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Mapping the dynamics of force transduction at cell-cell junctions of epithelial clusters.

Ng MR, Besser A, Brugge JS, Danuser G - Elife (2014)

Bottom Line: We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters.Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell–cell junctions.Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Biology, Harvard Medical School, Boston, United States.

ABSTRACT
Force transduction at cell–cell adhesions regulates tissue development, maintenance and adaptation. We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters. Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell–cell junctions. At the multi-cellular scale, cell–cell force exchange depended on the cell position within a cluster, and was adaptive to reconfigurations due to cell divisions or positional rearrangements. Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors. These data provide insights into mechanisms that could control mechanical stress homeostasis in dynamic epithelial tissues, and highlight our methods as a resource for the study of mechanotransduction in cell–cell adhesions [corrected].

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Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).(A) Comparison of cell–cell force magnitudes as measured by the force balancing method (blue,  is calculated from Equation 5) or FEM (red, ) vs the two independent measurements at each interface as predicted by force balancing calculations (= or ). Deviations of individual data from the dashed line indicate measurement errors. (B) Angular deviations between cell–cell forces as measured by the force balancing method (blue, ) or the FEM (red, ) and the two independent measurements at each interface as predicted by the force balancing calculations () (outliers (<3% of all data points) with angular deviations >90 degrees are not shown in the plot). (C) Relative error in cell–cell force measurements by the force balancing method (blue, ) or the FEM method (red, ). The median relative error for both measurement methods is 14% (outliers >100% relative error (<7% of all data points) are considered in the median calculation but are not shown in the plot). n = total number of measurements pooled from N distinct cell–cell junctions, with each junction having been measured over multiple time points.DOI:http://dx.doi.org/10.7554/eLife.03282.004
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fig2: Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).(A) Comparison of cell–cell force magnitudes as measured by the force balancing method (blue, is calculated from Equation 5) or FEM (red, ) vs the two independent measurements at each interface as predicted by force balancing calculations (= or ). Deviations of individual data from the dashed line indicate measurement errors. (B) Angular deviations between cell–cell forces as measured by the force balancing method (blue, ) or the FEM (red, ) and the two independent measurements at each interface as predicted by the force balancing calculations () (outliers (<3% of all data points) with angular deviations >90 degrees are not shown in the plot). (C) Relative error in cell–cell force measurements by the force balancing method (blue, ) or the FEM method (red, ). The median relative error for both measurement methods is 14% (outliers >100% relative error (<7% of all data points) are considered in the median calculation but are not shown in the plot). n = total number of measurements pooled from N distinct cell–cell junctions, with each junction having been measured over multiple time points.DOI:http://dx.doi.org/10.7554/eLife.03282.004

Mentions: Whereas previous studies examined cell clusters with two or at most three cells in a linear configuration (Liu et al., 2010; Maruthamuthu et al., 2011; McCain et al., 2012), the force balancing principle readily expands to the calculation of cell–cell forces in larger cell clusters with linear or ‘tree-like’ topologies (Figure 1). To determine the neighborhood topology of cells, we defined a cell cluster as a graphical network, where each cell is represented as a node and each junction between two cells is represented by an edge connecting two nodes of the network. In a ‘tree-like’ topology, removal of any of the graphical edges results in two completely disjointed sub-networks. In this case, the forces at any cell–cell interface can be determined by calculating the residual forces over the cellular footprints defined by the two sub-networks (Figure 1; for details, see ‘The force-balancing principle and its application to larger cell clusters’ in ‘Materials and methods’ section). Statistical analyses of our experimental data indicate that the median error of force calculations based on the force-balancing principle was ∼14% of the expected force magnitudes (Figure 2).10.7554/eLife.03282.004Figure 2.Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).


Mapping the dynamics of force transduction at cell-cell junctions of epithelial clusters.

Ng MR, Besser A, Brugge JS, Danuser G - Elife (2014)

Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).(A) Comparison of cell–cell force magnitudes as measured by the force balancing method (blue,  is calculated from Equation 5) or FEM (red, ) vs the two independent measurements at each interface as predicted by force balancing calculations (= or ). Deviations of individual data from the dashed line indicate measurement errors. (B) Angular deviations between cell–cell forces as measured by the force balancing method (blue, ) or the FEM (red, ) and the two independent measurements at each interface as predicted by the force balancing calculations () (outliers (<3% of all data points) with angular deviations >90 degrees are not shown in the plot). (C) Relative error in cell–cell force measurements by the force balancing method (blue, ) or the FEM method (red, ). The median relative error for both measurement methods is 14% (outliers >100% relative error (<7% of all data points) are considered in the median calculation but are not shown in the plot). n = total number of measurements pooled from N distinct cell–cell junctions, with each junction having been measured over multiple time points.DOI:http://dx.doi.org/10.7554/eLife.03282.004
© Copyright Policy
Related In: Results  -  Collection

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fig2: Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).(A) Comparison of cell–cell force magnitudes as measured by the force balancing method (blue, is calculated from Equation 5) or FEM (red, ) vs the two independent measurements at each interface as predicted by force balancing calculations (= or ). Deviations of individual data from the dashed line indicate measurement errors. (B) Angular deviations between cell–cell forces as measured by the force balancing method (blue, ) or the FEM (red, ) and the two independent measurements at each interface as predicted by the force balancing calculations () (outliers (<3% of all data points) with angular deviations >90 degrees are not shown in the plot). (C) Relative error in cell–cell force measurements by the force balancing method (blue, ) or the FEM method (red, ). The median relative error for both measurement methods is 14% (outliers >100% relative error (<7% of all data points) are considered in the median calculation but are not shown in the plot). n = total number of measurements pooled from N distinct cell–cell junctions, with each junction having been measured over multiple time points.DOI:http://dx.doi.org/10.7554/eLife.03282.004
Mentions: Whereas previous studies examined cell clusters with two or at most three cells in a linear configuration (Liu et al., 2010; Maruthamuthu et al., 2011; McCain et al., 2012), the force balancing principle readily expands to the calculation of cell–cell forces in larger cell clusters with linear or ‘tree-like’ topologies (Figure 1). To determine the neighborhood topology of cells, we defined a cell cluster as a graphical network, where each cell is represented as a node and each junction between two cells is represented by an edge connecting two nodes of the network. In a ‘tree-like’ topology, removal of any of the graphical edges results in two completely disjointed sub-networks. In this case, the forces at any cell–cell interface can be determined by calculating the residual forces over the cellular footprints defined by the two sub-networks (Figure 1; for details, see ‘The force-balancing principle and its application to larger cell clusters’ in ‘Materials and methods’ section). Statistical analyses of our experimental data indicate that the median error of force calculations based on the force-balancing principle was ∼14% of the expected force magnitudes (Figure 2).10.7554/eLife.03282.004Figure 2.Comparison of cell–cell force calculations by force-balancing principle and by finite element modeling (FEM).

Bottom Line: We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters.Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell–cell junctions.Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Biology, Harvard Medical School, Boston, United States.

ABSTRACT
Force transduction at cell–cell adhesions regulates tissue development, maintenance and adaptation. We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters. Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell–cell junctions. At the multi-cellular scale, cell–cell force exchange depended on the cell position within a cluster, and was adaptive to reconfigurations due to cell divisions or positional rearrangements. Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors. These data provide insights into mechanisms that could control mechanical stress homeostasis in dynamic epithelial tissues, and highlight our methods as a resource for the study of mechanotransduction in cell–cell adhesions [corrected].

Show MeSH
Related in: MedlinePlus