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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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Quantification of cell–cell force exchange in a 6-cell cluster with changing topology.(A) Image of an E-cadherin-GFP-expressing 6-cell cluster with ‘tree-like’ topology, which permits the calculation of force exchanges at each cell–cell junction by both the force-balancing principle and the thin-plate FEM modeling. (B) Segmentation of cells in the cluster, overlaid on the traction force field (small colored vectors) and an inverted fluorescence image of the cell cluster. Longer vectors in cell centers indicate residual traction forces for individual cells. Cell–cell stresses (white arrows) were calculated from inverted traction forces. (C) Graphical network representation of the cluster. Dashed arrows at graph edge midpoints indicate the cell–cell force vector obtained from the force-balancing principle. Solid arrows of the same color show the corresponding cell–cell force vector derived from the FEM. (D–F) The same cluster as (A–C) at a different time point, when two new junctions existed between cell 1 and cell 3, and cell 1 and cell 4, resulting in a loop topology. Cell–cell forces at junctions 1, 2, 3, 6, and 7 can no longer be derived based on the force-balancing principle. See also Video 3.DOI:http://dx.doi.org/10.7554/eLife.03282.006
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fig3s1: Quantification of cell–cell force exchange in a 6-cell cluster with changing topology.(A) Image of an E-cadherin-GFP-expressing 6-cell cluster with ‘tree-like’ topology, which permits the calculation of force exchanges at each cell–cell junction by both the force-balancing principle and the thin-plate FEM modeling. (B) Segmentation of cells in the cluster, overlaid on the traction force field (small colored vectors) and an inverted fluorescence image of the cell cluster. Longer vectors in cell centers indicate residual traction forces for individual cells. Cell–cell stresses (white arrows) were calculated from inverted traction forces. (C) Graphical network representation of the cluster. Dashed arrows at graph edge midpoints indicate the cell–cell force vector obtained from the force-balancing principle. Solid arrows of the same color show the corresponding cell–cell force vector derived from the FEM. (D–F) The same cluster as (A–C) at a different time point, when two new junctions existed between cell 1 and cell 3, and cell 1 and cell 4, resulting in a loop topology. Cell–cell forces at junctions 1, 2, 3, 6, and 7 can no longer be derived based on the force-balancing principle. See also Video 3.DOI:http://dx.doi.org/10.7554/eLife.03282.006

Mentions: We tested the validity of the thin-plate model in cell clusters with a ‘tree-like’ topology, where the force exchange at cell–cell interfaces could be determined both by the force-balancing approach and integration of the FEM-predicted stress profile along the same interface (Figure 1). Our analyses indicated that both approaches yielded consistent results; the error for interface force calculations by the FEM approach is comparable to the error we found for force calculations by the force balancing principle alone (Figure 2). This implies that the inaccuracy in FEM-predicted forces arises from the same sources of error as the inaccuracy in force balance-predicted forces, which are uncertainties in the traction force reconstruction. Thus, neither the simplifying approximation of the cell cluster by a homogeneous thin-plate nor the numerical solution of the model introduced substantial error when predicting cell–cell forces in ‘tree-like’ topologies. Although both the force-balancing-principle approach and the FEM approach appeared to have similar accuracy in determining cell–cell forces, application of the thin-plate model permits the analysis of force exchange in clusters that change between a ‘tree-like’ and a ‘loop’ topology (Figure 3C and Figure 3—figure supplement 1B vs Figure 3B and Figure 3—figure supplement 1A; Videos 2 and 3) and is thus a more generalized approach to quantify cell–cell force transmission.Video 2.Force exchanges in a three-cell MCF10A cluster with changing topology; related to Figure 3.


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

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

Quantification of cell–cell force exchange in a 6-cell cluster with changing topology.(A) Image of an E-cadherin-GFP-expressing 6-cell cluster with ‘tree-like’ topology, which permits the calculation of force exchanges at each cell–cell junction by both the force-balancing principle and the thin-plate FEM modeling. (B) Segmentation of cells in the cluster, overlaid on the traction force field (small colored vectors) and an inverted fluorescence image of the cell cluster. Longer vectors in cell centers indicate residual traction forces for individual cells. Cell–cell stresses (white arrows) were calculated from inverted traction forces. (C) Graphical network representation of the cluster. Dashed arrows at graph edge midpoints indicate the cell–cell force vector obtained from the force-balancing principle. Solid arrows of the same color show the corresponding cell–cell force vector derived from the FEM. (D–F) The same cluster as (A–C) at a different time point, when two new junctions existed between cell 1 and cell 3, and cell 1 and cell 4, resulting in a loop topology. Cell–cell forces at junctions 1, 2, 3, 6, and 7 can no longer be derived based on the force-balancing principle. See also Video 3.DOI:http://dx.doi.org/10.7554/eLife.03282.006
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
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fig3s1: Quantification of cell–cell force exchange in a 6-cell cluster with changing topology.(A) Image of an E-cadherin-GFP-expressing 6-cell cluster with ‘tree-like’ topology, which permits the calculation of force exchanges at each cell–cell junction by both the force-balancing principle and the thin-plate FEM modeling. (B) Segmentation of cells in the cluster, overlaid on the traction force field (small colored vectors) and an inverted fluorescence image of the cell cluster. Longer vectors in cell centers indicate residual traction forces for individual cells. Cell–cell stresses (white arrows) were calculated from inverted traction forces. (C) Graphical network representation of the cluster. Dashed arrows at graph edge midpoints indicate the cell–cell force vector obtained from the force-balancing principle. Solid arrows of the same color show the corresponding cell–cell force vector derived from the FEM. (D–F) The same cluster as (A–C) at a different time point, when two new junctions existed between cell 1 and cell 3, and cell 1 and cell 4, resulting in a loop topology. Cell–cell forces at junctions 1, 2, 3, 6, and 7 can no longer be derived based on the force-balancing principle. See also Video 3.DOI:http://dx.doi.org/10.7554/eLife.03282.006
Mentions: We tested the validity of the thin-plate model in cell clusters with a ‘tree-like’ topology, where the force exchange at cell–cell interfaces could be determined both by the force-balancing approach and integration of the FEM-predicted stress profile along the same interface (Figure 1). Our analyses indicated that both approaches yielded consistent results; the error for interface force calculations by the FEM approach is comparable to the error we found for force calculations by the force balancing principle alone (Figure 2). This implies that the inaccuracy in FEM-predicted forces arises from the same sources of error as the inaccuracy in force balance-predicted forces, which are uncertainties in the traction force reconstruction. Thus, neither the simplifying approximation of the cell cluster by a homogeneous thin-plate nor the numerical solution of the model introduced substantial error when predicting cell–cell forces in ‘tree-like’ topologies. Although both the force-balancing-principle approach and the FEM approach appeared to have similar accuracy in determining cell–cell forces, application of the thin-plate model permits the analysis of force exchange in clusters that change between a ‘tree-like’ and a ‘loop’ topology (Figure 3C and Figure 3—figure supplement 1B vs Figure 3B and Figure 3—figure supplement 1A; Videos 2 and 3) and is thus a more generalized approach to quantify cell–cell force transmission.Video 2.Force exchanges in a three-cell MCF10A cluster with changing topology; related to Figure 3.

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