Experiment, theory, and the keratocyte: An ode to a simple model for cell motility

Mogilner, Alex; Barnhart, Erin L.; Keren, Kinneret

doi:10.1016/j.semcdb.2019.10.019

Cited by 38 publications

(50 citation statements)

References 104 publications

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“…Indeed, the combined local activation of protrusions and global inhibition via membrane tension dynamically link cell shape to cell motion in the CPM. Similar to shape-motility interactions observed in real cells (13), Act cell shapes are closely linked to both motility characteristics underlying the UCSP: speed and turning behavior.…”

Section: Discussionsupporting

confidence: 56%

“…The models used are diverse, ranging from relatively simple particle models to detailed physical models linking intracellular signalling and cell shape (12,13). These models differ in how they describe motion: while motion characteristics such as speed and persistence are input parameters in the simpler particle models, in the more complex mechanistic models, motion emerges as output of the underlying dynamics (which can involve a combination of molecular signalling, cell shape, and environmental factors, depending on the models used).…”

Section: Introductionmentioning

confidence: 99%

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Actin-inspired feedback couples speed and persistence in a Cellular Potts Model of cell migration

Wortel

Niculescu

et al. 2018

Preprint

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8 9T cells are key effector cells in the immune system that are well-known for their ability to adapt their shape and 10 behavior to environmental cues. It has been suggested that these highly diverse, context-dependent migration 11 patterns reflect an optimization process -where T cells adjust motility parameters such as speed and persistence 12 to aid their search for antigen. Whereas models investigating such "search strategies" typically treat speed and 13 persistence as independent variables, one aspect of cell motility was recently found to be conserved across 14 a large variety of cell types: fast-moving cells turn less frequently. This raises the question whether T cells 15 can tune speed and persistence independently of each other. We therefore investigated to what extent this 16 universal coupling between cell speed and persistence (UCSP) shapes the behavior of migrating T cells. We 17 first show that the UCSP emerges spontaneously in an in silico Cellular Potts Model (CPM) of T cell migration. 18 Our model shows a link between the UCSP and cell shape dynamics, which put an upper bound on both the 19 speed and the persistence a cell can reach. We then use the CPM to examine how environmental constraints 20 affect motility patterns of T cells migrating in the crowded environments they also face in vivo, and show that T 21 cells completely lose their speed-persistence coupling when confined in a densely packed environment such 22 as the epidermis. Thus, although our model further highlights the validity of the UCSP in migrating cells, it 23 also demonstrates that environmental factors may overrule this coupling. Our data show that T cell motility 24 parameters are subject to both cell-intrinsic and extrinsic constraints, suggesting that "optimal" T cell search 25 strategies may not always be attainable in vivo. 26 1 28 T cells have the rare ability to migrate in nearly all tissues within the human body. Especially in tissues with a 29 high risk of infection -like the lung, the gut, and the skin -T cells are continuously on the move in search of 30 foreign invaders. Furthermore, migration in lymphoid organs such as the thymus and lymph nodes is crucial 31 for T cell function. 32Although T cells preserve their motility in these different contexts, they do adapt their morphology and 33 migratory behavior to environmental cues. It has been suggested that this remarkably flexible behavior reflects 34 different "search strategies" that allow T cells to maximize the chance of encountering antigen (Krummel et al., 35 2016). For example, naive T cells rapidly crawl along a network of stromal cells in the lymph node, alternating 36 between short intervals of persistent movement and random changes in direction (Miller et al., 2002(Miller et al., , 2003 37 Bajnoff et al., 2006; Beauchemin et al., 2007). This "stop and go" behavior allows them to cover large areas of the 38 lymph node in a short amount of time, and appears to be a good strategy for finding rare antigens without prior 39 information o...

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Section: Discussionsupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Actin-inspired feedback couples speed and persistence in a Cellular Potts Model of cell migration

Wortel

Niculescu

et al. 2018

Preprint

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“…It adopts a variety of architectures that contribute to protrusion, adhesion, contraction, and retraction of the cell 63 . At the leading edge, branched and crosslinked networks form a lamellipodium that, by pushing the plasma membrane forward, promotes cell movement 64 . Thin actin‐rich, finger‐like membrane protrusions called filopodia assemble from peripheral regions of the cell in response to chemical stimuli, providing initial cell‐substrate contact sites 65,66 .…”

Section: The Architecture Of the Actin Cytoskeletonmentioning

confidence: 99%

Three‐dimensional organization of the cytoskeleton: A cryo‐electron tomography perspective

2020

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Traditionally, structures of cytoskeletal components have been studied ex situ, that is, with biochemically purified materials. There are compelling reasons to develop approaches to study them in situ in their native functional context. In recent years, cryo-electron tomography emerged as a powerful method for visualizing the molecular organization of unperturbed cellular landscapes with the potential to attain near-atomic resolution. Here, we review recent works on the cytoskeleton using cryo-electron tomography, demonstrating the power of in situ studies. We also highlight the potential of this method in addressing important questions pertinent to the field of cytoskeletal biomechanics. K E Y W O R D S actin filaments, cryo-electron tomography, in situ architecture, intermediate filaments, microtubules Abbreviations: 3D, three-dimensional; ATP, adenosine triphosphate;

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“…1B), chosen to approximate an experimentally measured turning cell shape ( Fig. 3f in [11] and [12]). Similar to the observed turning cells, there is a lower aspect ratio on the slower side and a higher aspect ratio on the faster side, i.e.…”

Section: Asymmetries In Myosin Distribution Actin Flow and Traction mentioning

confidence: 99%

Modeling cell turning by mechanics at the cell rear

et al. 2020

Preprint

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In this study, we explore a simulation of a mechanical model of the keratocyte lamellipodium as previously tested and calibrated for straight steady-state motility [1] and for the process of polarization and motility initiation [2]. In brief, this model uses the balance of three essential forces (myosin contraction, adhesive drag and actin network viscosity) to determine the cell's mechanical behavior. Cell shape is set by the balance between the actin polymerization-driven protrusion at the cell boundary and myosin-driven retraction of the actin-myosin network. In the model, myosin acts to generate contractile stress applied to a viscous actin network with viscous resistance to actin flow created by adhesion to the substrate. Previous study [3] demonstrated that similar simple model with uniform constant adhesion predicts a rotating behavior of the cell; however, this behavior is idealized, and does not mimic observed features of the keratocyte's turning behavior. Our goal is to explore what are the consequences of introducing mechanosensitive adhesions to the model.

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Experiment, theory, and the keratocyte: An ode to a simple model for cell motility

Cited by 38 publications

References 104 publications

Actin-inspired feedback couples speed and persistence in a Cellular Potts Model of cell migration

Actin-inspired feedback couples speed and persistence in a Cellular Potts Model of cell migration

Three‐dimensional organization of the cytoskeleton: A cryo‐electron tomography perspective

Modeling cell turning by mechanics at the cell rear

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