scholarly journals Quasi-periodic migration of single cells on short microlanes

2019 ◽  
Author(s):  
Fang Zhou ◽  
Sophia A. Schaffer ◽  
Christoph Schreiber ◽  
Felix J. Segerer ◽  
Andriy Goychuk ◽  
...  
Keyword(s):  
Cell Migration ◽  
Actin Polymerization ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Local Deformation ◽  
Physical Models ◽  
Cellular Potts Model ◽  
Periodic Movement ◽  
Cell Shapes ◽  
Cytoskeleton Dynamics

AbstractCell migration on microlanes represents a suitable and simple platform for the exploration of the molecular mechanisms underlying cell cytoskeleton dynamics. Here, we report on the quasi-periodic movement of cells confined in stripe-shaped microlanes. We observe persistent polarized cell shapes and directed pole-to-pole motion within the microlanes. Cells depolarize at one end of a given microlane, followed by delayed repolarization towards the opposite end. We analyze cell motility via the spatial velocity distribution, the velocity frequency spectrum and the reversal time as a measure for depolarization and spontaneous repolarization of cells at the microlane ends. The frequent encounters of a boundary in the stripe geometry provides a robust framework for quantitative investigations of the cytoskeleton protrusion and repolarization dynamics. In a first advance to rigorously test physical models of cell migration, we find that the statistics of the cell migration is recapitulated by a Cellular Potts model with a minimal description of cytoskeleton dynamics. Using LifeAct-GFP transfected cells and microlanes with differently shaped ends, we show that the local deformation of the leading cell edge in response to the tip geometry can locally either amplify or quench actin polymerization, while leaving the average reversal times unaffected.

scholarly journals The interplay of cell–cell and cell–substrate adhesion in collective cell migration

2014 ◽  
Vol 11 (100) ◽  
pp. 20140684 ◽  
Author(s):  
Chenlu Wang ◽  
Sagar Chowdhury ◽  
Meghan Driscoll ◽  
Carole A. Parent ◽  
S. K. Gupta ◽  
...  
Keyword(s):  
Cell Migration ◽  
Cell Surface ◽  
Actin Polymerization ◽  
Collective Cell Migration ◽  
Cell Contacts ◽  
Substrate Adhesion ◽  
Cell Substrate ◽  
Cell Shapes ◽  
Cell Substrate Adhesion ◽  
Cell Cell

Collective cell migration often involves notable cell–cell and cell–substrate adhesions and highly coordinated motion of touching cells. We focus on the interplay between cell–substrate adhesion and cell–cell adhesion. We show that the loss of cell-surface contact does not significantly alter the dynamic pattern of protrusions and retractions of fast migrating amoeboid cells ( Dictyostelium discoideum ), but significantly changes their ability to adhere to other cells. Analysis of the dynamics of cell shapes reveals that cells that are adherent to a surface may coordinate their motion with neighbouring cells through protrusion waves that travel across cell–cell contacts. However, while shape waves exist if cells are detached from surfaces, they do not couple cell to cell. In addition, our investigation of actin polymerization indicates that loss of cell-surface adhesion changes actin polymerization at cell–cell contacts. To further investigate cell–cell/cell–substrate interactions, we used optical micromanipulation to form cell–substrate contact at controlled locations. We find that both cell-shape dynamics and cytoskeletal activity respond rapidly to the formation of cell–substrate contact.

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 From Energy to Cellular Force in the Cellular Potts Model

2019 ◽  
Author(s):  
Elisabeth G. Rens ◽  
Leah Edelstein-Keshet
Keyword(s):  
Potts Model ◽  
Cell Shape ◽  
Rho Gtpase ◽  
Single Cells ◽  
Simple Algorithm ◽  
Cellular Potts Model ◽  
Minimization Method ◽  
Cell Shapes ◽  
Cell Shape Changes ◽  
Shape Changes

AbstractSingle and collective cell dynamics, cell shape changes, and cell migration can be conveniently represented by the Cellular Potts Model, a computational platform based on minimization of a Hamiltonian while permitting stochastic fluctuations. Using the fact that a force field is easily derived from a scalar energy (F = −∇H), we develop a simple algorithm to associate effective forces with cell shapes in the CPM. We display the predicted forces for single cells of various shapes and sizes (relative to cell rest-area and cell rest-perimeter). While CPM forces are specified directly from the Hamiltonian on the cell perimeter, we infer internal forces using interpolation, and refine the results with smoothing. Predicted forces compare favorably with experimentally measured cellular traction forces. We show that a CPM model with internal signaling (such as Rho-GTPase-related contractility) can be associated with retraction-protrusion forces that accompany cell shape changes and migration. We adapt the computations to multicellular systems, showing, for example, the forces that a pair of swirling cells exert on one another, demonstrating that our algorithm works equally well for interacting cells. Finally, we show forces associated with the dynamics of classic cell-sorting experiments in larger clusters of model cells.Author summaryCells exert forces on their surroundings and on one another. In simulations of cell shape using the Cellular Potts Model (CPM), the dynamics of deforming cell shapes is traditionally represented by an energy-minimization method. We use this CPM energy, the Hamiltonian, to derive and visualize the corresponding forces exerted by the cells. We use the fact that force is the negative gradient of energy to assign forces to the CPM cell edges, and then extend the results to interior forces by interpolation. We show that this method works for single as well as multiple interacting model cells, both static and motile. Finally, we show favorable comparison between predicted forces and real forces measured experimentally.

scholarly journals p90 ribosomal S6 kinase (RSK) phosphorylates myosin phosphatase and thereby controls edge dynamics during cell migration

2019 ◽  
Vol 294 (28) ◽  
pp. 10846-10862 ◽  
Author(s):  
Shiela C. Samson ◽  
Andrew Elliott ◽  
Brian D. Mueller ◽  
Yung Kim ◽  
Keith R. Carney ◽  
...  
Keyword(s):  
Cell Migration ◽  
Actin Polymerization ◽  
Molecular Mechanisms ◽  
Rho Kinase ◽  
Leading Edge ◽  
Myosin Phosphatase ◽  
S6 Kinase ◽  
Mammalian Cell Lines ◽  
P90 Ribosomal S6 Kinase ◽  
Ribosomal S6 Kinase

Cell migration is essential to embryonic development, wound healing, and cancer cell dissemination. Cells move via leading-edge protrusion, substrate adhesion, and retraction of the cell's rear. The molecular mechanisms by which extracellular cues signal to the actomyosin cytoskeleton to control these motility mechanics are poorly understood. The growth factor-responsive and oncogenically activated protein extracellular signal-regulated kinase (ERK) promotes motility by signaling in actin polymerization-mediated edge protrusion. Using a combination of immunoblotting, co-immunoprecipitation, and myosin-binding experiments and cell migration assays, we show here that ERK also signals to the contractile machinery through its substrate, p90 ribosomal S6 kinase (RSK). We probed the signaling and migration dynamics of multiple mammalian cell lines and found that RSK phosphorylates myosin phosphatase–targeting subunit 1 (MYPT1) at Ser-507, which promotes an interaction of Rho kinase (ROCK) with MYPT1 and inhibits myosin targeting. We find that by inhibiting the myosin phosphatase, ERK and RSK promote myosin II–mediated tension for lamella expansion and optimal edge dynamics for cell migration. These findings suggest that ERK activity can coordinately amplify both protrusive and contractile forces for optimal cell motility.

scholarly journals ELMO2 association with Gαi2 regulates pancreatic cancer cell chemotaxis and metastasis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8910
Author(s):  
Yecheng Wang ◽  
Hongyan Li ◽  
Fei Li
Keyword(s):  
Pancreatic Cancer ◽  
Cell Migration ◽  
Cancer Cell ◽  
Actin Polymerization ◽  
Molecular Mechanisms ◽  
Cancer Metastasis ◽  
Pancreatic Cancer Cell ◽  
Cancer Cell Migration ◽  
Pancreatic Cancer Cells ◽  
Cell Chemotaxis

Background Pancreatic cancer is a highly lethal disease. Nearly half of the patients have distant metastasis and remain asymptomatic. Emerging evidence suggests that the chemokine, CXCL12, has a role in cancer metastasis. The interaction between CXCL12 and CXCR4 activates heterotrimeric G proteins, which regulates actin polymerization and cancer cell migration. However, the molecular mechanisms underlying pancreatic cancer cell migration are still largely obscure. Here, we addressed the role of ELMO2 in chemotaxis and metastasis of pancreatic cancer cells. Methods Pancreatic cancer cell lines PANC-1 and AsPC-1 and siRNA-mediated knockdown of ELMO2 were used to determine the effects of ELMO2 on cancer cell chemotaxis, invasion, migration. Co-immunoprecipitation assays were carried out to identify interacting partners of ELMO2. Results ELMO2 knockdown inhibited pancreatic cancer cell chemotaxis, migration, invasion, and F-actin polymerization. Co-immunoprecipitation assays revealed that ELMO2 interacted with Gαi2 and that CXCL12 triggered Gα i2-dependent membrane translocation of ELMO2. Thus, ELMO2 is a potential therapeutic target for pancreatic cancer.

scholarly journals Density-dependent migration characteristics of cancer cells driven by pseudopod coordination

2021 ◽  
Author(s):  
Gerhard A Burger ◽  
Bob van de Water ◽  
Sylvia E Le Dévédec ◽  
Joost B Beltman
Keyword(s):  
Cell Migration ◽  
Cancer Cells ◽  
Single Cells ◽  
Cluster Formation ◽  
Time Lapse ◽  
Imaging Data ◽  
Cellular Potts Model ◽  
Primary Tumors ◽  
Density Dependent ◽  
Strong Cluster

The ability of cancer cells to invade neighboring tissue from primary tumors is an important determinant of metastatic behavior. Quantification of cell migration characteristics such as migration speed and persistence helps to understand the requirements for such invasiveness. One factor that may influence invasion is how local tumor cell density shapes cell migration characteristics, which we here investigate with a combined experimental and computational modeling approach. First, we generated and analyzed time-lapse imaging data on two aggressive Triple-Negative Breast Cancer (TNBC) cell lines, HCC38 and Hs578T, during 2D migration assays at various cell densities. HCC38 cells exhibited a counter-intuitive increase in speed and persistence with increasing density, whereas Hs578T did not exhibit such an increase. Moreover, HCC38 cells exhibited strong cluster formation with active pseudopod-driven migration, especially at low densities, whereas Hs578T cells maintained a dispersed positioning. In order to obtain a mechanistic understanding of the density-dependent cell migration characteristics and cluster formation, we developed realistic spatial simulations using a Cellular Potts Model (CPM) with an explicit description of pseudopod dynamics. Model analysis demonstrated that strong coordination between pseudopods within single cells could explain the experimentally observed increase in speed and persistence with increasing density in HCC38 cells. Thus, the density-dependent migratory behavior could be an emergent property of single-cell characteristics without the need for additional mechanisms. This implies that coordination amongst pseudopods may play a role in the aggressive nature of cancers through mediating dispersal.

A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration

2019 ◽  
Vol 19 (25) ◽  
pp. 2271-2282 ◽  
Author(s):  
Bo Lu ◽  
Xue-Hui Liu ◽  
Si-Ming Liao ◽  
Zhi-Long Lu ◽  
Dong Chen ◽  
...  
Keyword(s):  
Cell Migration ◽  
Intermolecular Interactions ◽  
Mammalian Cells ◽  
Molecular Mechanisms ◽  
Intramolecular Interaction ◽  
Polysialic Acid ◽  
Tumor Cell Migration ◽  
Neural Cell Adhesion ◽  
Polybasic Domains ◽  
Novel Model

Polysialic acid (polySia) is a novel glycan that posttranslationally modifies neural cell adhesion molecules (NCAMs) in mammalian cells. Up-regulation of polySia-NCAM expression or NCAM polysialylation is associated with tumor cell migration and progression in many metastatic cancers and neurocognition. It has been known that two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST), can catalyze polysialylation of NCAM, and two polybasic domains, polybasic region (PBR) and polysialyltransferase domain (PSTD) in polySTs play key roles in affecting polyST activity or NCAM polysialylation. However, the molecular mechanisms of NCAM polysialylation and cell migration are still not entirely clear. In this minireview, the recent research results about the intermolecular interactions between the PBR and NCAM, the PSTD and cytidine monophosphate-sialic acid (CMP-Sia), the PSTD and polySia, and as well as the intramolecular interaction between the PBR and the PSTD within the polyST, are summarized. Based on these cooperative interactions, we have built a novel model of NCAM polysialylation and cell migration mechanisms, which may be helpful to design and develop new polysialyltransferase inhibitors.

scholarly journals sxtA4+ and sxtA4- Genotypes Occur Together within Natural Pyrodinium bahamense Sub-Populations from the Western Atlantic

2021 ◽  
Vol 9 (6) ◽  
pp. 1128
Author(s):  
Kathleen Cusick ◽  
Gabriel Duran
Keyword(s):  
Molecular Mechanisms ◽  
Harmful Algal Bloom ◽  
Single Cells ◽  
Natural Populations ◽  
Indian River Lagoon ◽  
Toxin Production ◽  
Genotype Frequency ◽  
Rrna Gene ◽  
Western Atlantic ◽  
Pyrodinium Bahamense

Saxitoxin (STX) is a secondary metabolite and potent neurotoxin produced by several genera of harmful algal bloom (HAB) marine dinoflagellates. The basis for variability in STX production within natural bloom populations is undefined as both toxic and non-toxic strains (of the same species) have been isolated from the same geographic locations. Pyrodinium bahamense is a STX-producing bioluminescent dinoflagellate that blooms along the east coast of Florida as well as the bioluminescent bays in Puerto Rico (PR), though no toxicity reports exist for PR populations. The core genes in the dinoflagellate STX biosynthetic pathway have been identified, and the sxtA4 gene is essential for toxin production. Using sxtA4 as a molecular proxy for the genetic capacity of STX production, we examined sxtA4+ and sxtA4- genotype frequency at the single cell level in P. bahamense populations from different locations in the Indian River Lagoon (IRL), FL, and Mosquito Bay (MB), a bioluminescent bay in PR. Multiplex PCR was performed on individual cells with Pyrodinium-specific primers targeting the 18S rRNA gene and sxtA4. The results reveal that within discrete natural populations of P. bahamense, both sxtA4+ and sxtA4- genotypes occur, and the sxtA4+ genotype dominates. In the IRL, the frequency of the sxtA4+ genotype ranged from ca. 80–100%. In MB, sxtA4+ genotype frequency ranged from ca 40–66%. To assess the extent of sxtA4 variation within individual cells, sxtA4 amplicons from single cells representative of the different sampling sites were cloned and sequenced. Overall, two variants were consistently obtained, one of which is likely a pseudogene based on alignment with cDNA sequences. These are the first data demonstrating the existence of both genotypes in natural P. bahamense sub-populations, as well as sxtA4 presence in P. bahamense from PR. These results provide insights on underlying genetic factors influencing the potential for toxin variability among natural sub-populations of HAB species and highlight the need to study the genetic diversity within HAB sub-populations at a fine level in order to identify the molecular mechanisms driving HAB evolution.

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.

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