Mechanical Feedback through E-Cadherin Promotes Direction Sensing during Collective Cell Migration

Cai, Danfeng; Chen, Shann Ching; Prasad, Mohit; He, Li; Wang, Xiaobo; Choesmel-Cadamuro, Valérie; Sawyer, Jessica K.; Danuser, Gaudenz; Montell, Denise J.

doi:10.1016/j.cell.2014.03.045

Cited by 451 publications

(528 citation statements)

References 48 publications

Supporting

Mentioning

483

Contrasting

Unclassified

Order By: Relevance

“…2A, square). To obtain even smaller clusters, we knocked down E-cadherin specifically in central nonmotile polar cells, which causes clusters to break apart (29). Compared with other methods that generate smaller border cell clusters (34,35), this method does not directly alter the migrating cells themselves, thus presumably minimally changing their properties, and the smaller clusters generated are able to migrate.…”

Section: Resultsmentioning

confidence: 99%

“…Cells move in groups of diverse sizes and varying arrangements through equally complex microenvironments. The border cells represent a clear example of how collective movement can enhance direction sensing (29) and how the combined chemical and physical properties of the microenvironment influences the optimal cluster size. The results presented here therefore lead us to propose that the details of the diverse physical and chemical microenvironments likely exert a strong influence on the observed sizes and arrangements of collectively migrating cells in vivo.…”

Section: Discussionmentioning

confidence: 99%

“…SlboGal4, UAS-dsRedNLS; UASmoesinGFP, and slbo-Lifeact-GFP flies were used for live imaging and were described before (26,29). UAS-PVR DN , UAS-EGFR DN , and UAS-EcadRNAi (VDRC: KK103962) were described previously (23,24,26,29).…”

Section: Methodsmentioning

confidence: 99%

“…Larger clusters move at a higher velocity in a chemical gradient, due to their ability to sense the gradient over a larger length scale. Note that we disregard internal motions and dissipation due to friction forces between the cells of the cluster, because we are interested in the cluster motion as a whole, and recent data suggest that the cluster behaves as a multicellular unit (29). Such motions are observed to be small, as the border cells strongly adhere to the core polar cells (29).…”

Section: Theoretical Modelmentioning

confidence: 99%

See 3 more Smart Citations

Modeling and analysis of collective cell migration in an in vivo three-dimensional environment

Cai

Dai

Prasad

et al. 2016

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

Self Cite

View full text Add to dashboard Cite

A long-standing question in collective cell migration has been what might be the relative advantage of forming a cluster over migrating individually. Does an increase in the size of a collectively migrating group of cells enable them to sample the chemical gradient over a greater distance because the difference between front and rear of a cluster would be greater than for single cells? We combined theoretical modeling with experiments to study collective migration of the border cells in-between nurse cells in the Drosophila egg chamber. We discovered that cluster size is positively correlated with migration speed, up to a particular point above which speed plummets. This may be due to the effect of viscous drag from surrounding nurse cells together with confinement of all of the cells within a stiff extracellular matrix. The model predicts no relationship between cluster size and velocity for cells moving on a flat surface, in contrast to movement within a 3D environment. Our analyses also suggest that the overall chemoattractant profile in the egg chamber is likely to be exponential, with the highest concentration in the oocyte. These findings provide insights into collective chemotaxis by combining theoretical modeling with experimentation.cell migration | theoretical modeling | three-dimensional | chemotaxis

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Theoretical Modelmentioning

confidence: 99%

See 2 more Smart Citations

Modeling and analysis of collective cell migration in an in vivo three-dimensional environment

Cai

Dai

Prasad

et al. 2016

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…After their report was published, many laboratories applied TSMod to various molecules to visualize mechanical stress in living cells (63,64). In two representative examples, a tension-sensor targeting b-spectrin was applied to intravital imaging of Caenorhabditis elegans (65), and a tension sensor targeting E-cadherin was applied to Drosophila ovary imaging (66). However, application to higher-order animals such as mice has not yet succeeded.…”

Section: Visualization Of Physical Stresses In Vivomentioning

confidence: 99%

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

Hirata

Kiyokawa

2016

Biophysical Journal

View full text Add to dashboard Cite

Fö rster (or fluorescence) resonance energy transfer (FRET) is a nonradiative energy transfer process between two fluorophores located in close proximity to each other. To date, a variety of biosensors based on the principle of FRET have been developed to monitor the activity of kinases, proteases, GTPases or lipid concentration in living cells. In addition, generation of biosensors that can monitor physical stresses such as mechanical power, heat, or electric/magnetic fields is also expected based on recent discoveries on the effects of these stressors on cell behavior. These biosensors can now be stably expressed in cells and mice by transposon technologies. In addition, two-photon excitation microscopy can be used to detect the activities or concentrations of bioactive molecules in vivo. In the future, more sophisticated techniques for image acquisition and quantitative analysis will be needed to obtain more precise FRET signals in spatiotemporal dimensions. Improvement of tissue/organ position fixation methods for mouse imaging is the first step toward effective image acquisition. Progress in the development of fluorescent proteins that can be excited with longer wavelength should be applied to FRET biosensors to obtain deeper structures. The development of computational programs that can separately quantify signals from single cells embedded in complicated three-dimensional environments is also expected. Along with the progress in these methodologies, two-photon excitation intravital FRET microscopy will be a powerful and valuable tool for the comprehensive understanding of biomedical phenomena.Since the discovery of green fluorescent protein (GFP) (1), scientists have been widely employing this gene-encoded fluorescent protein (FP) to investigate the spatiotemporal dynamics of molecules with subcellular resolution. One of the applications of FP engineering is the development of biosensors based on the principle of Förster (or fluorescence) resonance energy transfer (FRET) (2). FRET is a nonradiative energy transfer process between two fluorophores located in close proximity to each other, and its efficiency is strongly dependent on the distance between the fluorophores. More precisely, the energy transfer rate (k t ) from a donor to an acceptor fluorophore is calculated in the following Förster's equation;where J is the overlap of donor emission and acceptor excitation spectra, k 2 is an orientation factor of transition moment (a factor determined by the relative orientation of the two fluorophores), n is a refractive index, R is the distance between the donor and acceptor fluorophores, and k f is the donor fluorescence emission speed. Therefore, FRET efficiency is determined by the distance and orientation of the two fluorophores. To measure FRET efficiency, there are roughly two methods; ratiometric analysis and lifetime analysis. Ratiometric analysis utilizes fluorescence intensity of an acceptor (e.g., yellow FP (YFP)) and a donor (e.g., cyan FP (CFP)) upon the donor excitation. Because accept...

show abstract

Collective Cell Migration in Neural Crest Development

Théveneau

Andrieu

2015

Encyclopedia of Life Sciences

View full text Add to dashboard Cite

The migration of multiple cells as a cooperative unit known as collective cell migration is a common phenomenon in development, cancer and healing. Cooperation can be implemented by physical and/or chemical means and thus happens in epithelial as well as mesenchymal cell populations. Neural crest cells, a highly motile embryonic population, are a well‐known model for epithelial–mesenchymal transition and cell migration. Neural crest cells use various strategies to cooperate and migrate collectively which make them a good model for the study of collectiveness. Further, neural crest cells' interaction with other embryonic populations also relies on cell cooperation, thus providing a model for the study of cell cooperation during organogenesis. Key Concepts Neural crest cells are migratory multipotent stem cells. Neural crest cells distribute according to cell–cell and cell–environment interactions. Some neural crest cell populations migrate collectively. Collectiveness is based on cell–cell cooperation via paracrine chemotaxis and cell–cell adhesion. Collectiveness influences cell guidance. Cooperation takes place at several orders of magnitude: among neural crest cells and between neural crest cells and adjacent cell populations.

show abstract

Mechanical Feedback through E-Cadherin Promotes Direction Sensing during Collective Cell Migration

Cited by 451 publications

References 48 publications

Modeling and analysis of collective cell migration in an in vivo three-dimensional environment

Modeling and analysis of collective cell migration in an in vivo three-dimensional environment

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

Collective Cell Migration in Neural Crest Development

Contact Info

Product

Resources

About