Spatiotemporal force and motion in collective cell migration

Saraswathibhatla, Aashrith; Galles, Emmett E.; Notbohm, Jacob

doi:10.1038/s41597-020-0540-5

Cited by 21 publications

(28 citation statements)

References 38 publications

(80 reference statements)

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“…Polyacrylamide substrates were prepared for traction force microscopy as described above but with the addition of 0.2 µm fluorescent particles (Dark Red 660/680, Fluospheres, Thermo Fisher Scientific). During gel polymerization, the gels were centrifuged upside down to localize the particles to the top as described in our prior work 57 , 58 . The traction experiments were performed with the cells expressing red fluorescent protein in their nuclei.…”

Section: Methodsmentioning

confidence: 99%

Effect of substrate stiffness on friction in collective cell migration

Vazquez

Saraswathibhatla

Notbohm

2022

Sci Rep

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In collective cell migration, the motion results from forces produced by each cell and transmitted to the neighboring cells and to the substrate. Because inertia is negligible and the migration occurs over long time scales, the cell layer exhibits viscous behavior, where force and motion are connected by an apparent friction that results from the breaking and forming of adhesive bonds at the cell–cell and cell–substrate interfaces. Most theoretical models for collective migration include an apparent friction to connect force and motion, with many models making predictions that depend on the ratio of cell–cell and cell–substrate friction. However, little is known about factors that affect friction, leaving predictions of many theoretical models untested. Here, we considered how substrate stiffness and the number of adhesions affected friction at the cell–substrate interface. The experimental data were interpreted through prior theoretical models, which led to the same conclusion, that increased substrate stiffness increased the number of cell–substrate adhesions and caused increased cell–substrate friction. In turn, the friction affected the collective migration by altering the curvature at the edge of the cell layer. By revealing underlying factors affecting friction and demonstrating how friction perturbs the collective migration, this work provides experimental evidence supporting prior theoretical models and motivates the study of other ways to alter the collective migration by changing friction.

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Section: Methodsmentioning

confidence: 99%

Effect of substrate stiffness on friction in collective cell migration

Vazquez

Saraswathibhatla

Notbohm

2022

Sci Rep

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“…An alternative explanation is that the treatments affected pack size by altering the distance over which cell-cell forces propagate. To consider this explanation, we quantified propagation of tensile stresses in the monolayer by using monolayer stress microscopy [24,51,52] and computing an autocorrelation. Results showed that the correlation length of tension was not statistically affected by treatment with JSP (Supplemental Fig.…”

Section: Resultsmentioning

confidence: 99%

Coordinated tractions increase the size of a collectively moving pack in a cell monolayer

Saraswathibhatla

Henkes

Galles

et al. 2021

Extreme Mechanics Letters

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“…To examine the effects of 2D-packing on cell geometry, we used a dataset where the biophysical dynamics of collective migration were studied on confined PolyDiMethylSiloxane (PDMS) islands 24 . Data were extracted for MDCK cells subject to three experimental setups viz ., cytochalasin ‘D’ treatment (CytoD), high cell density (High) and low cell density (Low).…”

Section: Resultsmentioning

confidence: 99%

“…Unlike published studies, our pipeline can be applied not only to scratch assay but also data from confluent monolayers and individual cells. The Saraswathibhatla et al ., and Zaritsky et al ., datasets were two such distinct studies which upon CGF analysis allowed us to speculate the role of 2D-packing on migratory heterogeneity 24,25 . While we cannot ignore the cell and experimental system specific effects, these trends between migratory subsets do recapitulate jamming-unjamming transitions which are reported during tissue development and disease progression 8,39,40 .…”

Section: Discussionmentioning

confidence: 99%

“…Label-free time-lapse imaging data acquired with phase-contrast microscopy were downloaded from published studies 16,24–26 and processed with Fiji software (https://imagej.net/Fiji/Downloads) as previously described 12 . Briefly, images from individual datasets were converted into an 8-bit format, adjusted for contrast and threshold, and analysed with the ‘Analyze Particles’ tool and ‘MTrack2’ plugin in Fiji.…”

Section: Methodsmentioning

confidence: 99%

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Cell Geometry Distinguishes Migration-Associated Heterogeneity in Two-Dimensional Systems

Varankar

Hari

Bapat

et al. 2021

Preprint

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Background: In vitro migration assays are a cornerstone of cell biology and have found extensive utility in research. Over the past decade, several variations of the two-dimensional (2D) migration assay have improved our understanding of this fundamental process. However, the ability of these approaches to capture the functional heterogeneity during migration and their accessibility to inexperienced users has been limited. Methods: We downloaded published time-lapse 2D cell migration datasets and subjected them to feature extraction with the Fiji software. We used the 'Analyze Particles' tool to extract ten cell geometry features (CGFs), which were grouped into 'shape, 'size and 'position' descriptors. Next, we defined the migratory status of cells using the 'MTrack2' plugin. All data obtained from Fiji were further subjected to rigorous statistical analysis with R version 4.0.2. Results: We observed consistent associative trends between size and shape descriptors and validated the robustness of our observations across four independent datasets. We used these descriptors to resolve the functional heterogeneity during migration by identifying and characterizing 'non-migrators (NM)' and 'migrators (M)'. Statistical analysis allowed us to identify considerable heterogeneity in the NM subset, that has not been previously reported. Interestingly, differences in 2D-packing appeared to affect CGF trends and heterogeneity of the migratory subsets for the datasets under investigation. Conclusion: We developed an analytical pipeline using open source tools, to identify and morphologically characterize functional migratory subsets from label-free, time-lapse migration data. Our quantitative approach identified a previously unappreciated heterogeneity of non-migratory cells and predicted the influence of 2D-packing on migration.

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Spatiotemporal force and motion in collective cell migration

Cited by 21 publications

References 38 publications

Effect of substrate stiffness on friction in collective cell migration

Effect of substrate stiffness on friction in collective cell migration

Coordinated tractions increase the size of a collectively moving pack in a cell monolayer

Cell Geometry Distinguishes Migration-Associated Heterogeneity in Two-Dimensional Systems

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