Measurement of Mechanical Tension at cell-cell junctions using two-photon laser ablation

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Developmental Cell
Apr 2016


The cortical actomyosin cytoskeleton is found in all non-muscle cells where a key function is to control mechanical force (Salbreux et al., 2012). When coupled to E-cadherin cell-cell adhesion, cortical actomyosin generates junctional tension that influences many aspects of tissue function, organization and morphogenesis (Lecuit and Yap, 2015). Uncovering the molecular mechanisms underlying the generation of junctional tension requires tools for measuring it in live cells with a high spatio-temporal resolution. For this, we have set up a technique of laser ablation, in which we use the high power output of a two-photon laser to physically cut the actin cortex at the sites of cell-cell adhesion labeled with E-cadherin-GFP. Tension, thus is visualized as the outwards recoil of the vertices that define a junction after this was ablated/cut. Analysis of recoil versus time allows extracting parameters related to the amount of contractile force that is applied to the junction before ablation (initial recoil) and the ratio between elasticity of the junction and viscosity of the media (cytoplasm) in which the junctional cortex is immersed. Using this approach we have discovered how Src protein-tyrosine kinase (Gomez et al., 2015); actin-binding proteins such as tropomyosins (Caldwell et al., 2014) and N-WASP (Wu et al., 2014); Myosin II (Priya et al., 2015) and coronin-1B (Michael et al., 2016) contribute to the molecular apparatus responsible for generating tension at the cell-cell junctions. This protocol describes the experimental procedure for setting up laser ablation experiments and how to optimize ablation and acquisition conditions for optimal measurements of junctional tension. It also provides a full description, step by step, of the post-acquisition analysis required to evaluate changes in contractile force as well as cell elasticity and/or cytoplasm viscosity.

Keywords: Laser ablation (激光烧蚀), Tension (张力), Cell-cell junction (细胞间连接), Two-photon (双光子), Viscoelasticity (粘弹性), Epithelial cells (上皮细胞)


Physical tension on junctions has been revealed by a variety of microscopy methods. These include laser ablation (Ratheesh et al., 2012; Smutny et al., 2015; Michael et al., 2016), optical tweezers (Bambardekar et al., 2015), FRET tension sensors (Grashoff et al., 2010; Borghi et al., 2012; Conway et al., 2013; Leerberg et al., 2014) and immunofluorescence for protein epitopes that are revealed under tension (Yonemura et al., 2010). Among these, laser ablation has become the most popular method, as it is easy to implement and provide a direct measurement of mechanical tension compared with other methods (e.g., FRET or immunofluorescence where the evidence for mechanical tension is more indirect). However, special considerations need to be taken to set up these experiments as well as its analysis, which are important for the correct interpretation of results. This protocol, provides the basic steps needed for the setup and optimization of laser ablation experiments in confluent monolayers of epithelial cells as well as a complete description of the image analysis procedure for measurements of initial recoil after ablation, which is an index of junctional tension.

Materials and Reagents

  1. MCF-7 or Caco-2 cells from ATCC®
    Note: This protocol can be easily extended to any other endothelial or epithelial cell line with well defined cell-cell junctions like AML12 cells.
  2. Plasmids (or lentivirus) to express a junctional marker like E-cadherin-GFP.
    See Bio-protocol e937 by Priya and Gomez (2013) for lentivirus preparation for expression of mouse E-cadherin-GFP in cells knockdown for endogenous human E-cadherin. In this protocol, we describe the transfection of cells for overexpression of E-cadherin-GFP.
  3. Purified plasmid DNA encoding E-cadherin-GFP (Addgene, catalog number: 67937 ) or any other junctional protein like ZO-1 (Addgene, catalog number: 30313 ), vinculin (Addgene, catalog number: 30312 ), MRLC (Addgene, catalog number: 35680 ), or the actin marker Utrophin (Addgene, catalog number: 26737 )
  4. Lipofectamine 3000 and P3000 reagent (Thermo Fisher Scientific, InvitrogenTM, catalog number: L3000015 )
  5. Dulbecco’s modified Eagle’s medium high glucose with stable L-glutamine (DMEM) (Thermo Fisher Scientific, GibcoTM, catalog number: 11995-073 )
  6. Fetal bovine serum (FBS) (Thermo Fisher Scientific, GibcoTM, catalog number: 26140079 )
  7. PBS without Ca2+ and Mg2+ (Astral Scientific, catalog number: 09-8912-100 )
  8. Opti-MEM media (Thermo Fisher Scientific, GibcoTM, catalog number: 31985070 )
  9. Hank’s balanced salt solution (HBSS) (Sigma-Aldrich, catalog number: H8264 )
  10. CaCl2
  11. Imaging media (see Recipes)


  1. Laser scanning confocal microscope, LSM 510 Meta Zeiss confocal microscope (Zeiss, Jena, Germany) equipped with:
    An acoustic optical tunable filter (AOTF) for bleaching of selected areas
    A heated chamber (37 °C) for live cell imaging
    A tunable two-photon laser (700-1100 nm, > 2,000 mW power, Chameleon Laser, Coherent Inc.)
    A 30 mW argon laser (458, 488 and 514 nm laser lines)
    A 60x objective, 1.4 NA oil Plan Apochromat (Zeiss) immersion lens
    Dichroic and emission filters for the use of the 488 nm laser lines and detection of GFP fluorescence
  2. Glass bottom dishes, No. 1.5 Coverslip (35 mm diameter, MATTEK, catalog number: P35G-1.5-20-C or 29 mm diameter, Shengyou Biotechnology, catalog number: D29-10-1.5-N )


  1. ImageJ software (https://imagej.nih.gov/ij/)
  2. Fiji software (http://imagej.net/Fiji)
  3. MTrackJ pluging (http://www.imagescience.org/meijering/software/mtrackj/manual/)
  4. Microsoft Excel (https://products.office.com/en-au/excel)
  5. GraphPad PRISM software (http://www.graphpad.com/scientific-software/prism/)


  1. Cell preparation
    Expression of GFP-Tagged proteins to label cell-cell junctions could be achieved by endogenously tagging a gene of interest using genome editing tools like CRISPR, virus transduction (see Priya and Gomez, 2013) or transient transfection of a plasmid encoding a junctional protein fused to GFP using Lipofectamine 3000 as it is described below (See Appendix I).
    Note: The overexpression of plasmids should not cause any gain of function and/or alter cell’s physiology (i.e., abrupt changes in morphology).
    1. Plating and transfection of cells with E-cadherin-GFP constructs
      1. For ablation experiments, MCF-7 cells are cultured in DMEM supplemented with 10% FBS and transfected with a plasmid encoding E-cadherin-GFP.
      2. Cells are incubated at 37 °C in DMEM + 10% FBS and when these are ~80% confluent harvested by trypsinization.
      3. Single-cell suspensions are seeded on glass bottom dishes at 75% confluence and allowed to grow for 24 h for transfection with plasmids using Lipofectamine 3000.
      4. On the day of transfection, medium of cells is changed to Opti-MEM (1 ml) in the absence of serum and antibiotics and transfection performed as described in Appendix I.
      5. 24 to 48 h after transfection, and once cells are 90 to 100% confluent, cells were washed and incubated in the presence of imaging media for microscopy analysis. Figure 1 shows a representative image of the morphology of cells before ablation using 60x magnification.
        Note: The imaging media is used as it does not have phenol red, which can interfere with live cell imaging by increasing the fluorescence background. This leads to the use of higher laser power for imaging and the production of reactive species that might result toxic for cells.

        Figure 1. Fluorescence image of Caco-2 cells expressing E-cadherin-GFP. See also Supplementary Video 4.

  2. Image acquisition
    1. For the use of multiphoton lasers read carefully the Safety considerations associate to its use (Appendix IV)
    2. For recoil measurements, please ensure analyze cells with consistent level of expression of the E-cadherin-GFP construct. Ideally overexpression levels should be kept at minimal to prevent overexpression artifacts (see also Appendix I) and being compatible with live cell imaging.
    1. Once identified the target cells, acquire time-lapse images of GFP fluorescence in a region of interest of 270 x 270 pixels, 0.1860119 μm/pixel (at 4x digital zoom, 0.8 μm optical section) before (2 frames) and after (5 frames, or until no more changes in junctional length are observed, ~1 min). Images are acquired with a time interval of 8 sec for a total time of 44 sec using a 488 nm laser line of an argon laser (30 mW) at 1-3% transmission (Figures 2A and 2B; Supplementary Video 1; Appendix II).
      Note: This region of interest is sufficient to acquire a single cell-cell junction to analyze its changes in length after ablation without the need of acquiring the entire field of view (512 x 512 pixels, Figure 2A) that would slow down the speed at which junctional recoil can be monitored.
    2. A constant region of interest of 2.8 x 1.7 μm with the longer axis parallel to the cell-cell contact (Figure 2A) was marked for ablation using 30 iterations of the Chameleon laser set at 790 nm with 40% transmission (See Supplementary Video 1 and Appendix II). This resulted in efficient ablation without significant cell damage (Figure 2B, see also Supplementary Video 2 for a case where cell damage is significant).
      Note: For quantifications and statistical analysis this acquisition procedure is repeated between 15 and 25 times per condition per experiment in at least 3 independent experiments (See also Figure 14).

      Figure 2. Regions of interest acquired during ablation experiments and representative still images of a junction before and after ablation. A. Scheme of different regions of interest used for laser ablation and measurements of junctional tension; B. Slices of movie stills of a laser ablation experiment to measure tension on cell-cell junctions. Yellow lines: the original positions of vertices before laser ablation; Red lines: the real-time positions of vertices; Arrowhead: the site of ablation.

  3. Optimization of laser power and iterations for the ablation step (see Appendix V).
    Note: This optimization should be done using the cell line of interest expressing the preferred junctional marker in sufficient amount for efficient detection using a laser confocal microscope and perform time lapse imaging. If the marker is overexpressed, the experimentalist should try to express it at minimal levels enough for imaging and avoid any gain of function effect due to overexpression.
    1. To set up this optimization step, it is imperative to start with cells that have tension on their junctions, as a successful ablation would lead to observable elongation of the junction, i.e., recoil of the vertices that define it (Supplementary Videos 1, 2 and 4).
    2. In practice, perform initial tests with ablation settings using a high number of iterations (> 20 and increase more if necessary) and high laser power (~70% and increase more if necessary). Under these harsh conditions, significant cell damage should be observed, which will show that laser power of the infrared laser is effective and it is properly collimated (See also Appendix III, Supplementary Video 3).
    3. Once this laser power and iterations have been attained, then these parameters could be reduced stepwise until recoil of junctions is observed but with much less cell damage.
    4. While keeping constant iterations (~10-20) the laser could be reduced until a level where no more recoil is observed, but bleaching of fluorescence occurs instead. These tests would help to identify the minimal laser power needed for an efficient ablation protocol.
    5. Once this is achieved, it is possible to obtain settings in which damage to the cell membrane is minimal. This could be done by doing additional controls ablating a junction (labeled with apical junctional marker) between a cell that expresses cytoplasmic mCherry and a cell that does not.
      Under these conditions, it should be possible to perform ablation experiments in which observable recoil is observed but no significant flow of mCherry fluorescence from one cell to another is observed (see Supplementary Videos 2 and 3).
    6. Moreover, acquisition of a DIC image together with GFP fluorescence images allow for checking that laser power is not too high to cause damage.

Data analysis

  1. Image analysis
    1. Measurements of distances between vertices over time
      1. One at the time, open acquired time-lapse images (n = 15 - 25 per condition per experiment) in ImageJ software. A median filter (1 pixel) should be applied if the images are noisy and a maximal projection if Z-stacks were acquired at each time point.
      2. Use the MTrackJ plugin to measure the strain or deformation ε(t) of the cell-cell junction as a function of time after ablation. In particular, using this plugin we track the XY coordinates of each vertex that defines the ablated junction over time (see MTrackJ manual available at http://www.imagescience.org/meijering/software/mtrackj/manual/). Then, copy the X and Y values into an excel sheet. For each ablated junction we will obtain 4 columns: X(top), Y(top), X(bottom) and Y(bottom) and n rows, where n is the number of time points present in the movie (This ranges from 6 to 20, depending on how fast the system reaches the plateau).
    2. Using the tracking data generated by the MTrackJ plugin, calculate the length of the contact L(t) for each time point t as:

      which in Excel can be done using the following formula

            L(t)=sqrt((Xtop(t) - Xbottom(t)) ^ 2 + (Ytop(t) - Ybottom(t)) ^ 2)         (Eq. 2)

    3. The amount of recoil or strain ε(t) after ablation is then measured at each time point (row) as the difference between the length of the contact at any time [L(t)] and the length of the contact before ablation [L(0)].

            ε(t)=L(t)-L(0)          (Eq. 3)

    4. Figure 3 shows an example of experimental data obtained using Eq. 3. Where it is plotted the average recoil value from 20 ablations (See also Supplementary File 1).

      Figure 3. The records of ε(t), vertex separation minus vertex separation at time = 0. The plots are mean values of 20 junctions analyzed. Error bars are ± SEM (See also Supplementary File 1).

  2. Fitting of the data: extraction of initial recoil and k values
    Rationale: Within the time scales of the ablation experiments, if junctional strain exhibits a single exponential growth with a defined plateau after ablation, then it can be modeled as a Kelvin-Voigt fiber (Fernandez-Gonzalez et al., 2009) by fitting it to the following equation.

    F0 is the tensile force present at the junction before ablation,
    E is the elasticity of the junction,
    μ is the viscosity coefficient related to the viscous drag of the cell cytoplasm.
    As fitting parameters for the above equation we introduced


    1. From the fitting results then it is possible to extract two quantities: initial recoil, which is a measure of the underlying contractile tension on the junction before ablation and the k value, which is the ratio between the junctional elasticity and viscosity of the media.
      Note: When ablations are performed on different conditions, a change in initial recoil but not in k value is a strong indication that the tension on the junctions is affected. In contrast, simultaneous changes in initial recoil and k values are more difficult to interpret. For this last case, to could infer changes in physical tension (i.e., the amount of force) on cell-cell junctions first is needed to obtain an independent measurement of junctional elasticity (or stiffness). This can be done for example using atomic force microscopy or optical tweezers. Values of elasticity or stiffness are then used to calculate μ from the k values obtained from laser ablation experiments 𝜇 = 𝐸𝑘. Then, values of μ obtained in this manner, allow the calculation of the average amount of force on cell-cell junctions before ablation (F0=initial recoil*μ) even in conditions where elasticity and or viscosity are altered.
      Fitting of the recoil data (Eq. 3) can be done using GraphPad PRISM software. The file from where the snapshots displayed in Figures 4-14 is provided as Supplementary File 1. To start the analysis, first create a new XY table project where replicate Y (n = 20 to 30) values are entered and plotted for each time point (Figure 4).

      Figure 4. Snapshot of the GraphPad PRISM dialog window for the creation of a new XY project for the analysis of junctional recoil data

    2. Then paste the ε(t) values obtained in Excel (Eq. 3, see steps A1-A4 of the Image analysis section) into the GraphPad PRISM table (Figure 5, see also the Data Table: ‘recoil measurements’ within the Supplementary File 1 provided together with this protocol).

      Figure 5. Snapshot of an XY table that contains the recoil data from an experiment. The X column contains the values of time (in seconds) at which images were acquired. Time = 0 seconds corresponds to the time point acquired just before ablation. The Y component correspond to the ε(t) data derived from control cells (Eq. 3) and this data is grouped within group A. The values A:Y1, A:Y2, A:Yn corresponds to the recoil values from single junctions that were ablated. See also Supplementary File 1.

    3. Using this software plot the average ε(t) values by going to insert → New graph of existing data → Mean ± SEM (Figure 6).

      Figure 6. Snapshot of the ‘Create a new graph’ window in GraphPad PRISM for the plot of recoil results

    4. Then perform the fitting by going to the ‘fit non linear’ button (Figure 7). This will open a new window with the different options to use already available equations or to create a new equation for fitting of the data. Please note that for this and the following steps it might be useful having read the general guidelines for non-linear regression using GraphPad Prism available at: http://www.graphpad.com/guides/prism/7/curve-fitting/index.htm?reg__curve_fitting_with_prism_6.htm

      Figure 7. Snapshot of the fitting analysis options in GraphPad PRISM software

    5. In the new dialog window, create a new equation for fitting (Figure 8).

      Figure 8. Snapshot of the non-linear fitting menu within the GraphPad Prism software

    6. In the ‘Equation’ menu (see top of Figure 9)

      Figure 9. Adding the equation for initial recoil measurements within the non-linear functions of GraphPad PRISM

      1. Assign a Name to the new Equation, for example ‘laser nanoscissors’.
      2. Paste the following equation within the Definition field:

        Y = (initialrecoil/K) * (1 - exp [-K * x]) (see also Figure 9)

      3. Then, go to the next tab ‘Rule for Initial Values’ in the same window and select the following conditions for the initial values of parameters for fitting (Figure 10).
      4. Go to the ‘Default constraints’ tab and assign values greater than zero for the fitting parameters initial recoil and k (Figure 11).
      5. Clear any transformation to be reported in the last tab of this window (Transform to report, Figure 12). These are not further required for this analysis.
      6. Accept all the changes by pressing the ‘ok’ button.
      7. Fit the data (least squares and without interpolation of unknowns). You will obtain a table with the results of the fitting (Figure 13).

        Figure 10. ‘Rule for Initial Values’ for fitting parameters of recoil measurements within the non-linear regression menu in GraphPad PRISM

        Figure 11. Definition of default constraints for fitting parameters of recoil data using non-linear regression

        Figure 12. ‘Transform to Report’ menu within the ‘create New Equation’ window in Non-linear regression analysis

        Figure 13. Snapshot of the results from the non-linear regression of the recoil data showing the values for initial recoil and k

      8. Copy the row with the different ‘initial recoil’ (3rd row of the results, see also Figure 13) and ‘k’ values (4th row of results) together with their standard errors (SD, rows 6 and 7, respectively) of the different experimental conditions and paste them into another sheet in GraphPad PRISM (see sheet ‘Average initial recoil’ within the Supplementary File 1, see also Figure 14). From there it is possible to calculate average values of initial recoil and k values from different conditions and for independent experiments (different dates) and perform statistical tests across these to evaluate differences in recoil velocity (i.e., tension).

        Figure 14. Table with initial recoil values and its errors obtained from non-linear regression analysis of recoil data. Here the data is pasted into a new grouped table within the GraphPad PRISM file (see also this PRISM file provided as Supplementary File 1 for this protocol).

      9. From the above model, it can be deduced that differences in the tensile force present on junctions can be estimated by comparing initial recoil values between different conditions assuming that the viscosity is not significantly different between them. In order to assess whether this assumption is valid during these experiments, it is important to compute the rate constant, k, between different conditions as this would change if viscosity or elasticity of the junctions were significantly altered. No significant change in k values between different experimental conditions (assessed by t-test or ONE-WAY ANOVA) suggests that changes in tensile force are the dominant contributors to the changes in initial recoil velocity.


  1. Imaging media
    Hank’s balanced salt solution supplemented with 10 mM HEPES pH 7.4 and 5 mM CaCl2


This protocol was adapted from previous work from our laboratory (Ratheesh et al., 2012; Michael et al., 2016). Confocal microscopy was performed at the IMB/ACRF Cancer Biology Imaging Facility, established with the generous support of the Australian Cancer Research Foundation. We also thanks to John Griffin and Darren Paul for advise on safety considerations in relation to the use of pulsed lasers.


  1. Bambardekar, K., Clement, R., Blanc, O., Chardes, C. and Lenne, P. F. (2015). Direct laser manipulation reveals the mechanics of cell contacts in vivo. Proc Natl Acad Sci U S A 112(5): 1416-1421.
  2. Borghi, N., Sorokina, M., Shcherbakova, O. G., Weis, W. I., Pruitt, B. L., Nelson, W. J. and Dunn, A. R. (2012). E-cadherin is under constitutive actomyosin-generated tension that is increased at cell–cell contacts upon externally applied stretch. Proc Natl Acad Sci U S A 109(31): 12568-12573.
  3. Caldwell, B. J., Lucas, C., Kee, A. J., Gaus, K., Gunning, P. W., Hardeman, E. C., Yap, A. S. and Gomez, G. A. (2014). Tropomyosin isoforms support actomyosin biogenesis to generate contractile tension at the epithelial zonula adherens. Cytoskeleton (Hoboken) 71(12): 663-676.
  4. Conway, D. E., Breckenridge, M. T., Hinde, E., Gratton, E., Chen, C. S. and Schwartz, M. A. (2013). Fluid shear stress on endothelial cells modulates mechanical tension across VE-cadherin and PECAM-1. Curr Biol 23(11): 1024-1030.
  5. Fernandez-Gonzalez, R., Simoes Sde, M., Roper, J. C., Eaton, S. and Zallen, J. A. (2009). Myosin II dynamics are regulated by tension in intercalating cells. Dev Cell 17(5): 736-743.
  6. Gomez, G. A., McLachlan, R. W., Wu, S. K., Caldwell, B. J., Moussa, E., Verma, S., Bastiani, M., Priya, R., Parton, R. G., Gaus, K., Sap, J. and Yap, A. S. (2015). An RPTPα/Src family kinase/Rap1 signaling module recruits myosin IIB to support contractile tension at apical E-cadherin junctions. Mol Biol Cell 26(7): 1249-1262.
  7. Grashoff, C., Hoffman, B. D., Brenner, M. D., Zhou, R., Parsons, M., Yang, M. T., McLean, M. A., Sligar, S. G., Chen, C. S., Ha, T. and Schwartz, M. A. (2010). Measuring mechanical tension across vinculin reveals regulation of focal adhesion dynamics. Nature 466(7303): 263-266.
  8. Lecuit, T. and Yap, A. S. (2015). E-cadherin junctions as active mechanical integrators in tissue dynamics. Nat Cell Biol 17(5): 533-539.
  9. Leerberg, J. M., Gomez, G. A., Verma, S., Moussa, E. J., Wu, S. K., Priya, R., Hoffman, B. D., Grashoff, C., Schwartz, M. A. and Yap, A. S. (2014). Tension-sensitive actin assembly supports contractility at the epithelial zonula adherens. Curr Biol 24(15): 1689-1699.
  10. Michael, M., Meiring, J. C., Acharya, B. R., Matthews, D. R., Verma, S., Han, S. P., Hill, M. M., Parton, R. G., Gomez, G. A. and Yap, A. S. (2016). Coronin 1B reorganizes the architecture of F-Actin networks for contractility at steady-state and apoptotic adherens junctions. Dev Cell 37(1): 58-71.
  11. Priya, R. and Gomez, G. (2013). Measurement of junctional protein dynamics using fluorescence recovery after photobleaching (FRAP). Bio-Protocol 3: e937.
  12. Priya, R., Gomez, G. A., Budnar, S., Verma, S., Cox, H. L., Hamilton, N. A. and Yap, A. S. (2015). Feedback regulation through myosin II confers robustness on RhoA signalling at E-cadherin junctions. Nat Cell Biol 17(10): 1282-1293.
  13. Ratheesh, A., Gomez, G. A., Priya, R., Verma, S., Kovacs, E. M., Jiang, K., Brown, N. H., Akhmanova, A., Stehbens, S. J. and Yap, A. S. (2012). Centralspindlin and α-catenin regulate Rho signalling at the epithelial zonula adherens. Nat Cell Biol 14(8): 818-828.
  14. Salbreux, G., Charras, G. and Paluch, E. (2012). Actin cortex mechanics and cellular morphogenesis. Trends Cell Biol 22(10): 536-545.
  15. Smutny, M., Behrndt, M., Campinho, P., Ruprecht, V. and Heisenberg, C. P. (2015). UV laser ablation to measure cell and tissue-generated forces in the zebrafish embryo in vivo and ex vivo. Methods Mol Biol 1189: 219-235.
  16. Wu, S. K., Gomez, G. A., Michael, M., Verma, S., Cox, H. L., Lefevre, J. G., Parton, R. G., Hamilton, N. A., Neufeld, Z. and Yap, A. S. (2014). Cortical F-actin stabilization generates apical-lateral patterns of junctional contractility that integrate cells into epithelia. Nat Cell Biol 16(2): 167-178.
  17. Yonemura, S., Wada, Y., Watanabe, T., Nagafuchi, A., and Shibata, M. (2010). α-Catenin as a tension transducer that induces adherens junction development. Nat Cell Biol 12: 533-542.


皮质肌动球蛋白细胞骨架在所有非肌肉细胞中发现,其中关键功能是控制机械力(Salbreux等人,2012)。当与E-钙粘蛋白细胞粘附相结合时,皮层肌动蛋白产生连接性张力,影响组织功能,组织和形态发生的许多方面(Lecuit和Yap,2015)。揭示连接张力生成所依赖的分子机制需要用于在活细胞中测量具有高时空分辨率的工具。为此,我们设计了一种激光烧蚀技术,其中我们使用双光子激光器的高功率输出来在E-cadherin-GFP标记的细胞粘附部位物理切割肌动蛋白皮质。因此,张力可视化为在切割/切割之后定义连接点的顶点的向外反冲。后坐力与时间的分析允许提取与消融之前施加到接合处的收缩力量(初始反冲)相关的参数以及连接的弹性与连接皮层浸入的介质(细胞质)的粘度之间的比率。使用这种方法,我们发现Src蛋白酪氨酸激酶(Gomez等人,2015);肌动蛋白结合蛋白如原肌球蛋白(Caldwell等,2014)和N-WASP(Wu等人,2014); Myosin II(Priya等人,2015)和coronin-1B(Michael等人,2016)有助于负责在细胞细胞产生张力的分子装置路口该协议描述了用于设置激光烧蚀实验的实验程序,以及如何优化消融和采集条件以实现连接张力的最佳测量。它还提供了评估收缩力变化以及细胞弹性和/或细胞质粘度所需的后采集分析的完整描述。

背景 通过各种显微镜方法已经揭示了接合处的物理张力。这些包括激光消融(Ratheesh等人,2012; Smutny等人,2015; Michael等人,2016),光学镊子(Bambardekar等人,2015),FRET张力传感器(Grashoff等人,2010; Borghi等人,2012; Conway et al,2013; Leerberg等人,2014)和在张力下显示的蛋白质表位的免疫荧光(Yonemura等,2010, )。其中,激光烧蚀已经成为最流行的方法,因为与其他方法(例如,FRET或免疫荧光)相比,容易实现并提供机械张力的直接测量,其中机械张力的证据是更间接)。然而,需要特别考虑设立这些实验及其分析,这对于正确的结果解释很重要。该协议提供了在融合单层上皮细胞中激光烧蚀实验的设置和优化所需的基本步骤,以及用于测量消融后初始反冲的图像分析程序的完整描述,其是连接张力的指标。

关键字:激光烧蚀, 张力, 细胞间连接, 双光子, 粘弹性, 上皮细胞


  1. 来自ATCC的MCF-7或Caco-2细胞
    注意:该方案可以容易地扩展到任何其他内皮细胞或上皮细胞系,具有明确定义的细胞 - 细胞连接,如AML12细胞。
  2. 质粒(或慢病毒)表达连接标记物,如E-钙粘蛋白-GFP。
    Priya和Gomez(2013)参阅Bio-protocol e937,用于在内源性人E-钙粘蛋白敲低细胞中表达小鼠E-钙粘蛋白-GFP的慢病毒制剂。在该方案中,我们描述了用于过表达E-钙粘蛋白-GFP的细胞的转染
  3. 编码E-cadherin-GFP(Addgene,目录号:67937)或任何其它连接蛋白如ZO-1(Addgene,目录号:30313),纽蛋白(Addgene,目录号:30312),MRLC(Addgene,catalog编号:35680)或肌动蛋白标记Utrophin(Addgene,目录号:26737)
  4. Lipofectamine 3000和P3000试剂(Thermo Fisher Scientific,Invitrogen TM,目录号:L3000015)
  5. Dulbecco改良的Eagle中等高葡萄糖与稳定的L-谷氨酰胺(DMEM)(Thermo Fisher Scientific,Gibco TM,目录号:11995-073)
  6. 胎牛血清(FBS)(Thermo Fisher Scientific,Gibco TM,目录号:26140079)
  7. 不含Ca 2+的PBS和Mg 2+(Astral Scientific,目录号:09-8912-100)
  8. Opti-MEM介质(Thermo Fisher Scientific,Gibco TM ,目录号:31985070)
  9. 汉克平衡盐溶液(HBSS)(Sigma-Aldrich,目录号:H8264)
  10. CaCl 2
  11. 成像媒体(见配方)


  1. 激光扫描共焦显微镜,LSM 510 Meta Zeiss共焦显微镜(Zeiss,Jena,Germany)配备:
    可调谐双光子激光器(700-1100nm,> 2,000mW功率,Chameleon Laser,Coherent Inc.)
    30 mW氩激光(458,48和514 nm激光线)
    一个60x的目标,1.4 NA油计划疏散(蔡司)浸没镜头
  2. 玻璃底盘,1.5号盖片(直径35mm,MATTEK,目录号:P35G-1.5-20-C或29mm直径,Shengyou Biotechnology,目录号:D29-10-1.5-N)


  1. ImageJ软件( https://imagej.nih.gov/ij/
  2. 斐济软件( http://imagej.net/Fiji
  3. MTrackJ pluging( http://www.imagescience.org/meijering/software/mtrackj/manual/
  4. Microsoft Excel( https://products.office.com/en-au/excel
  5. GraphPad PRISM软件( http://www.graphpad.com/scientific -software/prism/


  1. 细胞制备
    GFP标记的蛋白质标记细胞 - 细胞连接的表达可以通过使用基因组编辑工具如CRISPR,病毒转导(参见Priya和Gomez,2013)或者编码连接蛋白融合的质粒的瞬时转染来内源性标记感兴趣的基因来实现使用Lipofectamine 3000,如下所述(参见附录I )。
    1. 用E-钙粘蛋白-GFP构建体电镀和转染细胞
      1. 对于消融实验,将MCF-7细胞在补充有10%FBS的DMEM中培养并用编码E-钙粘蛋白-GFP的质粒转染。
      2. 细胞在37℃下在DMEM + 10%FBS中孵育,当通过胰蛋白酶消化收集约80%汇合液时。
      3. 将单细胞悬液以75%汇合接种在玻璃底层培养皿上,并允许使用Lipofectamine 3000用质粒转染24小时进行转染。
      4. 在转染当天,在不存在血清和抗生素的情况下将细胞培养基更换为Opti-MEM(1ml),并按照附录I
      5. 在转染后24至48小时,一旦细胞90至100%融合,洗涤细胞并在成像介质存在下孵育显微镜分析。图1显示了使用60倍放大率的消融前细胞形态的代表性图像 注意:使用成像介质,因为它不具有酚红,可通过增加荧光背景干扰活细胞成像。这导致使用更高的激光功率进行成像和产生可能对细胞有毒的反应物种。


  2. 图像采集
    1. 对于使用多光子激光器,请仔细阅读与其使用相关的安全注意事项(附录IV
    2. 对于反冲测量,请确保分析具有一致水平的E-钙粘蛋白-GFP构建体的细胞。理想的过表达水平应该保持在最低限度以防止过度表达伪像(另见附录I ),并与活细胞成像兼容。
    1. 一旦识别出目标细胞,在(2帧)之前和之后(5帧)获得感兴趣的区域中的GFP荧光的延时图像为270×270像素,0.1860119μm/像素(在4倍数字变焦,0.8μm光学部分) ,或直到观察不到连接长度的更多变化,〜1分钟)。以1-3%透射率的氩激光器(30mW)的488nm激光线以8秒的时间间隔采集总时间为44秒的图像(图2A和2B; 补充视频1 ; 附录II )。
      注意:该感兴趣的区域足以获得单个细胞 - 细胞连接以分析其消融后的长度变化,而不需要获取整个视野(512×512像素,图2A),其将减慢可以监测连接反冲的速度。
    2. 2.8×1.7μm的恒定感兴趣的区域,长轴平行于细胞 - 细胞接触(图2A)被标记为消融,使用30次迭代的变色龙激光器,其在790nm具有40%的透射率(参见补充视频1 附录II )。这导致了有效的消融而没有明显的细胞损伤(图2B,另见补充视频2 ,对于细胞损伤重要的情况)。

      图2.消融实验期间获取的感兴趣区域和消融前后结点的代表性静止图像。 A。用于激光消融的不同兴趣区域的方案和连接张力的测量; B.激光切割实验的电影静脉切片,以测量细胞细胞连接处的张力。黄线:激光消融前顶点的原始位置;红线:顶点的实时位置;箭头:消融部位。

  3. 激光功率的优化和消融步骤的迭代(参见附录V )。
    1. 为了建立这个优化步骤,必须从在它们的连接点处具有张力的细胞开始,因为成功的消融将导致连接点的可观察到的伸长,即,定义它的顶点的反冲(补充影片1 ,<一个class ="ke-insertfile"href ="http://en.bio-protocol.org/attached/file/20161130/20161130212644_8538.docx"target ="_ blank"> 2 和 4 )。
    2. 在实践中,使用大量迭代(> 20并且如果需要增加更多)和高激光功率(约70%,如果需要增加更多)进行消融设置的初始测试。在这些恶劣条件下,应该观察到明显的细胞损伤,这将显示出红外激光的激光功率是有效的,并且它被正确地准直(参见附录III 补充视频3 )。
    3. 一旦达到此目的,可以获得细胞膜损伤最小的设置。这可以通过在表达细胞质mCherry的细胞和不具有细胞质的细胞之间进行另外的控制来消除结合(标记为顶端连接标记)。
      在这些条件下,应该可以进行消融实验,其中观察到可观察的反冲,但是没有观察到从一个细胞到另一个细胞的mCherry荧光的显着流动(参见补充视频2  和 3 )。
    4. 此外,通过GFP荧光图像获取DIC图像,可以检查激光功率是否不会太高,造成损害。


  1. 图像分析
    1. 测量顶点之间的距离随时间的变化
      1. 一次在ImageJ软件中打开获得的延时图像(每个实验每个条件为n = 15 - 25)。如果在每个时间点获取Z-stack,则图像噪声较大时,应使用中值滤波器(1像素),并应用最大投影。
      2. 使用MTrackJ插件来测量消融后的细胞 - 细胞结的应变或变形ε(t)作为时间的函数。特别是,使用这个插件,我们跟踪定义消融结点随时间推移的每个顶点的XY坐标(参见位于 http://www.imagescience.org/meijering/software/mtrackj/manual/)。然后,将X和Y值复制到Excel表中。对于每个烧蚀点,我们将获得4列:X(上),Y(顶),X(底)和Y(底部)和n行,其中n是电影中存在的时间点数(从6到20,取决于系统到达高原的速度)。
    2. 使用由MTrackJ插件生成的跟踪数据,计算每个时间点t的联系人L(t)的长度为:

             L(t)= sqrt((Xtop(t) - Xbottom(t))^ 2 +(Ytop(t) - Ybottom(t))^ 2)   ;      (方程2)

    3. 然后在每个时间点(行)处测量消融后的反冲或应变ε(t)的量作为任何时间[L(t)]与消融前接触长度之间的接触长度之间的差值[L (0)]
            ( t )= L t ) - L (0)          (等式3)

    4. 图3示出了使用等式3.绘制20次消融的平均后坐值(另见补充文件1)。

      图3.在时间= 0时ε(t),顶点分离减去顶点分离的记录。图是分析的20个连接点的平均值。误差棒是±SEM(参见补充文件1)。

  2. 数据拟合:提取初始反冲和k值
    原理:在消融实验的时间尺度内,如果连接应变在消融后表现出具有确定的平台的单一指数生长,则可以将其建模为开尔文 - Voigt纤维(Fernandez-Gonzalez等人,2009)通过将其拟合到以下等式

    F <0>是存在于消融之前的结处的拉伸力,
    μ是与细胞质粘性阻力相关的粘度系数 作为上述方程的拟合参数,我们引入了

    1. 从拟合结果可以提取两个量:初始反冲,这是消融前接头处的潜在收缩张力的测量值,k值是介质的连接弹性和粘度之间的比值。
      注意:当在不同的条件下进行烧蚀时,初始后坐力的变化,而不是k值的变化强烈地表明交界处的张力受到影响。相比之下,初始反冲和k值的同时变化更难解释。对于最后一种情况,首先需要对细胞细胞连接处的物理张力(即力的量)进行推断以获得连接弹性(或刚度)的独立测量。这可以例如使用原子力显微镜或光学镊子来完成。然后使用弹性值或刚度值从激光烧蚀实验μ= values获得的k值计算μ。然后,以这种方式获得的μ值,即使在弹性和/或粘度的条件下,也可以计算消融前的细胞 - 细胞结上的平均力量(F <0> =初始反冲*μ)被修改。
      反冲数据的拟合(等式3)可以使用GraphPad PRISM软件完成。图4-14中显示的快照的文件被提供为补充文件1 。要开始分析,首先创建一个新的XY表项目,其中输入复制Y(n = 20到30)值并为每个时间点绘制(图4)。

      图4. GraphPad PRISM对话窗口的快照,用于创建用于分析连接反冲数据的新XY项目

    2. 然后将Excel中获得的ε(t)值(方程3,参见图像分析部分的步骤A1-A4)粘贴到GraphPad PRISM表中(图5,另见数据表:补充文件1 与...一起提供这个协议)。

      图5.包含来自实验的反冲数据的XY表的快照。 X列包含获取图像的时间(以秒为单位)的值。时间= 0秒对应于消融前获取的时间点。 Y分量对应于从控制单元(等式3)导出的ε(t)数据,该数据分组在A组内。值A:Y1,A:Y2,A:Yn对应于来自单个结的反冲值被烧了另见补充文件1

    3. 使用该软件通过插入→现有数据的新图→平均值±SEM绘制平均ε(t)值(图6)。

      图6. GraphPad PRISM中的'创建新图形"窗口的快照,用于绘制回冲结果

    4. 然后通过转到"非线性"按钮执行拟合(图7)。这将打开一个具有不同选项的新窗口,以使用已经可用的方程式或创建拟合数据的新方程式。请注意,对于以下步骤,可以使用GraphPad Prism阅读有关非线性回归的一般准则: http://www.graphpad.com/guides/prism/7/curve-fitting/index.htm?reg__curve_fitting_with_prism_6 .htm

      图7. GraphPad PRISM软件中拟合分析选项的快照

    5. 在新的对话窗口中,创建一个新的拟合方程(图8)

      图8. GraphPad Prism软件中的非线性拟合菜单的快照

    6. 在"公式"菜单中(见图9的顶部)

      图9.在GraphPad PRISM的非线性函数中添加初始反冲测量方程

      1. 为新方程分配名称,例如"激光纳米刀"。
      2. 在"定义"字段中粘贴以下公式:

        Y =(initialrecoil/K)*(1-exp [-K * x])(另见图9)

      3. 然后,在同一窗口中进入下一个选项卡"初始值规则",并为拟合参数的初始值选择以下条件(图10)。
      4. 转到"默认约束"选项卡,为拟合参数初始反冲和k分配大于零的值(图11)。
      5. 清除要在此窗口的最后一个选项卡中报告的任何转换(转换为报告,图12)。这些分析不再需要。
      6. 按"确定"按钮接受所有更改。
      7. 拟合数据(最小二乘法和未知数插值)。您将获得具有配件结果的表(图13)。

        图10."GraphPad PRISM"非线性回归菜单中的反冲测量参数的初始值规则



        图13.来自反冲数据的非线性回归的结果的快照,显示初始反冲和k 的值

      8. 将结果复制到不同的"初始反冲"(3 rd 行,另见图13)和'k'值(4 th 行结果)其标准错误(分别为SD,第6和第7行),并将它们粘贴到GraphPad PRISM中的另一个工作表中(参见补充文件1 ,另见图14)。从那里可以计算来自不同条件和独立实验(不同日期)的初始反冲和k值的平均值,并在这些实验之间进行统计测试,以评估反冲速度的差异(即,张力) 。

        图14.具有初始反冲值的表及其从反冲数据的非线性回归分析获得的错误。这里将数据粘贴到GraphPad PRISM文件中的新分组表中(另见此PRISM文件作为补充文件1 提供;对于此协议)。

      9. 从上述模型可以看出,假设粘度在它们之间没有显着差异,可以通过比较不同条件下的初始反冲值来估计出现在接合处的拉伸力的差异。为了评估这些假设在这些实验中是否有效,计算不同条件之间的速率常数k是非常重要的,因为如果接头的粘度或弹性明显改变,这将会发生变化。在不同实验条件(通过测试或单向方差分析评估)之间,k值没有显着变化表明,拉力的变化是初始反冲速度变化的主要贡献者。 >


  1. 成像媒体
    Hank的平衡盐溶液补充有10mM HEPES pH 7.4和5mM CaCl 2


该协议改编自我们实验室(Ratheesh等人,2012; Michael等人,2016)的先前工作。在IMB/ACRF癌症生物学成像设施下进行共聚焦显微镜检查,并在澳大利亚癌症研究基金会的大力支持下建立。我们还感谢John Griffin和Darren Paul就使用脉冲激光器的安全考虑提供了建议。


  1. Bambardekar,K.,Clement,R.,Blanc,O.,Chardes,C.and Lenne,P.F。(2015)。 直接激光治疗揭示体内细胞接触的机制。  Proc Natl Acad Sci USA 112(5):1416-1421。
  2. Borghi,N.,Sorokina,M.,Shcherbakova,O.G.,Weis,W.I.,Pruitt,B.L.,Nelson,W.J。和Dunn,A.R。(2012)。 E-钙粘蛋白是由组成型肌动球蛋白引起的紧张在外部应用拉伸时细胞间接触增加。美国Proc Natl Acad Sci USA 109(31):12568-12573。
  3. Caldwell,B.J.,Lucas,C.,Kee,A.J.,Gaus,K.,Gunning,P.W.,Hardeman,E.C.,Yap,A.S。和Gomez,G.A。(2014)。 原肌球蛋白异构体支持肌动球蛋白生物发生以在上皮粘连附着物产生收缩张力。  细胞骨架(Hoboken) 71(12):663-676。
  4. Conway,D.E.,Breckenridge,M.T.,Hinde,E.,Gratton,E.,Chen,C.S。和Schwartz,M.A。(2013)。 内皮细胞上的流体剪切应力调节VE-钙粘蛋白的机械张力, PECAM-1。  Curr Biol 23(11):1024-1030。
  5. Fernandez-Gonzalez,R.,Simoes Sde,M.,Roper,J.C.,Eaton,S.and Zallen,J.A。(2009)。 肌球蛋白II的动力学受插入细胞的张力调节。 >  Dev Cell 17(5):736-743。
  6. Gomez,GA,McLachlan,RW,Wu,SK,Caldwell,BJ,Moussa,E.,Verma,S.,Bastiani,M.,Priya,R.,Parton,RG,Gaus,K.,Sap,亚普(ASAP)(2015)。 RPTPα/Src家族激酶/Rap1信号传导模块招募肌球蛋白IIB支持根尖E-钙粘蛋白连接处的收缩张力。分子生物细胞 26(7):1249-1262。
  7. Grashoff,C.,Hoffman,B. D.,Brenner,M. D.,Zhou,R.,Parsons,M.,Yang,M.T.,McLean,M.A.,Sligar, S.G.,Chen,C.S.Ha,T.and Schwartz,M.A。(2010)。 测量长春新碱的机械张力显示了粘连动力学的调节。 a>  Nature 466(7303):263-266。
  8. Lecuit,T.和Yap,A.S。(2015)。 E-cadherin结作为组织动力学中的积极机械整合者。一个>  Nat Cell Biol 17(5):533-539。
  9. Leerberg,J.M.Gomez,G.A.,Verma,S.,Moussa,E.J.,Wu,S.K.,Priya,R.,Hoffman,B.D.,Grashoff,C.,Schwartz,M.A。和Yap,A.S。(2014)。 张力敏感肌动蛋白组件支持上皮粘连附着物的收缩。/a>  Curr Biol 24(15):1689-1699。
  10. Michael,M.,Meiring,J.C.,Acharya,B.R.,Matthews,D.R.,Verma,S.,Han,S.P.,Hill,M.M.,Parton,R.G.,Gomez,G.A。和Yap,A.S。(2016)。 Coronin 1B将稳定的F-Actin网络的架构重新整理为收缩性 - 状态和凋亡的粘附点。  Dev Cell 37(1):58-71。
  11. Priya,R.和Gomez,G。(2013)。 使用光漂白后的荧光恢复(FRAP)测量连接蛋白动力学。生物协议 3:e937。
  12. Priya,R.Gomez,G.A.,Budnar,S.,Verma,S.,Cox,H.L.,Hamilton,N.A。和Yap,A.S。(2015)。 通过肌球蛋白II的反馈调节赋予E-钙粘蛋白RhoA信号的鲁棒性交界处。  Nat Cell Biol 17(10):1282-1293。
  13. Ratheesh,A.Gomez,G.A.,Priya,R.,Verma,S.,Kovacs,E.M.,Jiang,K.,Brown,N.H.,Akhmanova,A.,Stehbens,S.J。和Yap,A.S。(2012)。 Centralspindlin和α-catenin调节上皮粘附的Rho信号传导。 Nat细胞生物学 14(8):818-828。
  14. Salbreux,G.,Charras,G.and Paluch,E。(2012)。 肌动蛋白皮层力学和细胞形态发生。 趋势细胞周期22(10):536-545。
  15. Smutny,M.,Behrndt,M.,Campinho,P.,Ruprecht,V.and Heisenberg,C.P。(2015)。 紫外激光消融测量斑马鱼中的细胞和组织产生的力量胚胎体内和体外  Methods Mol Biol 1189:219-235。
  16. Wu,S.K.,Gomez,G.A.,Michael,M.,Verma,S.,Cox,H.L.,Lefevre,J.G.,Parton,R.G.,Hamilton,N.A.,Neufeld,Z.and Yap,A.S。(2014)。 皮质F-肌动蛋白稳定产生连接收缩的顶端 - 侧向模式,将细胞整合到上皮细胞中。  Nat Cell Biol 16(2):167-178。
  17. Yonemura,S.,Wada,Y.,Watanabe,T.,Nagafuchi,A.,and Shibata,M。(2010)。 α-Catenin作为张力传感器诱导粘附连接发育。  Nat Cell Biol 12:533-542。
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引用:Liang, X., Michael, M. and Gomez, G. A. (2016). Measurement of Mechanical Tension at cell-cell junctions using two-photon laser ablation. Bio-protocol 6(24): e2068. DOI: 10.21769/BioProtoc.2068.