Cell shape on micro-patterned adhesive substrates

Bischofs, Ilka B.; Lehnert, D.; Klein, Friederike; Bastmeyer, Martin; Schwarz, Ulrich S.

doi:10.1016/s0021-9290(06)84606-3

Cited by 2 publications

(6 citation statements)

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“…In particular, we showed that low concentrations of blebbistatin, which allow for cell spreading and SF formation, decreased the line tension of cell spreading edges, but did not alter the edge bundle rigidity and the surface tension in a detectable manner. This is in agreement with earlier results that showed that peripheral SFs are more susceptible to blebbistatin treatment than the cell cortex (Bischofs et al, 2008;Labouesse et al, 2015;Tabdanov et al, 2018). In the future, our findings may be further expanded by creating a model for predicting spreading in 3D fiber environments, in which we take into full consideration the typical spacing and angles between individual fibers in the fibrous environment.…”

Section: Discussionsupporting

confidence: 91%

“…To qualitatively visualize the average effect of blebbistatin compared to control cells, we overlaid the SF network architecture of all of the analyzed cells at time point t 2 (as shown in Figure 2). The average SF intensity of blebbistatin-treated cells spreading on the side pattern (Figure 3A) exhibited a more invaginated arc than control cells (Figure 3A, white arrowhead), in agreement with earlier results (Bischofs et al, 2008). Moreover, the SF network was not confined to the spreading edge as tightly as in control cells (white arrows).…”

Section: Blebbistatin Treatment Lowers the Line Tension Of Peripheral Sfssupporting

confidence: 90%

“…The corresponding elastic modulus is estimated by applying the tension-elasticity model (Bischofs et al, 2008) (see STAR Methods for more detail), which recently has been confirmed for cells in 3D scaffolds (Brand et al, 2017;Tabdanov et al, 2018). To calculate the elastic 1D modulus, we fitted circular arcs to the peripheral SFs of all analyzed cells and extracted the corresponding arc radii (Figures S2D and S2E).…”

Section: Cell Spreading Rate Depends On Pattern Geometry and Initial Adhesive Positionmentioning

confidence: 85%

“…We therefore repeated our experiments in the presence of 3 mM blebbistatin, an NMMII inhibitor (Figure S2A; Video S3). Application of blebbistatin in the usual dose range of 10-50 mM completely inhibited cell spreading and/or SF assembly (data not shown), requiring us to apply a much smaller dose (Bischofs et al, 2008;Aratyn-Schaus and Gardel, 2010;Pasapera et al, 2010;Aratyn-Schaus et al, 2011). Such low-dose blebbistatin treatments have previously been used to investigate actin flow on patterned cells (Kumar et al, 2014).…”

Section: Cells With Mild Blebbistatin Treatment Show Faster Spreading Kinetics and A Less-well-defined Actin Cytoskeletonmentioning

confidence: 98%

“…One important CPM parameter is the adhesion strength, which governs the ability of cells to spread on the micropatterns, and was chosen to be just strong enough to allow spreading (W = 10 nN/mm). Cell shape during spreading is determined by a balance between this adhesive energy and the surface tension, the simple line tension, and the elastic line tension (Bischofs et al, 2008;Albert and Schwarz, 2014, 2016a, 2016bBrand et al, 2017). The surface tension represents cortical contractility over the whole surface and was previously estimated to be approximately s = 0.7 mN/m for keratinocytes (Mertz et al, 2012).…”

Section: Cell Spreading Rate Depends On Pattern Geometry and Initial Adhesive Positionmentioning

confidence: 99%

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Extracellular Matrix Geometry and Initial Adhesive Position Determine Stress Fiber Network Organization during Cell Spreading

et al. 2019

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SUMMARY Three-dimensional matrices often contain highly structured adhesive tracks that require cells to turn corners and bridge non-adhesive areas. Here, we investigate these complex processes using micropatterned cell adhesive frames. Spreading kinetics on these matrices depend strongly on initial adhesive position and are predicted by a cellular Potts model (CPM), which reflects a balance between adhesion and intracellular tension. As cells spread, new stress fibers (SFs) assemble periodically and parallel to the leading edge, with spatial intervals of ~2.5 mm, temporal intervals of ~15 min, and characteristic lifetimes of ~50 min. By incorporating these rules into the CPM, we can successfully predict SF network architecture. Moreover, we observe broadly similar behavior when we culture cells on arrays of discrete collagen fibers. Our findings show that ECM geometry and initial cell position strongly determine cell spreading and that cells encode a memory of their spreading history through SF network organization.

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Section: Discussionsupporting

confidence: 91%

Section: Blebbistatin Treatment Lowers the Line Tension Of Peripheral Sfssupporting

confidence: 90%

Section: Cell Spreading Rate Depends On Pattern Geometry and Initial Adhesive Positionmentioning

confidence: 85%

Section: Cells With Mild Blebbistatin Treatment Show Faster Spreading Kinetics and A Less-well-defined Actin Cytoskeletonmentioning

confidence: 98%

Section: Cell Spreading Rate Depends On Pattern Geometry and Initial Adhesive Positionmentioning

confidence: 99%

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Extracellular Matrix Geometry and Initial Adhesive Position Determine Stress Fiber Network Organization during Cell Spreading

et al. 2019

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SFAlab: image-based quantification of mechano-active ventral actin stress fibers in adherent cells

Mostert,

Grolleman,

van Turnhout

et al. 2023

Front. Cell Dev. Biol.

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Ventral actin stress fibers (SFs) are a subset of actin SFs that begin and terminate at focal adhesion (FA) complexes. Ventral SFs can transmit forces from and to the extracellular matrix and serve as a prominent mechanosensing and mechanotransduction machinery for cells. Therefore, quantitative analysis of ventral SFs can lead to deeper understanding of the dynamic mechanical interplay between cells and their extracellular matrix (mechanoreciprocity). However, the dynamic nature and organization of ventral SFs challenge their quantification, and current quantification tools mainly focus on all SFs present in cells and cannot discriminate between subsets. Here we present an image analysis-based computational toolbox, called SFAlab, to quantify the number of ventral SFs and the number of ventral SFs per FA, and provide spatial information about the locations of the identified ventral SFs. SFAlab is built as an all-in-one toolbox that besides analyzing ventral SFs also enables the identification and quantification of (the shape descriptors of) nuclei, cells, and FAs. We validated SFAlab for the quantification of ventral SFs in human fetal cardiac fibroblasts and demonstrated that SFAlab analysis i) yields accurate ventral SF detection in the presence of image imperfections often found in typical fluorescence microscopy images, and ii) is robust against user subjectivity and potential experimental artifacts. To demonstrate the usefulness of SFAlab in mechanobiology research, we modulated actin polymerization and showed that inhibition of Rho kinase led to a significant decrease in ventral SF formation and the number of ventral SFs per FA, shedding light on the importance of the RhoA pathway specifically in ventral SF formation. We present SFAlab as a powerful open source, easy to use image-based analytical tool to increase our understanding of mechanoreciprocity in adherent cells.

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Cell shape on micro-patterned adhesive substrates

Cited by 2 publications

References 0 publications

Extracellular Matrix Geometry and Initial Adhesive Position Determine Stress Fiber Network Organization during Cell Spreading

Extracellular Matrix Geometry and Initial Adhesive Position Determine Stress Fiber Network Organization during Cell Spreading

SFAlab: image-based quantification of mechano-active ventral actin stress fibers in adherent cells

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