This work was supported by the Connaught Fund New Investigator Award to S.P., Canada Foundation for Innovation, NSERC Discovery Grant Program (grants RGPIN-2015-05114 and RGPIN-2020-05881), University of Manchester and University of Toronto Joint Research Fund, and University of Toronto XSeed Program.

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The authors have nothing to disclose.

The described cell spreading assay allows for the continuous tracking of morphological changes (e.g., cell size and shape) and cell edge movements (i.e., protrusion speed and retraction frequency), which are features missing in most cell spreading protocols19,24. While commonly used end-point cell spreading assays allow for the determination of cell spreading speed, these assays fail to resolve the temporal dynamics of cell edge movements. The lack of temporal information limits the ability to detect and quantify changes in lamellipodial protrusion-retraction cycles.
Our image processing and analysis software performs a streamlined analysis of the spreading cells, from cell segmentation to data quantification. Manual image analyses of cell spreading usually involve a biased selection of a threshold value or applying an automated segmentation algorithm, which is not suited for high-throughput experiments where many images need to be analyzed. Our software is, therefore, designed to detect and segment spreading cells in an automated&#160;fashion, in addition to quantifying protrusion dynamics and morphological descriptors. Together, these features make the described protocol amenable for large-throughput screenings of signaling pathways and molecular players that regulate lamellipodia.
To ensure that the analysis of spreading cells is robust and accurate, a few critical steps in the protocol must be performed with extra caution. The first step of the cell spreading assay involves plating fluorescently-labeled cells at a very low density on a fibronectin-coated coverslip the day before imaging (Figure 1A-D). These polarized cells enable precise focusing of the spreading cells&#39; protruding edges during the image acquisition. If the density of polarized cells is too high, spreading cells have a high chance of landing on or overlapping with the polarized cells, which may lead to a cell segmentation failure. The recovery period post-trypsinization is another critical step in this protocol. Cells treated with the drug of interest, e.g., DMSO or CK-666, are detached from the cell culture dish by trypsin-EDTA (Step 2), followed by a recovery period of 45 mins (Figure 1E). This recovery step allows cells to recover from the proteolytic cleavage of cell surface proteins by trypsin19,24 and synchronizes the onset of cell spreading (Figure 2). If the recovery step is omitted, the cell-to-cell variability in cell spread area increases, reducing the consistency of the biological phenotype.
During the image acquisition, any sample drift inevitably decreases the quality and precision of cell spreading analysis, especially the kymograph analysis. To minimize sample drift, a few measures should be taken. First, the user should optimize the stage movement during the image acquisition. The optimization includes minimizing stage travel between fields of view and reducing the speed of stage movement. Second, it is essential to tightly secure the sample on the microscope stage. If these suggested measures do not eliminate sample drift, post-acquisition processing should be considered. Among many proprietary and open-source computational tools, we recommend using the &#34;Descriptor-based registration&#34; Fiji plugin to correct image shifts and align the movies of spreading cells (instructions can be found at: https://imagej.net/Descriptor-based_registration_(2d/3d)).
It should be noted that the quantitative analysis of cell areas and edge dynamics performed by the software depends heavily on the accuracy of cell segmentation. To ensure precise segmentation, we recommend visualizing cell spreading using a confocal imaging system, preferably a spinning disk confocal microscope which offers high resolution, low photobleaching/phototoxicity, and high signal-to-noise ratio. A confocal microscope efficiently removes out-of-focus fluorescence emitted by the spreading cells, which would otherwise decrease the image segmentation accuracy and cell boundary tracing. If a widefield microscope is used for image acquisition, additional post-acquisitional processing, e.g., image deconvolution, may be required to remove out-of-focus fluorescence and improve the accuracy of cell segmentation. Therefore, the choice of the imaging system should be considered.
Within the described software, two image segmentation algorithms were implemented and optimized to reliably detect cells labeled with dim to moderately bright fluorescent proteins, such as cytosolic green and red fluorescent proteins (GFP and RFP)26,27. However, these segmentation algorithms have a limited dynamic range and are not suitable for detecting cells labeled with extremely bright fluorescent proteins or dyes. In our hands, these algorithms tend to undersegment extremely bright cells due to the skewness of the image histogram towards high intensity pixels. For bright samples, the intensities of the images can be controlled by adjusting the exposure time or the output power of the excitation laser.
With these considerations in mind, this live-cell spreading protocol is a robust and powerful tool to study the dynamics of lamellipodia. The automated image analysis platform is suited to many biological investigations, e.g., high-content screening of molecular/signaling factors that regulate lamellipodial protrusions.

Lamellipodial protrusions are prominent cytoskeletal structures formed at the front of a migrating cell. In lamellipodia, polymerization of actin with the aid of the Arp2/3 complex and formins&#160;creates a fast-growing branched actin meshwork that pushes against the plasma membrane1,2. The pushing force generated by the actin meshwork physically propels the cell forward1,3,4,5. Depletion of the Arp2/3 complex or disruption of signaling pathways essential for lamellipodial protrusions often impair cell migration6, 7. Although migration of lamellipodia-deficient cells has also been reported8,9, the importance of lamellipodia in cell migration is evident as depletion of this protrusive structure perturbs the cell&#39;s ability to move through&#160;complex biological microenvironments6,10.
A major hindrance to understanding the regulation of lamellipodia in migrating cells is the natural variability in lamellipodial protrusion kinetics, size, and shape11,12,13,14. Furthermore, recent studies have demonstrated that lamellipodia exhibit complex protrusive behaviors, including fluctuating, periodic, and accelerating protrusions14,15. Compared to the highly variable lamellipodia of migrating cells6,16, lamellipodia formed during cell spreading are more uniform12. Since the protrusive activity of spreading and migrating cells is driven by identical macromolecular assemblies, which include a branched actin network, contractile actomyosin bundles, and integrin-based cell-matrix adhesions17,18, spreading cells have been widely used as a model for investigating the regulation of lamellipodia dynamics.
Cell spreading is a dynamic mechanochemical process where a cell in suspension first adheres to a substrate through integrin-based adhesions17,19,20 and then spreads by extending actin-based protrusions21,22,23. During the spreading phase, lamellipodia emanating from the cell body protrude isotropically and persistently with little to no retraction or stalling12. The most commonly used cell spreading protocols are endpoints assays, where spreading cells are fixed at various times after plating19,24. These assays, although quick and simple, are limited in their diagnostic power to detect changes in the dynamic features of lamellipodia. To determine the molecular mechanisms that control lamellipodia dynamics, the Sheetz group pioneered the use of quantitative analysis of live spreading cells and uncovered many fundamental properties of cell edge protrusions11,12,22. These studies have demonstrated that the live-cell spreading assay is a robust and powerful technique in the toolbox of a cell biology laboratory. Despite that, a detailed protocol and open-source computational tool for a live-cell spreading assay are currently unavailable for the cell biology community. To this end, our protocol outlines the procedures of imaging live spreading cells and provides an automated image analysis tool. To validate this method, we used Arp2/3 inhibition as an experimental treatment and showed that inhibiting the function of the Arp2/3 complex did not arrest cell spreading but caused a significant reduction in cell protrusion speed, as well as the stability of cell edge protrusions, giving rise to jagged cell edges. These data demonstrate that the combination of live-cell imaging and automated image analysis is a useful tool for analyzing cell edge dynamics and identifying molecular components that regulate lamellipodia.

<table><tbody><tr><td>0.05% Trypsin (0.05%), 0.53 mM EDTA</td><td>Wisent Bioproducts</td><td>325-042-CL</td><td></td></tr><tr><td>10.0 cm Petri Dish, Polystyrene, TC Treated, Vented</td><td>Starstedt</td><td>83.3902</td><td></td></tr><tr><td>15 mL High Clarity PP Centrifuge Tube, Conical Bottom, with Dome Seal Screw Cap, Sterile</td><td>Falcon</td><td>352097</td><td></td></tr><tr><td>1-Well Chamlide CMS for 22 mm x 22 mm Coverslip</td><td>Quorum Technologies</td><td>CM-S22-1</td><td></td></tr><tr><td>35 mm TC-treated Easy-Grip Style Cell Culture Dish</td><td>Falcon</td><td>353001</td><td></td></tr><tr><td>50 mL Centrifuge Tube, Transparent, Plug Seal</td><td>Nest</td><td>602002</td><td></td></tr><tr><td>6.0 cm Cell Culture Dishes Treated for Increased Cell Attachment, Sterile</td><td>VWR</td><td>10861-658</td><td></td></tr><tr><td>Arp2/3 Complex Inhibitor I, CK-666</td><td>Millipore Sigma</td><td>182515</td><td></td></tr><tr><td>Camera, Prime 95B-25MM</td><td>Photometrics</td><td></td><td></td></tr><tr><td>Dimethyl Sulfoxide, Sterile</td><td>BioShop</td><td>DMS666</td><td></td></tr><tr><td>DMEM, 1x, 4.5 g/L Glucose, with L-Glutamine, Sodium Pyruvate and Phenol Red</td><td>Wisent Bioproducts</td><td>319-005 CL</td><td></td></tr><tr><td>DMEM/F-12, HEPES, No Phenol Red</td><td>Gibco</td><td>11039021</td><td></td></tr><tr><td>D-PBS, 1X</td><td>Wisent Bioproducts</td><td>311-425 CL</td><td></td></tr><tr><td>Fetal Bovine Serum</td><td>Wisent Bioproducts</td><td>080-110</td><td></td></tr><tr><td>Fiji Software</td><td>ImageJ</td><td></td><td></td></tr><tr><td>HEPES (1 M)</td><td>Gibco</td><td>15630080</td><td></td></tr><tr><td>Human Plasma Fibronectin Purified Protein 1 mg</td><td>Millipore Sigma</td><td>FC010</td><td></td></tr><tr><td>Immersion Oil</td><td>Cargille</td><td>16241</td><td></td></tr><tr><td>L-Glutamine Solution (200 mM)</td><td>Wisent Bioproducts</td><td>609-065-EL</td><td></td></tr><tr><td>MEM Non-Essential Amino Acids Solution (100X)</td><td>Gibco</td><td>11140050</td><td></td></tr><tr><td>Micro Cover Glasses, Square, No. 11/2 22 x 22 mm</td><td>VWR</td><td>CA48366-227-1</td><td></td></tr><tr><td>Microscope Body, Eclipse Ti2-E</td><td>Nikon</td><td></td><td></td></tr><tr><td>Objective, CFI Plan Apo Lambda 60X Oil</td><td>Nikon</td><td>MRD01605</td><td></td></tr><tr><td>Penicillin-Streptomycin</td><td>Sigma</td><td>P4333</td><td></td></tr><tr><td>Spinning Disk, Crest Light V2</td><td>CrestOptics</td><td></td><td></td></tr><tr><td>Spyder</td><td>Anaconda</td><td></td><td></td></tr><tr><td>Stage top incubator</td><td>Tokai Hit</td><td></td><td></td></tr><tr><td>Statistics Software, Prism</td><td>GraphPad</td><td></td><td></td></tr><tr><td>Tweezers, Style 2</td><td>Electron Microscopy Sciences</td><td>78326-42</td><td></td></tr></tbody></table>

quantitative analysis of cell edge dynamics during cell spreading

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out shape. Following the cell-substrate attachment, the cell forms a thin sheet of lamellipodia emanating from the cell body. In the lamellipodia, globular actin (G-actin) monomers polymerize into a dense filamentous actin (F-actin) meshwork that pushes against the plasma membrane, thereby providing the mechanical forces required for the cell to spread. Notably, the molecular players that control the actin polymerization in lamellipodia are essential for many other cellular processes, such as cell migration and endocytosis. 
Since spreading cells form continuous lamellipodia that span the entire cell periphery and persistently expand outward, cell spreading assays have become an efficient tool to assess the kinetics of lamellipodial protrusions. Although several technical implementations of the cell spreading assay have been developed, a detailed description of the workflow, which would include both a step-by-step protocol and computational tools for data analysis, is currently lacking. Here, we describe the experimental procedures of the cell spreading assay and present an open-source tool for quantitative and unbiased analysis of cell edge dynamics during spreading. When combined with pharmacological manipulations and/or gene-silencing techniques, this protocol is amenable to a large-scale screen of molecular players regulating lamellipodial protrusions.

The above protocol describes the experimental procedures for the live-cell imaging of spreading cells and a computational tool for the quantitative analysis of cell spreading dynamics. The computational tool can be used in a low- or high-throughput format to identify the molecular players regulating the actin polymerization machinery at the cell leading edge.
The schematic representation of the experimental procedures is depicted in Figure 1. The cell spreading assay was performed on immortalized mouse embryo fibroblasts stably expressing the pleckstrin homology (PH) domain of the Akt protein kinase tagged with eGFP25. The cells were detached with trypsin-EDTA and were allowed to recover in suspension for 45 minutes. During the recovery step, cells replenished their integrin receptors on the plasma membrane as indicated by the fast and synchronous attachment of the recovered cells to the fibronectin coated coverslips (Figure 2). Without the recovery period, spreading cells exhibited a broad distribution of cell size indicating a high variability in the onset of cell spreading (Figure 2A and B). Next, cells were plated on a fiducially-marked coverslip and their spreading dynamics were visualized by spinning disk confocal microscopy (schematics shown in Figure 1A - H). Throughout the image acquisition, we considered fields of view that featured cells with a signal-to-noise ratio of 2.5 or above. This was an important consideration as the subsequent image segmentation is sensitive to the cells&#39; fluorescence intensity relative to the background. In our experiments, we acquired images every 6 seconds for 15 minutes (schematics shown in Figure 1I-J).&#160;In agreement with previous reports16, imaging at a 6 second frame rate ensured sufficient temporal resolution for capturing the dynamics of individual protrusion and retraction events, while allowing us to acquire several fields of view in parallel. The resulting time-lapse images were&#160;analyzed using the custom-build Python software (Figure 3).
An unbiased quantification of cell spreading was performed by using two distinct analytical procedures: (i) Morphodynamic profiling of spreading cells (Figure 3A, C and 4) and (ii) Kymograph analysis of cell edge dynamics (Figure 3B and 5). The analysis of cell spreading by morphodynamic profiling involves the automated detection of the spreading and fiducial cells in the field of view (Figure 3C left), followed by a frame-by-frame image segmentation and detection of the spreading cell boundary. The segmentation is performed by global intensity thresholding the individual frames. The threshold value is calculated as the local minimum between the first and second intensity modes on the image histogram26. Images with a unimodal, right-skewed histogram are segmented by the triangle thresholding algorithm27. Following cell segmentation, the morphodynamic characteristics of the spreading cells (i.e., cell area, aspect ratio, and cell circularity) were computed (Figure 3C right).
Consistent with published results12,28, cell spreading was driven by an isotropic expansion of lamellipodia as indicated by a sigmoidal shape on the representative cell area plot (Figure 3C right, blue curve and S1). The area plot showed that the cell area increased by approximately 3-fold before reaching a plateau (Figure 4A and B). Throughout the process of cell spreading, the cells remained circular (circularity = 0.70 &#177; 0.076) and displayed veil-like protruding cell edges, which are indicative of lamellipodial protrusions (Figure 4C).
To validate the cell spreading assay, we inhibited Arp2/3 with 100 &#181;M CK-666 for 1 hour and 45 minutes and assessed the effect of this treatment on the cell spreading dynamics. In agreement with previous reports13, the suppression of Arp2/3 activity did not result in a significant decrease in the cell spreading speed&#160;(Figure 4A and B, pink curve). However, cell shape analysis revealed a significant difference in the circularity of control and CK-666 treated cells (Control: 0.70 &#177; 0.08 vs. CK-666: 0.54 &#177; 0.09, p &#60; 0. 1 x 10-3) (Figure 4C). While the control cells remained circular until the plateau, Arp2/3-inhibited cells acquired a polygonal shape which was retained throughout the course of spreading (Figure 4A). Together, these experimental results demonstrate that the described cell spreading assay reveals moderate changes in cell morphodynamics caused by perturbations of the actin polymerization machinery.
While morphodynamic profiling is often sufficient to detect gross alterations in cell spreading dynamics, this analysis has limited ability to identify specific cytoskeletal components that regulate the protrusion-retraction cycles of the cell edge, prompting us to implement an unbiased Kymograph Analysis tool (Figure 5 left, dashed lines). The analysis of cell edge speed revealed a moderate but significant decrease in the average protrusion speed of Arp2/3-inhibited cells compared to control (Control: 37.1 &#177; 12.87 nm/s vs. CK-666: 28.7 &#177; 13.4 nm/s, p = 0. 9 x 10-3) (Figure 5C). Furthermore, dynamics of the cell edge of control and Arp2/3-inhibited cells were remarkably different (Figure 5A and D). The control cells protruded persistently with little to no retractions during the rapid expansion phase, which lasted about 200 seconds, and exhibited intermittent retractions during the plateau phase (Figure 5A and D). In contrast, the expansion of Arp2/3-inhibited cells was intervened by retraction events, denoted by the red dots on the graphs (Figure 5B and D). Quantification of retraction frequency showed that Arp2/3-inhibited cells retracted 26% more frequently than control cells (Control: 0.18 &#177; 0.22 s-1 vs. CK-666: 0.24 &#177; 0.19 s-1, p = 0.03)&#160;(Figure 5D). These data demonstrate the high sensitivity of the kymograph analysis in detecting mild alterations in lamellipodial dynamics.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62369/62369fig1v2.jpg" /> 
Figure 1: The experimental workflow of a cell spreading assay. (A - H) Schematics of the cell spreading assay. (A) A 22 mm x 22 mm coverslip is coated with fibronectin diluted in PBS to a final concentration of 2.5 &#181;g/mL. (B) A confluent 10 cm dish of PH-Akt-GFP-expressing mouse embryonic fibroblasts (MEFs) is washed with PBS and treated with 0.05% trypsin-EDTA. The trypsin-treated cells are then split into a 15 mL centrifuge tube and a 6 cm tissue culture dish, both containing cell culture media. (C) From the 15 mL centrifuge tube, 500-1000 &#181;L is pipetted onto the fibronectin-coated coverslip. (D) The 6 cm dish and the 35 mm dish with the coverslip containing the sparsely seeded cells are placed in a 37 &#176;C incubator overnight. Once polarized, these cells will provide the frame of focus for the cell spreading acquisition. (E) An hour before image acquisition, the 6 cm dish&#39;s media is replaced with phenol-red free DMEM supplemented with HEPES and the drug of interest. After 1 hour, the cells are treated with 0.05% trypsin-EDTA and transferred to a 15 mL centrifuge tube (Tube A) containing the HEPES/drug-supplemented phenol red free DMEM. The cells in Tube A are then further diluted in another 15 mL centrifuge tube (Tube B), which is placed in the incubator for 45 minutes. (F) As the cells recover, the magnetic chamber is prepared from bottom to top: first the bottom plate is placed on a flat surface, then the coverslip with the polarized cells, the silicone gasket, the main body of the chamber, and finally the transparent cover are laid on top. (G) 1 mL of drug-supplemented phenol red free DMEM is pipetted into the magnetic chamber, which is then brought to the microscope stage. A CFI Plan Apo Lambda 60X Oil objective is selected for image acquisition. (H) The transparent cover is removed and 500 &#181;L of Tube B&#39;s contents are pipetted into the magnetic chamber. (I) For image acquisition, appropriate fields of view will contain green &#34;halos&#34;, which are suspended cells that have not yet attached to the coverslip. (J) The cells are imaged for 15 minutes. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/62369fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62369/62369fig2v2.jpg" /> 
Figure 2: The effect of recovery time on cell spreading. Cells maintained in suspension for the indicated time (cell recovery step in the protocol) were plated on fibronectin-coated coverslips for 15 minutes, fixed with 4% paraformaldehyde and imaged by phase contrast microscopy. (A) Top panels: phase contrast images acquired with a 20X objective. Bottom panels: watershed-segmented cell masks with the cell areas color-coded. (B) Quantification of cell area. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/62369fig2v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/62369/62369fig3v2.jpg" /> 
Figure 3: Graphical User Interface (GUI) and the working principles of image processing and analysis software. (A) The GUI of the &#34;Cell spread area&#34; tab. Refer to Step 5.3 for instructions. (B) The GUI of the &#34;Kymograph generator &#38; analysis&#34; tab. Refer to Step 6 for instructions. (C) The image processing pipeline of the software. The software first identifies spreading cells (labeled by a green bounding box) in the whole field of view. The spreading cells are identified based on their intensity value, circularity, and aspect ratio. The identified spreading cells are then segmented frame-by-frame using global intensity thresholding. Each binary mask is processed by median filtering and binary hole filling followed by morphological closing to smoothen the cell edge. The red outline corresponds to the segmented cell boundary. The cell&#39;s area, aspect ratio, and circularity are extracted from the binary cell map. The graph shows the area and circularity of a representative cell over time. Upon cell seeding, cells do not start spreading immediately, giving rise to the lag phase seen on the graph. Following the lag phase, cells spread rapidly during the rapid expansion phase and eventually reach a plateau phase. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/62369fig3v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62369/62369fig4v2.jpg" /> 
Figure 4: Representative results of cell spread area analysis upon Arp2/3 inhibition. (A) Representative images of PH-Akt-GFP-expressing MEFs spreading on a fibronectin-coated coverslip over the course of 3 minutes. The red line indicates the cell boundary extracted by the cell segmentation algorithm. Top panels: 0.1% DMSO-treated cells. Bottom panels: 100 &#181;M CK-666 (Arp2/3 inhibitor)-treated cells. (B) A graph showing cell spread area over time. The cell spread area was quantified as fold changes relative to the average cell spread area of control cells. Blue and pink lines represent control and Arp2/3-inhibited cells, respectively. The shaded regions indicate the upper and lower standard deviation of the cell spread area. (C) A bar plot with individual data points showing the average cell circularity of control and Arp2/3-inhibited cells. All error bars represent standard deviation. *, p &#60; 0.05, **, p &#60; 0.01, ***, p &#60; 0.001, n.s. (not significant, p &#62; 0.05) as detected by parametric student t-tests. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/62369fig4v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/62369/62369fig5v2.jpg" /> 
Figure 5: Representative results of kymograph analysis of spreading cells upon Arp2/3 inhibition. (A - B) Representative images and kymographs extracted from 0.1% DMSO-treated (control) cells and 100 &#181;M CK-666-treated&#160;(Arp2/3 inhibitor) cells. Left panels: inverted grayscale images of a control and Arp2/3-inhibited cell. The dashed lines correspond to the pre-defined lines where kymographs were extracted. Right panels: kymographs are extracted along the dashed lines shown on the grayscale images. The plot boundaries are color-coded to match the dashed lines on the grayscale images. The dashed line in each plot indicates the slope of the curve from which the average protrusion speed was calculated. To pinpoint the plateau phase, a logistic growth curve was fitted to the data points and the plateau was derived from the parameter, c (Supplementary Figure 1). The red dots denote the retraction events. (C) A bar plot with individual data points showing the average protrusion speeds of the control and Arp2/3-inhibited cells. All error bars represent standard deviation. (D) A bar plot with individual data points showing the frequency of retraction events of the control and Arp2/3-inhibited cells. (C - D) *, p &#60; 0.05, **, p &#60; 0.01, ***, p &#60; 0.001, n.s. (not significant, p &#62; 0.05) as detected by non-parametric Mann-Whitney tests. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/62369fig5v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Figure 1: A representative kymograph and the curve fitting result. A kymograph extracted from a spreading cell. The blue dashed line corresponds to the distance of the cell edge relative to the first frame. The red solid line corresponds to the fitted curve. To increase the confidence of the curve fitting, the raw data points were first smoothed by a Savitzky-Golay filter. After the curve-fitting, the parameter c, from the logistic equation, was used to identify the plateau point. The raw data point closest to c is designated as the plateau point. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/JoVE figure_supp_01.eps" target="_blank">Please click here to download this File.</a>
Supplemental Files. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/62369/supplemental_files.zip" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Quantitative Analysis of Cell Edge Dynamics during Cell Spreading at JoVE.com

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

In this protocol, we present the experimental procedures of a cell spreading assay that is based on live-cell microscopy. We provide an open-source computational tool for the unbiased segmentation of fluorescently labeled cells and quantitative analysis of lamellipodia dynamics during cell spreading.

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out ...

quantitative-analysis-of-cell-edge-dynamics-during-cell-spreading

Universidad San Sebastian

Research

JoVE Journal

Biology

5.3K Views.  University of Toronto. In this protocol, we present the experimental procedures of a cell spreading assay that is based on live-cell microscopy. We provide an open-source computational tool for the unbiased segmentation of fluorescently labeled cells and quantitative analysis of lamellipodia dynamics during cell spreading.

Video: Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns

Lateral displacement of cells orthogonal to a flow stream by rolling on asymmetric receptor patterns presents an opportunity for development of new devices for label-free separation and analysis of cells1. Such devices may use lateral displacement for continuous-flow separation, or receptor patterns that modulate adhesion to distinguish between different cell phenotypes or levels of receptor expression. Understanding the nature of cell rolling trajectories on receptor-patterned substrates is necessary for engineering of the substrates and design of such devices.
Here, we demonstrate a protocol for studying cell rolling trajectories on asymmetric receptor patterns that support cell rolling adhesion2. Well-defined, &mu;m-scale patterns of P-selectin receptors were fabricated using microcontact printing on gold-coated slides that were incorporated in a flow chamber. HL60 cells expressing the PSGL-1 ligand 3were flowed across a field of patterned lines and visualized on an inverted bright field microscope. The cells rolled and tracked along the inclined edges of the patterns, resulting in lateral deflection1. Each cell typically rolled for a certain distance along the pattern edges (defined as the edge tracking length), detached from the edge, and reattached to a downstream pattern. Although this detachment makes it difficult to track the entire trajectory of a cell from entrance to exit in the flow chamber, particle-tracking software was used to analyze and yield the rolling trajectories of the cells during the time when they were moving on a single receptor-patterned line. The trajectories were then examined to obtain distributions of cell rolling velocities and the edge tracking lengths for each cell for different patterns.
This protocol is useful for quantifying cell rolling trajectories on receptor patterns and relating these to engineering parameters such as pattern angle and shear stress. Such data will be useful for design of microfluidic devices for label-free cell separation and analysis.

We describe a protocol to observe and analyze cell rolling trajectories on asymmetric receptor-patterned substrates. The resulting data are useful for engineering of receptor-patterned substrates for label-free cell separation and analysis.

Lateral displacement of cells orthogonal to a flow stream by rolling on asymmetric receptor patterns presents an opportunity for development of new ...

Bioengineering

Using the Dot Assay to Analyze Migration of Cell Sheets

Although complex organisms appear static, their tissues are under a continuous turnover. As cells age, die, and are replaced by new cells, cells move within tissues in a tightly orchestrated manner. During tumor development, this equilibrium is disturbed, and tumor cells leave the epithelium of origin to invade the local microenvironment, to travel to distant sites, and to ultimately form metastatic tumors at distant sites. The dot assay is a simple, two-dimensional unconstrained migration assay, to assess the net movement of cell sheets into a cell-free area, and to analyze parameters of cell migration using time-lapse imaging. Here, the dot assay is demonstrated using a human invasive, lung colony forming breast cancer cell line, MCF10CA1a, to analyze the cells' migratory response to epidermal growth factor (EGF), which is known to increase malignant potential of breast cancer cells and to alter the migratory phenotype of cells.

Cell migration is essential for development, tissue maintenance and repair, and tumorigenesis, and is regulated by growth factors, chemokines, and cytokines. This protocol describes the dot assay, a two-dimensional, unconstrained migration assay to assess the migratory phenotype of attached, cohesive cell sheets in response to microenvironmental cues.

Although complex organisms appear static, their tissues are under a continuous turnover. As cells age, die, and are replaced by new cells, cells move ...

Cancer Research

Examining the Dynamics of Cellular Adhesion and Spreading of Epithelial Cells on Fibronectin During Oxidative Stress

The adhesion and spreading of cells onto the extracellular matrix (ECM) are essential cellular processes during organismal development and for the homeostasis of adult tissues. Interestingly, oxidative stress can alter these processes, thus contributing to the pathophysiology of diseases such as metastatic cancer. Therefore, understanding the mechanism(s) of how cells attach and spread on the ECM during perturbations in redox status can provide insight into normal and disease states. Described below is a step-wise protocol that utilizes an immunofluorescence-based assay to specifically quantify cell adhesion and spreading of immortalized fibroblast cells on fibronectin (FN) in vitro. Briefly, anchorage-dependent cells are held in suspension and exposed to the ATM kinase inhibitor Ku55933 to induce oxidative stress. Cells are then plated on FN-coated surface and allowed to attach for predetermined periods of time. Cells that remain attached are fixed and labeled with fluorescence-based antibody markers of adhesion (e.g., paxillin) and spreading (e.g., F-actin). Data acquisition and analysis are performed using commonly available laboratory equipment, including an epifluorescence microscope and freely available Fiji software. This procedure is highly versatile and can be modified for a variety of cell lines, ECM proteins, or inhibitors in order to examine a broad range of biological questions.

This method is useful for quantifying the early dynamics of cellular adhesion and spreading of anchorage-dependent cells onto the fibronectin. Furthermore, this assay can be used to investigate the effects of altered redox homeostasis on cell spreading and/or cell adhesion-related intracellular signaling pathways.

The adhesion and spreading of cells onto the extracellular matrix (ECM) are essential cellular processes during organismal development and for the ...

Biochemistry

Study of the Actin Cytoskeleton in Live Endothelial Cells Expressing GFP-Actin

The microvascular endothelium plays an important role as a selectively permeable barrier to fluids and solutes. The adhesive junctions between endothelial cells regulate permeability of the endothelium, and many studies have indicated the important contribution of the actin cytoskeleton to determining junctional integrity1-5. A cortical actin belt is thought to be important for the maintenance of stable junctions1, 2, 4, 5. In contrast, actin stress fibers are thought to generate centripetal tension within endothelial cells that weakens junctions2-5. Much of this theory has been based on studies in which endothelial cells are treated with inflammatory mediators known to increase endothelial permeability, and then fixing the cells and labeling F-actin for microscopic observation. However, these studies provide a very limited understanding of the role of the actin cytoskeleton because images of fixed cells provide only snapshots in time with no information about the dynamics of actin structures5. 
Live-cell imaging allows incorporation of the dynamic nature of the actin cytoskeleton into the studies of the mechanisms determining endothelial barrier integrity. A major advantage of this method is that the impact of various inflammatory stimuli on actin structures in endothelial cells can be assessed in the same set of living cells before and after treatment, removing potential bias that may occur when observing fixed specimens. Human umbilical vein endothelial cells (HUVEC) are transfected with a GFP-&beta;-actin plasmid and grown to confluence on glass coverslips. Time-lapse images of GFP-actin in confluent HUVEC are captured before and after the addition of inflammatory mediators that elicit time-dependent changes in endothelial barrier integrity. These studies enable visual observation of the fluid sequence of changes in the actin cytoskeleton that contribute to endothelial barrier disruption and restoration. 
Our results consistently show local, actin-rich lamellipodia formation and turnover in endothelial cells. The formation and movement of actin stress fibers can also be observed. An analysis of the frequency of formation and turnover of the local lamellipodia, before and after treatment with inflammatory stimuli can be documented by kymograph analyses. These studies provide important information on the dynamic nature of the actin cytoskeleton in endothelial cells that can used to discover previously unidentified molecular mechanisms important for the maintenance of endothelial barrier integrity.

Microscopic imaging of live endothelial cells expressing GFP-actin allows characterization of dynamic changes in cytoskeletal structures. Unlike techniques that use fixed specimens, this method provides a detailed assessment of temporal changes in the actin cytoskeleton in the same cells before, during, and after various physical, pharmacological, or inflammatory stimuli.

The microvascular endothelium plays an important role as a selectively permeable barrier to fluids and solutes. The adhesive junctions between endothelial ...

Quantitative Measurement of Invadopodia-mediated Extracellular Matrix Proteolysis in Single and Multicellular Contexts 

Cellular invasion into local tissues is a process important in development and homeostasis. Malregulated invasion and subsequent cell movement is characteristic of multiple pathological processes, including inflammation, cardiovascular disease and tumor cell metastasis1. Focalized proteolytic degradation of extracellular matrix (ECM) components in the epithelial or endothelial basement membrane is a critical step in initiating cellular invasion. In tumor cells, extensive in vitro analysis has determined that ECM degradation is accomplished by ventral actin-rich membrane protrusive structures termed invadopodia2,3. Invadopodia form in close apposition to the ECM, where they moderate ECM breakdown through the action of matrix metalloproteinases (MMPs). The ability of tumor cells to form invadopodia directly correlates with the ability to invade into local stroma and associated vascular components3. 
Visualization of invadopodia-mediated ECM degradation of cells by fluorescent microscopy using dye-labeled matrix proteins coated onto glass coverslips has emerged as the most prevalent technique for evaluating the degree of matrix proteolysis and cellular invasive potential4,5. Here we describe a version of the standard method for generating fluorescently-labeled glass coverslips utilizing a commercially available Oregon Green-488 gelatin conjugate. This method is easily scaled to rapidly produce large numbers of coated coverslips. We show some of the common microscopic artifacts that are often encountered during this procedure and how these can be avoided. Finally, we describe standardized methods using readily available computer software to allow quantification of labeled gelatin matrix degradation mediated by individual cells and by entire cellular populations. The described procedures provide the ability to accurately and reproducibly monitor invadopodia activity, and can also serve as a platform for evaluating the efficacy of modulating protein expression or testing of anti-invasive compounds on extracellular matrix degradation in single and multicellular settings.

Quantitative Measurement of Invadopodia-mediated Extracellular Matrix Proteolysis in Single and Multicellular Contexts

We describe the prototypical method for producing microscope coverslips coated with fluorescent gelatin for visualizing invadopodia-mediated matrix degradation. Computational techniques using available software are presented for quantifying the resultant levels of matrix proteolysis by single cells within a mixed population and for multicellular groups encompassing entire microscopic fields.

Cellular invasion into local tissues is a process important in development and homeostasis.  Malregulated invasion and subsequent cell movement is ...

All-optical Mechanobiology Interrogation of Yes-associated Protein in Human Cancer and Normal Cells using a Multi-functional System

Long-term multi-functional imaging and analysis of live cells require streamlined, functional coordination of various hardware and software platforms. However, manual control of various equipment produced by different manufacturers is labor-intensive and time-consuming, potentially decreasing the accuracy, reproducibility, and quality of acquired data. Therefore, an all-in-one and user-programmable system that enables automatic, multi-functional, and long-term image acquisition and is compatible with most fluorescent microscopy platforms can benefit the scientific community. This paper introduces the complete operating protocols of utilizing a novel integrated software system that consists of (1) a home-built software program, titled "Automatic Multi-functional Integration Program (AMFIP)," which enables automatic multi-channel imaging acquisition, and (2) a suite of quantitative imaging analysis and cell traction computation packages. 
This integrated system is applied to reveal the previously unknown relationship between the spatial-temporal distribution of mechano-sensitive Yes-associated protein (YAP) and the cell mechanics, including cell spreading and traction, in CRISPR/Cas9-engineered human normal cells (B2B) and lung cancer cells (PC9). Leveraging this system's capability of multi-channel control and readout, the result shows: (1) B2B normal cells and PC9 cancer cells show a distinct relationship between YAP expression, traction, and cell dynamics during cell spreading and migration processes; and (2) PC9 cancer cells apply noticeable peri-nuclear forces on substrates. In summary, this paper presents a detailed stepwise protocol on how to utilize an integrated user-programmable system that enables automatic multi-functional imaging and analysis to elucidate YAP mechano-sensitivity. These tools open the possibility for detailed explorations of multifaceted signaling dynamics in the context of cell physiology and pathology.

This paper presents a detailed stepwise protocol on how to utilize an integrated multi-functional and user-programmable system that enables automatic multi-channel imaging and mechanobiological analysis to elucidate the mechano-sensitivity of Yes-associated protein (YAP).

Long-term multi-functional imaging and analysis of live cells require streamlined, functional coordination of various hardware and software platforms. ...

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes depend on the advances of growth cones that located at the tips of neurites. Axonal growth cones generate driving forces by sensing their local microenvironment and modulating cytoskeletal dynamics and actin-adhesion coupling (clutch coupling). Decades of research have led to the identification of guidance molecules, their receptors, and downstream signaling cascades for regulating neuronal migration and axonal guidance; however, the molecular machineries required for generating forces to drive growth cone advance and navigation are just beginning to be elucidated. At the leading edge of neuronal growth cones, actin filaments undergo retrograde flow, which is powered by actin polymerization and actomyosin contraction. A clutch coupling between F-actin retrograde flow and adhesive substrate generates traction forces for growth cone advance. The present study describes a detailed protocol for monitoring F-actin retrograde flow by single speckle imaging. Importantly, when combined with an F-actin marker Lifeact, this technique can quantify 1) the F-actin polymerization rate and 2) the clutch coupling efficiency between F-actin retrograde flow and the adhesive substrate. Both are critical variables for generating forces for growth cone advance and navigation. In addition, the present study describes a detailed protocol of traction force microscopy, which can quantify 3) traction force generated by growth cones. Thus, by coupling the analyses of&#160;single speckle imaging and traction force microscopy, investigators can monitor the molecular mechanics underlying growth cone advance and navigation.

To advance, growth cones must exert traction forces against the external environment. The generation of traction forces is dependent on actin dynamics and clutch coupling. The present study describes methods for analyzing actin dynamics, clutch coupling and traction forces for growth cone advance.

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes ...

Neuroscience

A Simplified System for Evaluating Cell Mechanosensing and Durotaxis In Vitro

The composition and mechanical properties of the extracellular matrix are highly variable between tissue types. This connective tissue stroma diversity greatly impacts cell behavior to regulate normal and pathologic processes including cell proliferation, differentiation, adhesion signaling and directional migration. In this regard, the innate ability of certain cell types to migrate towards a stiffer, or less compliant matrix substrate is referred to as durotaxis. This phenomenon plays an important role during embryonic development, wound repair and cancer cell invasion. Here, we describe a straightforward assay to study durotaxis, in vitro, using polydimethylsiloxane (PDMS) substrates. Preparation of the described durotaxis chambers creates a rigidity interface between the relatively soft PDMS gel and a rigid glass coverslip. In the example provided, we have used these durotaxis chambers to demonstrate a role for the cdc42/Rac1 GTPase activating protein, cdGAP, in mechanosensing and durotaxis regulation in human U2OS osteosarcoma cells. This assay is readily adaptable to other cell types and/or knockdown of other proteins of interests to explore their respective roles in mechanosignaling and durotaxis.

A Simplified System for Evaluating Cell Mechanosensing and Durotaxis In Vitro

Many mammalian cells preferentially migrate towards a more rigid matrix or substrate through durotaxis. The goal of this protocol is to provide a simple in vitro system that can be used to study and manipulate cell durotaxis behaviors by incorporating polydimethylsiloxane (PDMS) substrates of defined rigidity, interfacing with glass coverslips.

The composition and mechanical properties of the extracellular matrix are highly variable between tissue types. This connective tissue stroma diversity ...

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Live imaging of the pHluorin tagged Soluble N-ethylmaleimide-sensitive-factor Attachment protein REceptor (v-SNARE) Vesicle-associated membrane protein 7 (VAMP7) by total internal reflection fluorescence microscopy (TIRFM) is a straightforward way to explore secretion from the lysosomal compartment. Taking advantage of cell culture on micropatterned surfaces to normalize cell shape, a variety of statistical tools were employed to perform a spatial analysis of secretory patterns. Using Ripley&#8217;s K function and a statistical test based on the nearest neighbor distance (NND), we confirmed that secretion from lysosomes is not a random process but shows significant clustering. Of note, our analysis revealed that exocytosis events are also clustered in nonadhesion areas, indicating that adhesion molecules are not the only structures that can induce secretory hot spots at the plasma membrane. Still, we found that cell adhesion enhances clustering. In addition to precisely defined adhesive and nonadhesive areas, the circular geometry of these micropatterns allows the use of polar coordinates, simplifying analyses. We used Kernel Density Estimation (KDE) and the cumulative distribution function on polar coordinates of exocytosis events to identify enriched areas of exocytosis. In ring-shaped micropattern cells, clustering occurred at the border between the adhesive and nonadhesive areas. Our analysis illustrates how statistical tools can be employed to investigate spatial distributions of diverse biological processes.

Live imaging of lysosomal exocytosis on micropatterned cells allows a spatial quantification of this process. Morphology normalization using micropatterns is an outstanding tool to uncover general rules about the spatial distribution of cellular processes.

Live imaging of the pHluorin tagged Soluble N-ethylmaleimide-sensitive-factor Attachment protein REceptor (v-SNARE) Vesicle-associated membrane protein 7 ...

Quantification of Cell-Substrate Adhesion Area and Cell Shape Distributions in MCF7 Cell Monolayers

The methods presented here quantify some parameters of confluent adherent cell monolayers from multiple appropriately stained confocal images: adhesion to the substrate as a function of the number and size of focal adhesions, and cell shape, characterized by the cell shape index and other shape descriptors. Focal adhesions were visualized by paxillin staining and cell-cell borders were marked by junction plakoglobin and actin. The methods for cell culture and staining were standard; images represent single focal planes; image analysis was performed using publicly available image processing software. The presented protocols are used to quantify the number and size of focal adhesions and the differences in cell shape distribution in the monolayers, but they can be repurposed for the quantification of the size and shape of any other distinct cellular structure that can be stained (e.g., mitochondria or nuclei). Assessing these parameters is important in the characterization of the dynamic forces in adherent cell layer, including cell adhesion and actomyosin contractility that affects cell shape.

The article describes quantification of 1) the size and number of focal adhesions and 2) cell shape index and its distribution from confocal images of the confluent monolayers of MCF7 cells.

The methods presented here quantify some parameters of confluent adherent cell monolayers from multiple appropriately stained confocal images: adhesion to ...

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Summary

Explore More Videos

Chapters in this video

Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns

Using the Dot Assay to Analyze Migration of Cell Sheets

Examining the Dynamics of Cellular Adhesion and Spreading of Epithelial Cells on Fibronectin During Oxidative Stress

Study of the Actin Cytoskeleton in Live Endothelial Cells Expressing GFP-Actin

Quantitative Measurement of Invadopodia-mediated Extracellular Matrix Proteolysis in Single and Multicellular Contexts

All-optical Mechanobiology Interrogation of Yes-associated Protein in Human Cancer and Normal Cells using a Multi-functional System

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

A Simplified System for Evaluating Cell Mechanosensing and Durotaxis In Vitro

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Quantification of Cell-Substrate Adhesion Area and Cell Shape Distributions in MCF7 Cell Monolayers