute to migration behaviors in different ways, with memory effects present that can alter pair motility. If adhesion weakens with time, our findings show that cell pair break-up depends strongly on the way cells interact with the matrix. Finally, the motility for cells in a larger cluster (size 50 cells) is examined to illustrate the full capabilities of the model and to stress the role of cellular pairs in complex cellular structures. Overall, our framework shows how properties of cells and their environment influence the stability and motility of cellular assemblies. This is an important step in the advancement of the understanding of collective motility, and can contribute to knowledge of complex biological processes involving migration, aggregation and detachment of cells in healthy and diseased systems.

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Section: Methodssupporting

confidence: 90%

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics

et al. 2013

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“…19 Derived from forced based mechanistic models of single cell migration, a model of a cell cluster was developed taking into consideration the impact of three major factors: ligand concentration, matrix metalloproteinase activity, and cluster geometry. 55 This model is promising, successfully showing potential effects of altering single variables in a system of cells in motion.…”

Section: Computational Models Pertaining To Differentiated Cell Migramentioning

confidence: 96%

“…23,24 Observations such as this have led to both the development and engineering of in vitro platforms to study migration as well as consideration of this phenomenon in CM. 24,49,55 The internal differences in gene and protein expression of different cell types are now considered in CM.…”

Section: Computational Models Pertaining To Differentiated Cell Migramentioning

confidence: 99%

Computational Modeling of Stem Cell Migration: A Mini Review

et al. 2014

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Abstract-Stem cell migration is crucial in many biological processes such as embryogenesis, histogenesis, and stem cell biology. It is also an important process in physiology, and in medicine, it can contribute to develop effective stem cell therapies. While there is a large body of experimental evidence that attempts to understand the biological and physiological mechanisms governing stem cell activity in the organism, computational modeling studies are scarce. Because stem cell migration is affected by biological diversity and the complexity of the cells' microenvironment, experiments are hard to conduct and corresponding measurements are sophisticated. Computational modeling is a good complementary method to help us understand this process. Here, a mini-review is presented discussing the existing efforts and the unsolved key issues in stem cell migration. In addition, existing computational models studying the migration of differentiated cells are briefly discussed in the context of how they can be applied to increase our understanding of the dynamics involved in stem cell migration: Particular emphasis is placed on how biomechanical aspects of migration are explored in these models.

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“…Our work shows that eliminating specific cells allow the analysis of subtle but scorable phenotypes. A current challenge is to provide computational models for collective migration (Vargas and Zaman, 2011); however, the value and significance of such models heavily relies on our knowledge of this complex and dynamic process. In the future, it will be of great interest to incorporate parameters that take into account the homeostatic cell interactions of the kind we have described, to faithfully simulate collective migration.…”

Section: Homeostatic Interactions At the Tip Of The Migrating Chain: mentioning

confidence: 99%

Homeostatic Interactions at the Front of Migration Control the Integrity and the Efficiency of a Migratory Glial Chain

Berzsenyi¹,

Kumar²,

Giangrande³

2011

J. Neurosci.

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In metazoans, cell migration often occurs in a collective manner: the cells move while physically and functionally connected to their neighbors. The coordinated and timely movement of the cells eventually ensures the proper organization of tissues, and deregulation in such a process contributes to the development of severe diseases. Thus, understanding the cellular mechanisms underlying coordinated cell movement is of great interest in basic and medical science.The developing Drosophila wing provides an excellent model to follow the chain migration of glial cells in vivo. Cells at the tip of the glial collective have been shown to control the timely movement of the chain. In the present study, we show that while pioneers trigger chain migration, they cannot move as single cells. We also show that isolating cell clusters at the chain tip restores the formation of smaller migratory communities. Interestingly, the migratory efficiency of these de novo formed communities depends on the number of cells and progressively improves as the size of the cluster increases. Thus, homeostatic events at the migratory front control community integrity, efficiency, and coordination, emphasizing the importance of interactions and cell counting in fine-tuning collective processes.

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Computational Model for Migration of a Cell Cluster in Three-Dimensional Matrices

Cited by 8 publications

References 23 publications

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics

A Computational Model for Collective Cellular Motion in Three Dimensions: General Framework and Case Study for Cell Pair Dynamics

Computational Modeling of Stem Cell Migration: A Mini Review

Homeostatic Interactions at the Front of Migration Control the Integrity and the Efficiency of a Migratory Glial Chain

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