Taking Aim at Moving Targets in Computational Cell Migration

Masuzzo, Paola; Troys, Marleen Van; Ampè, Christophe; Martens, Lennart

doi:10.1016/j.tcb.2015.09.003

Cited by 98 publications

(123 citation statements)

References 165 publications

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“…Multiple models of collective cell migration have been reported to simulate force transmission between cells[14], the generation of finger cells [45,46], the advancement of free edges [47] and other features of collective migration, but little has been done on cell migration velocity evolution in wound healing. Similar particle based modeling has been used to simulate collective migration [45,48].…”

Section: Discussionmentioning

confidence: 99%

Collective cell migration has distinct directionality and speed dynamics

Zhang

Lee

et al. 2017

Cell. Mol. Life Sci.

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When a constraint is removed, confluent cells migrate directionally into the available space. How the migration directionality and speed increase are initiated at the leading edge and propagate into neighboring cells are not well understood. Using a quantitative visualization technique — Particle Image Velocimetry (PIV) — we revealed that migration directionality and speed had strikingly different dynamics. Migration directionality increases as a wave propagating from the leading edge into the cell sheet, while the increase in cell migration speed is maintained only at the leading edge. The overall directionality steadily increases with time as cells migrate into the cell-free space, but migration speed remains largely the same. A Particle-Based Compass (PBC) model suggests cellular interplay (which depends on cell-cell distance) and migration speed are sufficient to capture the dynamics of migration directionality revealed experimentally. Extracellular Ca2+ regulated both migration speed and directionality, but in a significantly different way, suggested by the correlation between directionality and speed only in some dynamic ranges. Our experimental and modeling results reveal distinct directionality and speed dynamics in collective migration, and these factors can be regulated by extracellular Ca2+ through cellular interplay. Quantitative visualization using PIV and our PBC model thus provide a powerful approach to dissect the mechanisms of collective cell migration.

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Section: Discussionmentioning

confidence: 99%

Collective cell migration has distinct directionality and speed dynamics

Zhang

Lee

et al. 2017

Cell. Mol. Life Sci.

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“…A number of relevant studies have helped to reveal homeostatic and nonhomeostatic HSC–niche behavior . Spatial data that describe cell migration patterns enable the testing of hypotheses regarding the relative locations of different cell types, the modes of cell movement, and the factors that determine the behavior of migrating cells .…”

Section: Introductionmentioning

confidence: 99%

Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection

et al. 2017

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The hematopoietic stem cell (HSC) niche provides essential microenvironmental cues for the production and maintenance of HSCs within the bone marrow. During inflammation, hematopoietic dynamics are perturbed, but it is not known whether changes to the HSC-niche interaction occur as a result. We visualize HSCs directly in vivo, enabling detailed analysis of the 3D niche dynamics and migration patterns in murine bone marrow following Trichinella spiralis infection. Spatial statistical analysis of these HSC trajectories reveals two distinct modes of HSC behavior: (a) a pattern of revisiting previously explored space and (b) a pattern of exploring new space. Whereas HSCs from control donors predominantly follow pattern (a), those from infected mice adopt both strategies. Using detailed computational analyses of cell migration tracks and life-history theory, we show that the increased motility of HSCs following infection can, perhaps counterintuitively, enable mice to cope better in deteriorating HSC-niche microenvironments following infection. STEM CELLS 2017;35:2292-2304 SIGNIFICANCE STATEMENTThis analysis shows differences in the migration behavior of hematopoietic stem cells (HSCs) following exposure to infection by Trichinella spiralis. HSCs harvested from infected mice show pronounced heterogeneity in their behavior compared with HSCs from healthy mice, in a way that suggests long-lasting agitation following deterioration of the HSC niche environment.

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“…Reverse engineering of how these individual cell movements lead to collective migration patterns has proved difficult. Whereas computational models are able to test whether a given set of ad hoc assumptions lead to emergence of observed patterns, these models usually ignore heterogeneity of cell responses, overlook complex behavior dynamics, and rarely perform quantitative comparisons with in vivo results (9)(10)(11)(12).…”

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confidence: 99%

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

Cotter

Schüttler

Igoshin

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

145

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Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with datadriven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.agent-based simulation | image processing | emergent behavior | fluorescent imaging | cell communication C ollective cell migration is essential for many developmental processes, including fruiting body development of myxobacteria (1) and Dictyostelium (2), embryonic gastrulation (3, 4), and neural crest development (5). Conversely, cancer cell metastases represent detrimental migratory events that disseminate dysfunctional cells (6). In all these processes, a population of cells leaves its current location and migrates in a coordinated manner to new locations where motility becomes reduced. Remarkable progress has been made in studying the intracellular machinery of these organisms (7). Much less is known about the systemlevel coordination of cell migration. Cell movement in these systems is a 3D, dynamic process coordinated by a combination of diverse physical and chemical cues acting on the cells (3,5,8). Recent developments in tracking individual cell movement in vivo have provided unprecedented detail and revealed surprising levels of heterogeneity (5, 7). Reverse engineering of how these individual cell movements lead to collective migration patterns has proved difficult. Whereas computational models are able to test whether a given set of ad hoc assumptions lead to e...

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Taking Aim at Moving Targets in Computational Cell Migration

Cited by 98 publications

References 165 publications

Collective cell migration has distinct directionality and speed dynamics

Collective cell migration has distinct directionality and speed dynamics

Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

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