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JoVE Journal Bioengineering

Bioengineering

Measurement of Force-Sensitive Protein Dynamics in Living Cells Using a Combination of Fluorescent Techniques

Published: November 2, 2018 doi: 10.3791/58619
Automatic Translation
1, 1, 1
1Department of Biomedical Engineering, Duke University

Summary

Here, we present a protocol for the simultaneous use of Förster resonance energy transfer-based tension sensors to measure protein load and fluorescence recovery after photobleaching to measure protein dynamics enabling the measurement of force-sensitive protein dynamics within living cells.

Abstract

Cells sense and respond to physical cues in their environment by converting mechanical stimuli into biochemically-detectable signals in a process called mechanotransduction. A crucial step in mechanotransduction is the transmission of forces between the external and internal environments. To transmit forces, there must be a sustained, unbroken physical linkage created by a series of protein-protein interactions. For a given protein-protein interaction, mechanical load can either have no effect on the interaction, lead to faster disassociation of the interaction, or even stabilize the interaction. Understanding how molecular load dictates protein turnover in living cells can provide valuable information about the mechanical state of a protein, in turn elucidating its role in mechanotransduction. Existing techniques for measuring force-sensitive protein dynamics either lack direct measurements of protein load or rely on the measurements performed outside of the cellular context. Here, we describe a protocol for the Förster resonance energy transfer-fluorescence recovery after photobleaching (FRET-FRAP) technique, which enables the measurement of force-sensitive protein dynamics within living cells. This technique is potentially applicable to any FRET-based tension sensor, facilitating the study of force-sensitive protein dynamics in variety of subcellular structures and in different cell types.

Introduction

The extracellular environment is a rich source of both biochemical and physical cues that dictate cell behavior. In particular, the physical nature of the microenvironment can mediate key cellular functions, including cell growth, migration, and differentiation1,2,3,4. Dysregulation of the mechanics of the microenvironment is a critical component to many diseases that do not yet have adequate treatments, such as cancer5, atherosclerosis6, and fibrosis7. A complete understanding of how cells convert physical stimuli into biochemically-detectable signals, a process termed mechanotransduction, requires the elucidation of the molecular mechanisms mediating force transmission, both into and out of the cells and within multiple subcellular structures.

Inside subcellular structures, proteins are constantly turning over; binding and unbinding based on the strength of their interactions with binding partners8. For forces to be successfully transmitted across a physical distance, there must be an unbroken chain of protein-protein interactions, meaning that a protein's turnover must be slow enough to sustain and transmit force to its binding partner9. While protein-protein interactions generally consist of several non-covalent bonds between the protein domains, the interaction is often conceptualized as a bound state that can transition to an unbound state under different conditions10,11. For a given protein-protein interaction, it is possible that force can have no effect on the lifetime of the interaction, known as an "ideal bond", reduce the lifetime of the interaction, known as a "slip bond", or increase the lifetime of the interaction, known as a "catch bond"10. Thus, there is an intricate relationship between protein load and protein dynamics, which we refer to as force-sensitive dynamics.

Towards understanding the effect of load on bond dynamics, a number of highly informative experiments have been performed on the single-molecule level. Using isolated proteins, or fragments of proteins and manipulation techniques such as magnetic tweezers, optical tweezers, and atomic force microscopy, these studies have demonstrated force-sensitive protein-protein interactions for several relevant proteins11,12. Both integrins13 and cadherins14, which are transmembrane proteins important for forming cell-matrix and cell-cell interactions, respectively, have demonstrated alterations in dynamics due to load. Within the cell, vinculin is recruited to both talin15 and α-catenin16 in a force-dependent manner and can form a catch bond with actin17, indicating a crucial role for vinculin at both focal adhesions (FAs) and adherens junctions (AJs) under load. Single-molecule studies allow for the isolation of specific protein-protein interactions and yield unambiguous results, but they do not account for the complexity of the cellular environment.

Landmark experiments demonstrated that several subcellular structures, including FAs and AJs, are mechanosensitive, and exhibit enhanced assembly in response to internally-generated or externally-applied loads18,19,20,21,22. Additionally, several theoretical models have suggested that mechanosensitive assembly could be driven by force-sensitive protein dynamics23,24,25. To examine these force-sensitive dynamics within living cells, a few indirect approaches have been taken. FRAP and related techniques provide a relatively simple methodology for measuring protein dynamics in cells26,27,28,29. However, the measurement of protein load has been more limited. A typical approach is to compare protein dynamics in cells with and without the exposure to a cytoskeletal inhibitor used to reduce overall cell contractility8,30,31. Conceptually, this is a comparison between a high load and low load state. However, there is no quantification of the load across the protein in either state, and there may be unintended biochemical effects of the inhibitor, such the loss of key binding sites along an F-actin filament. Another approach, specific to FAs, has been to measure total force exertion on the substrate by the FA using traction force microscopy to approximate molecular load and examine the relationship with the dynamics of a single protein within the FA32. While this approach allows for the quantification of total force, it does not provide molecularly specific information. FAs are made up of over 200 different proteins, many of which can bear load33. Thus, measuring the total force output of an FA potentially obscures the possibility of multiple force transmission pathways and does not reliably provide a measure of load on a specific protein.

Unlike previous approaches in mechanobiology, the advent of FRET-based tension sensors allows direct measurement of loads experienced by specific proteins inside living cells34,35,36. Here, we present a protocol that combines FRET-based tension sensors with FRAP-based measure of protein dynamics. We refer to this technique as FRET-FRAP. This approach enables the simultaneous measurement of protein load and protein dynamics, thus allowing the assessment of the force-sensitive protein dynamics in living cells (Figure 1). Already, the FRET-FRAP technique has been applied to the study of the force-sensitive dynamics of the mechanical linker protein vinculin37. Tension sensors have been developed for numerous proteins that are relevant in a variety of subcellular structures. For example, sensors have been developed for vinculin34 and talin38,39 in FAs, cadherins and catenins in AJs40,41,42, nesprin in the nuclear LINC complex43, α-actinin44 and filamin36 in the cytoskeleton, and MUC-1 in the glycocalyx45, among others46. Similarly, FRAP is a commonly used technique has been used on mechanosensitive proteins within the focal adhesions8,31, adherens junctions47, actin cortex26, and nucleus48. Moving forward, the FRET-FRAP technique should be broadly applicable to any of these existing sensors or newly developed sensors, allowing for the measurements of force-sensitive dynamics in a wide variety of subcellular structures and contexts. Towards this end, we provide a detailed, generalized protocol for implementing the FRET-FRAP technique applicable in these different systems. Hopefully, this will enable a wide variety of experiments elucidating the roles of various mechanosensitive proteins in regulating force transmission and in mediating cell behavior.

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Protocol

1. Generate Samples for Imaging

  1. Stably express tension sensor construct in desired cell type.
    1. Clone tension sensor construct into pRRL vector or other viral expression plasmid.
      NOTE: Several different molecular cloning tools are available to achieve this step including the use of restriction enzymes, overlap extension, and Gibson Assembly35. The pRRL vector is used in lenti viral transduction and enables a substantial degree of protein production through the use of the human cytomegalovirus (CMV) promoter. Different vectors may be needed for a particular context. For instance, the CMV promoter is silenced in some cell types49. Additionally, only FRET-based sensors containing fluorescent protein that lack strong sequence homology, such as mTFP1 and Venus A206K, can be used to create stable cell lines. Sensors containing cyan fluorescent protein and yellow fluorescent protein will likely be subject to homologous recombination50.
    2. Generate lentivirus in Human Embryonic Kidney (HEK) 293T cells using psPax2 and pMD2.G packaging plasmids using standard virus production methods51.
      CAUTION: Lentivirus should only be handled by properly trained personnel in a biosafety level 2 laboratory environment.
      NOTE: This combination of cells and packaging plasmids is appropriate for use with pRRL. Other systems may be required with other vectors.
    3. Transduce desired cells with virus using standard transduction protocols52 and use flow cytometry to sort cells53 selecting a homogenous population expressing each construct at approximately endogenous levels37. After the cell selection, experiments can be conducted immediately, or cells can be cryogenically frozen for later use. Do not exceed 2 freeze-thaw cycles for a given stable cell line.
      NOTE: The use of cell lines deficient in the protein to be studied (e.g., vinculin -/- MEFs for the use with the vinculin tension sensor) will increase the signal to noise ratio in FRET experiments as well as limit over-expression artifacts. Such stable mouse embryonic fibroblast (MEF) lines can be used for approximately 15 passages before significant loss of expression or degradation of sensors is apparent. If viral based methods are not desired, a plethora of commercial reagents can be used according to the manufacturer’s protocol to transiently transfect a variety of cell types with tension sensors in an appropriate plasmid, such as pcDNA3.1. Optimal expression will be 24-48 h following transfection.
  2. Prepare substrates for cell seeding.
    1. Acquire 4, 35 mm glass-bottomed dishes.
    2. Working in a cell culture hood, in a 15 mL canonical tube, make 4 mL of 10 µg/mL fibronectin in phosphate-buffered saline (PBS) solution using sterile PBS in the cell culture hood. Gently invert the tube once to mix and let the solution sit for 5 min in the cell culture hood.
      NOTE: The concentration or type of ECM protein may have to be adjusted for other cell types. The conditions provided are suitable for MEFs.
    3. Pipette 1 mL of fibronectin solution onto each glass-bottomed dish.
    4. Leave the fibronectin solution on the dishes for 1 h at room temperature or overnight at 4 °C.
    5. Aspirate the fibronectin solution, rinse once with PBS, and add 1 mL of PBS.
  3. Seed the cells onto prepared substrates.
    1. Start with the cells of interest at a confluence percentage appropriate for subcultivation in a 6 cm culture dish.
      NOTE: Different cell types will require distinct cell culture conditions and subcultivation protocols. This section provides guidelines suitable for MEFs. Typically, MEFs are grown to 85% confluence before subcultivation.
    2. Working within a cell culture hood, rinse the cells once with 3 mL of PBS. Add 1 mL of 0.05% Trypsin-EDTA and incubate for 5 min at 37 °C.
    3. Add 3 mL of complete media to the 6 cm dish, collect the cells, and place into a 15 mL conical tube.
      NOTE: Composition for complete media will depend on the cell type being used. For MEFs, complete media is often defined as high glucose Dulbecco's Modified Eagle Medium with 10% fetal bovine serum, 1% Antibiotic-Antimycotic (containing Amphotericin B, Penicillin, and Streptomycin), and a 1% non-essential amino acid (NEAA) solution.
    4. Spin the cells down at 1000 x g for 5 min.
    5. Aspirate the media and resuspend the cell pellet in 1 mL of complete media.
    6. Remove PBS from fibronectin-coated glass dishes. Count the cells and seed 30,000 cells onto each fibronectin-coated glass dish with the appropriate complete media for a final volume of 1.5 mL.
      NOTE: This cell density is appropriate for MEFs and will lead to a population of cells that are not touching, but not exceedingly sparse. The exact cell number may need to be adjusted for other cell types or other imaging chamber.
    7. Allow the cells to spread for 4 h following seeding. At 2 h of spreading, aspirate the growth media, and rinse once with imaging media, leaving 1.5 mL of imaging media.
      NOTE: This spreading time is appropriate for MEFs but may need to be altered for other cells. However, incubation periods of longer than 6-8 h will lead to the significant deposition of ECM protein from serum in the complete media. Imaging media should contain the same additions as complete media but should be optically clear and not contain any compounds that fluoresce in imaging channels, such as flavins, or quench fluorescence, such as phenol red. A generally useful imaging media is DMEM-gfp Live Cell Visualization media supplemented with 10% FBS and 1% NEAA solution. If background autofluorescence is unacceptably high, then the amount of serum can be reduced. If a media change is not possible after the initial plating, the cells can be directly resuspended in imaging media supplemented with a trypsin inhibitor.

2. Set up Microscope for Imaging

  1. Turn on the microscope.
    1. Turn on the arc lamp first.
      NOTE: An arc lamp will release an electromagnetic pulse, which can damage other equipment that is already on.
    2. Turn on the filter wheel controller, automated stage controller, microscope-computer interface, and camera.
    3. Turn on the FRAP laser and laser position controllers.
      CAUTION: High-powered lasers can be damaging to eyes if directly viewed. It is recommended to configure the microscope system to block laser excitation from being directed to the eye pieces, which can be accomplished by moving a mirror into the FRAP beam path during bleaching to reflect the laser toward the sample and prevent transmission to the eyepiece.
    4. Turn on the computer and open microscope control software.
    5. Allow 15 min for the arc lamp and FRAP laser to warm up.
  2. Calibrate the FRAP laser.
    1. Open the laser configuration window. Set Illumination Setting (during pulse) to the appropriate FRAP illumination settings for laser exposure to the sample. Set Illumination Setting (during imaging) to the illumination settings appropriate for imaging only the acceptor fluorophore.
    2. Select the objective to calibrate under Coordinate System Setting. Uncheck Manually Click Calibration Points and check Display images during calibration.
    3. Set the Dwell time to 10,000 µs and the number of pulses to 100.
    4. Place the calibration slide, made of ethidium bromide sealed between a glass slide and a coverslip, into the stage adaptor with the coverslip side down.
      CAUTION: Ethidium bromide is a mutagen and should be handled using gloves. If the slide is compromised, dispose of according to the institution’s guidelines.
    5. Use the acceptor illumination settings to focus on the surface of the slide, identifiable as the focal plane with the brightest signal. Small defects in the coating will be visible to aid in focusing.
    6. Move the slide to an area with uniform fluorescence across the imaging plane.
    7. Click on Create Setting. The software will initialize the calibration process, automatically bleaching and detecting the position of the bleached point.
    8. Ensure successful calibration by assessing the final image, which will be a 3 x 3 grid of bleached points that should be evenly distributed and in focus. Save the calibration image for future reference.
    9. Remove the calibration slide and safely store. Calibration should be performed before beginning each experiment but does not need to be performed between samples.

3. Choose Parameters for FRET Imaging

  1. Fix one of the generated samples of the cells expressing the tension sensor with 4% paraformaldehyde for 10 min. Paraformaldehyde solution should be methanol free, often referred to as EM-grade, to prevent denaturing of fluorescent proteins. Place in PBS after fixation.
    CAUTION: Paraformaldehyde solutions are toxic. This step should be performed in a fume hood and the solution should be disposed of according to institutional policies.
    NOTE: This optimization does not depend on protein dynamics, and a fixed sample allows for maximum imaging time without worrying about cell health.
  2. Rinse the sample three times with PBS and leave in PBS.
    NOTE: Use of most commercially-available mounting media will affect fluorophore properties, making the sample unsuitable for FRET imaging54. Ideally, the cells will be imaged immediately, but may be left overnight at 4 °C. Longer wait times will result in deterioration of the sample.
  3. Place the sample into the microscope stage holder for imaging.
  4. Open the Multi-Dimensional Acquisition (MDA) tool. Establish a sequential imaging of three channels: acceptor only excitation and emission (acceptor channel), donor excitation and acceptor emission (FRET channel), and donor only excitation and emission (donor channel).
    NOTE: There are a variety of ways to image FRET samples. The three-channel or “three-cube” method of imaging paired with means of calibrating the system to measure FRET efficiency is recommended for FRET-based tension sensors55,56. This approach is fast, simple, nondestructive, requires only a standard fluorescence imaging microscope, and enables the comparison of experiments across different days and imaging setups.
  5. Scan the sample using an exposure time of 500 ms and a neutral density (ND) filter of 10%. Find a cell expressing the tension sensor with clear localization to a structure of interest.
  6. Select an exposure time of 500 ms or the desired length for each imaging channel and an ND filter of 100% and acquire a FRET image sequence.
  7. Estimate the average intensity of the sensor at the subcellular structures of interest in each imaging channel. Low signals may lead to inaccurate results due to improper correction estimates, non-linearities in detectors, or significant contribution of background signals. An approximate guideline is to aim for intensities above 10% of the dynamic range of the camera (i.e., for a 16-bit camera, intensities should be above 6,000).
    NOTE: Identical optical settings (exposure times, filters, objectives, and other variables such as camera gain or binning) must be used for all FRET experiments that will be compared. Changing any of these settings will lead to an alteration in the amount FRET that is either generated and/or detected in the microscopy set-up. FRET efficiency measurements are independent of these setting, but the calibration factors used to determine FRET efficiency are not. In theory, various sets of calibration factors could be used to generate FRET efficiencies from different optical settings, but this is not recommended. Bleaching or phototoxicity can be different between the various settings, creating spurious results.
  8. Acquire a second FRET image sequence of the same field of view. Estimate photobleaching between frames by comparing average intensity of the sensor in each imaging channel. Photobleaching should be kept to a minimum, preferably less than 1-5% loss of signal.
  9. Adjust the imaging parameters to maximize the intensity while minimizing photobleaching. For coarse adjustments, change the ND filter being used during acquisition. For finer adjustments, change the exposure time in steps of 250 ms.
  10. Repeat Steps 3.5 – 3.8 until adequate signal can be obtained while minimizing photobleaching.
    NOTE: Typically, settings for the vinculin tension sensor in vinculin -/- MEFs are 1,500 ms, 1,500 ms, and 1,000 ms for the donor, FRET, and acceptor channels respectively. The optimal values will vary with the type of illumination system, objective, filter sets, and sensor expression level.

4. Choose Parameters for FRAP Imaging

  1. Optimize the laser settings to ensure complete bleaching of the region of interest (ROI) without bleaching the surrounding area or causing photodamage.
    1. Fix one of the generated samples of the cells expressing the tension sensor with 4% paraformaldehyde for 10 min.
      NOTE: This optimization does not depend on protein dynamics, and a fixed sample allows for maximum imaging time without worrying about cell health. This will also prevent the recovery of bleaching by mobile proteins, allowing for the isolation of the effect of bleaching, avoiding any effects from rapid, diffusion-mediated fluorescence recovery occurring between the incidence of bleaching and taking the first post-bleach image.
      CAUTION: Paraformaldehyde solutions are toxic. This step should be performed in a fume hood and the solution should be disposed of according to institutional policies.
    2. Rinse the sample 3 times with PBS and leave in PBS.
      NOTE: The use of most commercially-available mounting media will affect fluorophore properties, making the sample unsuitable for FRAP imaging54. Ideally, the cells will be imaged immediately, but may be left overnight at 4 °C. Longer wait times will result in deterioration of the sample.
    3. Place the sample into the microscope stage holder for imaging.
    4. Open the laser configuration window. Start with setting a laser dwell time of 1,000 µs and 10 pulses, meaning that each spot in the scan across the ROI will receive 10,000 µs of full-power laser
      NOTE: A 500 mW, 515 nm laser was used for bleaching. This was chosen to selectively bleach Venus A206K, the acceptor in vinculin tension sensor, with maximal efficiency. If FRET-based tension sensors with other fluorescent proteins are used, another type of laser may have to be employed.
    5. Find a cell expressing the tension sensor with clear localization to a structure of interest and acquire an image.
    6. Draw a rectangular ROI outlining the area to bleach and store the ROI location. Pulse the laser. Snap another image of the sample.
      NOTE: The box size should be approximately the size of the entire FA. Care should be taken that the box size does not vary drastically across experiments. The bleached area must be carefully monitored in proteins whose dynamics are affected by diffusion. This is a potential concern in transmembrane proteins, such as cadherins47, or proteins that diffuse slowly27,57.
    7. Check the quality of photobleaching by checking that the entire ROI is bleached such that the intensity is near background levels. Additionally, make sure there is no bleaching outside of the ROI.
    8. Adjust the laser settings as needed to achieve a significant amount of bleaching within the ROI without inducing significant bleaching outside the ROI. For coarse adjustments, raise and lower the dwell time in steps of 100 µs, and for fine adjustments, raise and lower the number of pulses in steps of 5 pulses.
    9. Repeat Steps 4.1.5 – 4.1.8 until reaching the minimum settings at which the ROI is fully bleached without off-target photobleaching.
      NOTE: Achieving a substantial initial bleaching value without inducing phototoxicity is a key aspect of FRAP analysis. Use the laser settings that result in a complete bleach in the fixed samples. In general, the minimal number of photons should be used to achieve the desired bleaching level. Also, the bleaching protocol should be kept relatively consistent during experiments, as alterations can affect measurements of protein dynamics58.
  2. Optimize time-lapse parameters to fully capture the dynamics of the protein of interest while minimizing photobleaching.
    1. Prepare the microscopy set-up for live cell imaging, preferably with a heated stage and objective as well as CO2 control. Allow to equilibrate for 20 min.
      NOTE: To maintain the health of the imaged cells, temperature and pH must be maintained in the imaging vessel. A variety of heated stages and objective heaters can readily maintain the cell temperature at 37 °C. The control of pH for many media types can be accomplished by the use of a peristaltic pump to pass humidified 5% CO2 over the sample at 15 mL/min. Alternatively, if CO2 control is unavailable, live imaging media containing HEPES should be used to prevent large pH changes.
    2. Place one of the generated samples of the cells expressing the tension sensor into the microscope stage holder for imaging. Allow to equilibrate for 10 min.
    3. Using the MDA tool, set up a time-lapse to acquire 3-5 images pre-bleach, bleach the ROI, and continue taking 10-60 images.
      NOTE: For vinculin at FAs, imaging every 5 s for 5 min post-bleach is sufficient to observe the dynamics without introducing excessive bleaching31. Useful starting points for imaging rate and duration for many other proteins can be found in the literature47,48,59,60.
    4. Use acceptor imaging settings that minimize the exposure of the sample to light, while maintaining a sufficient signal-to-noise ratio, to image the structure of interest. A good starting point is half of the ND filter and exposure time necessary for imaging of the acceptor during FRET.
    5. Find a cell expressing the tension sensor with clear localization to a structure of interest and snap an image.
    6. Draw a rectangular ROI to highlight where to bleach and store the ROI location. Initiate the time-lapse.
    7. Examine the resulting set of images for potential issues.
      1. If there are substantial jumps (greater than 10% of initial intensity) in fluorescence recovery between frames, reduce the time-step between frames.
      2. If there is a significant global loss of fluorescence over time (greater than 5-10% of initial intensity), reduce the number of images taken post-bleach and/or change the imaging settings to reduce the exposure of the sample to light.
      3. If fluorescence recovery has not plateaued by the end of the time-lapse, increase the total length of the time-lapse.
    8. Adjust the time-lapse parameters accordingly and repeat Steps 4.2.5 – 4.2.7 until the fluorescence recovery is adequately captured without global photo-damage to the sample.

5. Acquire FRET-FRAP data

  1. Prepare the microscopy set-up for live cell imaging, preferably with a heated stage and objective as well as CO2 control. Allow to equilibrate for 20 min.
    1. To ensure the health of the imaged cells, maintain the temperature at 37 °C in the imaging chamber. Use a peristaltic pump to pass humidified 5% CO2 over the sample at 15 mL/min to maintain the pH.
    2. Alternatively, if CO2 control is unavailable, use live imaging media containing HEPES to prevent from large pH changes.
  2. Open the MDA tool and set up with FRET imaging parameters, including the different filter sets.
  3. Save this MDA to the experimental folder with the name of MDA_FRET_Date.
  4. Set up another MDA with FRAP imaging parameters, including the different filter sets, the time-lapse settings, and the journal to pulse the laser after pre-bleach acquisition.
  5. Save this MDA to the experimental folder with the name of MDA_FRAP_Date. Close the MDA window.
  6. In the toolbar at the top of the screen, select Journal | Start Recording.
  7. Open the MDA window, load the MDA_FRET_Date state and press Acquire. Then load the MDA_FRAP_Date state and press Acquire.
  8. At the end of the acquisition, in the toolbar at the top of the screen, select Journal | Stop Recording.
  9. Save this journal to the experimental folder with the name of FRETFRAP_Date and add it to a toolbar for easy access. Close the MDA window.
  10. Place one of the generated samples of the cells expressing the tension sensor into the microscope holder for imaging. Allow to equilibrate for 10 min.
  11. Navigate the sample using the image acquisition under Acquire | Acquire with minimal exposure time and ND filter to identify the cells of interest.
  12. Set continuous autofocus by navigating to Devices | Focus. Manually focus on the sample until reaching the correct imaging plane.
  13. Click Set Continuous Focus, wait for the system to adjust, and click Start Continuous Focusing.
    NOTE: This is not required, but significantly improves quality of FRAP recovery curves because it prevents the sample from drifting out-of-focus.
  14. Find a cell expressing the tension sensor with clear localization to a structure of interest and snap an image.
  15. Draw a rectangular ROI to highlight where to bleach. Store the ROI location.
  16. Initialize the FRETFRAP_Date journal, which will begin the acquisition of FRET images followed by the initialization of the FRAP time-lapse.
  17. Repeat Steps 5.14-5.16 until 10-15 image sets are acquired.
    NOTE: Measurement cannot be repeated in the same cell. Once photobleaching occurs, FRET data is unreliable.

6. Analyze FRET-FRAP data

  1. Analyze the FRET images using the software of choice.
    NOTE: There are several ways to image and quantitate FRET61, including ratiometric FRET62 and FRET index34,35. However, it is highly recommended to use the estimates of FRET efficiency55,63 for the interpretation of FRET-FRAP data. See the Discussion for further exploration of this topic. For sensitized emission and calculation of FRET efficiency, custom software is available from the Hoffman Lab at https://gitlab.oit.duke.edu/HoffmanLab-Public.
  2. Quantify relevant parameters for each subcellular structure that was bleached. This should include average FRET index/efficiency and average initial acceptor intensity (proportional to concentration) but could also include physical parameters such as ROI size.
  3. Analyze the FRAP images using the software of choice.
    NOTE: There are several ways to quantitate FRAP26,27,28,29. Key experimental concerns include accounting for bleaching during post-bleach imaging, changes in background intensity, and translocation of highly dynamic subcellular structures, such as focal adhesions. Bleaching corrections and variations in background illumination can be accomplished through the analysis of non-bleached and non-fluorescent regions of the images. Highly dynamic subcellular structures, particularly those showing excessive growth or disassembly dynamics are incompatible with standard FRAP analyses and should not be analyzed. Additionally, there are a variety of ways to normalize the data. The provided guidelines are for the simplest analysis.
  4. Correct the recovery data for bleaching effects and then normalize to pre-bleach intensities. Quantify the half-time of recovery and the mobile fraction according to the following equation28,34:
    MF - (MF - Ro)e-kt
    where MF is the mobile fraction, Ro is the initial recovery, and k is the recovery rate. The half-time of the recovery is determined by:
    τ1/2 = ln 2/k.
    NOTE: There are a variety of publicly-available software packages for completing these analyses64 as well as a variety of ImageJ plugins. Custom software is available from the Hoffman Lab at https://gitlab.oit.duke.edu/HoffmanLab-Public. More analyses should be used for the situations where the diffusion affects the dynamics of the protein of interest, multiple time scales are apparent in the recovery, or non-standard bleaching geometries are used.

7. Interpret FRET-FRAP data

  1. Compile relevant information for each ROI including: FRET index/efficiency, acceptor intensity, FRAP half-time, FRAP mobile fraction.
    NOTE: FRET index or efficiency is used to determine average load across the protein within the ROI. Acceptor intensity measures the local concentration of the protein. The half time of recovery is a measure of protein dynamics. A smaller half-time indicates more rapid turnover. FRAP mobile fraction measures the amount of protein within the ROI that is actively turning over. A larger mobile fraction indicates that a larger percentage of the protein within the ROI is turning over.
  2. To probe the effect of local concentration on protein turnover rate and amount, plot FRAP half-time and mobile fraction against initial acceptor intensity.
  3. To probe the effect of protein load on protein turnover rate and amount, plot FRAP half-time and mobile fraction against FRET index/efficiency.
    NOTE: Depending on the protein or structure, it may also be interesting to examine effects of physical parameters, such as structure size or eccentricity, on protein load or turnover.

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Representative Results

FRET-FRAP is made up of the combination of two fluorescent techniques, FRET and FRAP. As we focused on the effects of protein load, we used FRET-based tension sensors34,46. These sensors are often based on a tension sensing module consisting of two fluorescent proteins, such as mTFP1 and VenusA206K, connected by a flagelliform linker (Figure 1A). When the module is placed between the head and tail domains of a protein, it is possible to measure the load exerted across the protein. When analyzing FRET data, images taken in the acceptor channel are used to assess tension sensor localization and concentration, as this signal is independent of FRET (Figure 1B). After the calculation of FRET efficiency, protein load can be visualized on a colorimetric scale where a decrease in FRET efficiency toward cooler colors indicates an increase in protein load, and FRET efficiencies in the red range indicate low protein load (Figure 1B). FRAP imaging is conducted by using a laser to bleach the acceptor fluorophore in a single subcellular structure and monitor recovery over time (Figure 1C). The resulting normalized FRAP curve can be analyzed to extract parameters describing the protein dynamics, including the half-time of recovery and mobile fraction (Figure 1D). Because FRET and FRAP analyses were performed on the same cell, the average protein load and turnover in a subcellular structure can be plotted as a single point. Imaging multiple cells yields multiple points and an emerging trend can indicate whether a protein is destabilized (Figure 1E) or stabilized by molecular load (Figure 1F).

The vinculin tension sensor (VinTS) stably expressed in vinculin null MEFs very clearly localizes to FAs spread throughout the cell, as seen by looking at the acceptor channel image (Figure 2A). The acceptor channel image is used to create a segmentation mask that identifies each individual FA with a unique ID, visually designated by different colors (Figure 2B). The segmentation algorithm is based on the "water" method and labels the FAs approximately in order of brightness, as previously described34,65. The segmentation results are converted to a binary mask which is then applied to the FRET efficiency results (Figure 2C), and the average FRET efficiency within each unique FA is calculated (Figure 2D). Additional properties can be calculated for each FA in a similar manner, including average acceptor intensity, size, eccentricity, and location within the cell. This way, whichever FA is chosen for FRAP can be matched to the unique FA ID and the associated properties.

FRAP imaging and analysis is sensitive to several factors that can be controlled, including laser and imaging parameters, and some factors that cannot be controlled, such as overall FA stability26,27,28,29. For example, too much exposure to light during the time-lapse imaging can lead to major issues in interpreting FRAP data. Although the analysis of control FAs that were not bleached can be used to normalize for minor photobleaching over time, with too much exposure of the sample to light, the resulting FRAP curve shows an initial recovery followed by a dip in normalized intensity that cannot be accurately fit with an exponential function. If this effect is consistently observed in the data, it is necessary to re-optimize the imaging parameters to either decrease exposure time, increase the time-step between imaging frames, or decrease the length of the time-lapse to reduce the exposure of the sample to light.

Another example of FRAP data that is uninterpretable, is when the FA that was photobleached translocates rapidly during recovery28. A representative case of excessive translocation is shown in Figure 3. The initial image, where the ROIs are chosen, does not give an indication of FA stability (Figure 3A). Monitoring the bleached FA over time, it quickly moves away from the initial position and the automated tracking is unable to immediately follow due to the low fluorescent signal following photobleaching (Figure 3A). The resulting FRAP curve shows an initial phase of slight recovery with a jump when the fluorescence is recovered enough for the software to detect the FA and move the ROI (Figure 3B). This curve cannot be successfully fit by an exponential function. The rapid translocation of the FA also suggests that the FA structure is unstable. Thus, unstable FAs should not be included in the same FRET-FRAP analysis as stable FAs, due to both technical and biological issues.

With satisfactory FRET and FRAP data, the next step is completing the FRET-FRAP analysis by simultaneously assessing protein load and dynamics. Figure 4A shows the FRET efficiency maps of three vinculin null MEFs stably expressing VinTS. The FAs outlined in white were chosen for FRAP analysis, and the acceptor intensities are shown over time. These three FAs have vinculin under different amounts of load and display a different vinculin recovery profile. Quantifying these properties by calculating the half-time of recovery and plotting against the average FRET efficiency in each FA demonstrates the overall trend of vinculin being stabilized by increased load (Figure 4B). However, the mobile fraction plotted against FRET efficiency shows no trend, suggesting that mobile fraction is not regulated by molecular load (Figure 4C). Introducing a point mutation into the VinTS at amino acid 50 (A50I) has been shown to prevent vinculin binding to a major binding partner within FAs, talin66. The alteration of this protein-protein interaction affects vinculin force-sensitive dynamics. Vinculin null MEFs stably expressing VinTS A50I have different cell and FA morphologies, different vinculin loading profiles, and different vinculin dynamics (Figure 4D). Quantifying the half-times of recovery and FRET efficiencies and plotting shows that when the vinculin-talin interaction is disturbed, vinculin at FAs is destabilized by increased load (Figure 4E) while mobile fraction shows no trend (Figure 4F).

Figure 1
Figure 1: Principles of FRET-FRAP technique. (A) Schematic of the FRET-based tension sensor module (TSMod) inserted into a protein of interest and the effect of tension on the FRET signal. (B) To quantify FRET using sensitized emission, images are taken to capture donor signal (not shown), acceptor signal, and FRET signal. With appropriate corrections, the FRET image can be assigned a colorimetric scale to visualize how much tension is being applied to the sensor. (C) FRAP is conducted using the acceptor signal, which is directly proportional to the concentration. (D) FRAP imaging analysis produces curves of fluorescence intensity over time that can be fit using mathematical models to determine protein dynamics. (E, F) When FRET and FRAP are combined, force and turnover in a single FA can be measured. Measuring multiple FAs in multiple cells yields a relationship between protein load and protein turnover. In this analysis, a relationship in which increased load correlates with increased turnover is referred to as a force-destabilized state (E). In this analysis, a relationship in which increased load correlates with decrease turnover is referred to as a force-stabilized state (F). This figure has been modified from Rothenberg et al.37. Please click here to view a larger version of this figure.

Figure 2
Figure 2: FA identification and FRET analysis. (A) A vinculin null MEF expressing the VinTS visualized in the acceptor channel, where the intensity indicates local concentration of vinculin. Scale bar = 30 µm. (B) FAs are segmented based on the acceptor channel to create a FA ID mask where each FA is assigned a unique ID, here shown as different colors, approximately in order of brightness. (C) The FA ID mask is converted to a binary mask and applied to the FRET efficiency image to show the FRET efficiency values only at FAs. (D) The FRET efficiency within each FA is averaged to obtain a single value for each FA, which is associated with the FA ID in the output data table. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Example of a translocating FA. (A) A vinculin null MEF expressing the VinTS A50I mutant sensor is visualized in the acceptor channel, with the color table inverted for clarity. Scale bar = 30 µm. The FA outlined in black was selected for bleaching. Zoomed-in images show the FA progression over time with the red outline indicating where the software identified the FA. Scale bar = 2 µm. (B) The resulting normalized FRAP curve from data in (A). There is an approximately 5% jump in intensity following point 3 resulting from the FA translocating quickly before sufficient recovery for the software to detect the change in FA location. Please click here to view a larger version of this figure.

Figure 4
Figure 4: Representative FRET-FRAP results. (A) Vinculin null MEFs expressing the VinTS displayed as average FRET efficiency images of the entire cell (scale bar = 30 µm) with zoomed-in inverted acceptor channel images showing FRAP recovery progression (scale bar = 2 µm). (B) FRAP half-time of recovery plotted against FRET efficiency for 32 cells, with the points representing cells in (A) highlighted in red. (C) FRAP mobile fraction plotted against FRET efficiency for the same cells in (B). (D) Vinculin null MEFs expressing the VinTS A50I mutant sensor displayed as average FRET efficiency images of the entire cell (scale bar = 30 µm) with zoomed-in inverted acceptor channel images showing FRAP recovery progression (scale bar = 2 µm). (E) FRAP half-time of recovery plotted against FRET efficiency for 21 cells, with the points representing cells in (D) highlighted in red. (F) FRAP mobile fraction plotted against FRET efficiency for the same cells in (E). Data were originally published in Rothenberg et al.37 and are visualized here in a new format. Please click here to view a larger version of this figure.

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Discussion

The FRET-FRAP method allows for direct measurement of force-sensitive protein dynamics, a property that has been difficult to directly probe inside living cells. The sensitivity of protein dynamics to molecular load is critical to the protein's function as a force transmitter or transducer. Loading is required for the transmission of both internally-generated and externally-applied forces, called mechanotransmission, and for the conversion of those forces into biochemically-detectable signals, called mechanotransduction. However, the alterations in load can affect the duration a protein stays bound, thus, the less time a protein spends bearing load, the less chance the force has to be transmitted to other proteins or transduced into a biochemically-detectable signal and sensed. The FRET-FRAP method bridges the gap between the molecular and cellular level by allowing molecular-scale measurements of force-sensitive dynamics to be accessed within a broader cellular context. Furthermore, it allows for these measurements to be taken while perturbing the intracellular or extracellular environment either biochemically or mechanically. This technique should be applicable to any FRET-based tension sensor, allowing for the investigation of protein mechanical state in a variety of subcellular structures and extracellular contexts.

Critical steps in ensuring that the desired FRET-FRAP measurements are obtained involve optimizing the imaging parameters and performing data analysis and interpretation. Optimizing the imaging parameters, as described within the protocol, is necessary to limit the photodamage to the sample, while allowing for the desired structures and dynamics to be distinguished and for sufficient signal strength for the calculation of FRET. Establishing these imaging parameters for a particular cell line and protein of interest early on will facilitate direct comparison between different experimental groups. It is worth noting that alterations to the system, such as mutating the protein of interest or introducing inhibitors, can lead to changes in protein localization (thereby altering signal intensity) and dynamics. The optimized parameters should enable clear, accurate measurements across all experimental conditions. Therefore, it is recommended to choose the parameters that are not at the extreme end of being useful, for example, being able to barely distinguish signal from noise.

While the imaging in this protocol was described for an epifluorescence microscope and attached FRAP laser module, FRET-FRAP is applicable to other imaging systems. For example, this technique can be adapted to line-scanning confocal microscopes as well as spinning-disk confocal microscopes with an attached photobleaching module. Imaging settings should be optimized in an analogous fashion to achieve adequate signal-to-noise without causing photodamage or excessive photobleaching. Particularly concerning FRET imaging, high quantum efficiency detectors are required to obtain sufficient signal for successful FRET calculation without inducing fluorophore damage. There are a number of publications describing separate FRET or FRAP imaging using a confocal microscope67,68,69, which can be used to guide optimization for FRET-FRAP imaging.

Following the experiment, data analysis should be treated carefully and performed in a reproducible, preferably automated, manner. Due to the inability to bleach more than 2-3 subcellular regions in a single cell before bleaching too much of the available pool of protein, the throughput of this technique is relatively limited. Thus, data sets are often combined across multiple days of imaging, requiring consistent treatment of data. Both FRET and FRAP offer challenges with data analysis. FRET index and FRET efficiency measurements allow for a quantification of protein load. FRET index is a relative measure that is highly dependent on microscope settings, while FRET efficiency measurements are absolute and independent of microscope settings55,70. We have recently shown that a previously developed method using "three-cube" imaging can be used to determine FRET efficiency from measurements of sensitized emission that are typically quantified with FRET Index when using FRET-based tension sensors56. The measurements of FRET efficiency are required if the measurements of the absolute forces experience by the tension sensors are to be calculated34. The cells expressing FRET-based tension sensors, especially stable cells at high passage numbers, may recombine or degrade the sensors, leading to unusable FRET data50. This is easily identified when calculating donor-to-acceptor ratios during the calculation of FRET efficiency37,56 but may be harder to detect using FRET index. When starting with a FRET-based tension sensor, it can be helpful to obtain a large data set (>50 cells) of only FRET data for the constructs of interest to identify the expected range of FRET efficiencies. Additionally, FRAP data may be difficult to extract from structures that are very mobile, such as FAs that are rapidly sliding or disassembling. Selecting a subpopulation of structures or optimizing cell plating conditions to mitigate this effect can help to minimize this issue.

In concept, FRET-FRAP can be applied to any FRET-based sensor in any subcellular region, with proper optimization. In practice, it may be difficult to capture force-sensitive dynamics of proteins that are not under substantial mechanical load or that have half-times of recovery on the very short timescale of a few seconds or on the long timescale of tens of minutes. Results from single-molecule studies can point to the proteins that may demonstrate force-sensitive dynamics within living cells. Thus far, this includes many FA and AJ proteins13,14,15,16 as well as some cytoskeletal elements71,72,73. Fortuitously, FRET-based sensors have been designed for many of these proteins46. These results can guide the selection of a protein of interest; however, it should not be expected that FRET-FRAP data will exactly mirror the results from these single-molecule studies. In fact, biochemical regulation, interactions with other proteins, and local cytoskeletal structure may obscure, or alter, the effects of forces on protein-protein interactions. The ability to observe these complexities is a unique strength of the FRET-FRAP approach.

A combination of manipulations to the cell and the protein of interest can be used to elucidate the important factors in regulating protein dynamics. For example, it can be helpful to have a sensor that is force-insensitive, either through the deletion or mutation of a force-binding domain35,74 as there should be no dependence of the protein turnover dynamics on the force reported by the sensor. Additionally, the mutations of other critical binding sites or phosphorylation sites in the protein can provide a more complete picture of how the protein of interest is being regulated. Making global changes to the cell or the environment through cytoskeletal inhibitors or by changing the substrate properties (ex. extracellular matrix or stiffness), respectively, can help determine how the force-sensitive dynamics of the protein respond to mechanical perturbations. Combining the information on protein load and force-sensitive dynamics with other biophysical properties of the protein can help to establish the mechanical state of the protein of interest. This can include the localization and local protein-protein interactions within a subcellular structure75,76. Additionally, the protein could reside in different conformation states, even within the same subcellular structure, depending on context76,77. Protein load, dynamics, localization, and conformation can all be simultaneously affected by internally-generated and externally-applied forces37,76,78,79, dictating a protein's role in force transmission and mechanotransduction. The versatility of the FRET-FRAP method and its potential compatibility with a variety of proteins and manipulations should enable the elucidation of the interaction between bulk mechanics, protein dynamics, and mechanosensitive signaling.

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Disclosures

The authors have nothing to disclose.

Acknowledgments

This work was supported by a National Science Foundation CAREER Award (NSF-CMMI-14-54257) as well as grants from the American Heart Association (16GRNT30930019) and National Institutes of Health (R01GM121739-01) awarded to Dr. Brenton Hoffman and a National Science Foundation Graduate Research Fellowship awarded to Katheryn Rothenberg. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NSF or NIH.

Materials

Name Company Catalog Number Comments
0.05% Trypsin-EDTA Thermo Fisher 25300062
16% Paraformaldehyde Electron Microscopy Sciences 30525-89-4
60x Objective NA1.35 Olympus UPLSAPO 60XO
Antibiotic-Antimycotic Solution (100x) Gibco 15240-062
Automated Stage Prior Scientific H117EIX3
Custom Dichroic Mirror Chroma Technology Corp T450/514rpc
Custom mTFP1 Emission Filter Chroma Technology Corp ET485/20m
Custom mTFP1 Excitation Filter Chroma Technology Corp ET450/30x
Custom Venus Excitation Filter Chroma Technology Corp ET514/10x
DMEM-gfp Live Cell Visualization Medium Sapphire MC102
Dulbecco's Modified Eagle's Medium  Sigma Aldrich D5796 with L-glutamine and sodium bicarbonate
Fetal Bovine Serum HyClone SH30396.03
Fibronectin, Human Corning 47743-654
FRAPPA Calibration Slide Andor provided along with FRAPPA unit
FRAPPA System with 515 nm Laser Andor
Glass-bottomed Fluoro Dishes World Precision Instruments FD35
HEK293-T Cells ATCC CRL-3216
Hexadimethrine Bromide, Polybrene Sigma Aldrich H9268-5G
High-glucose Dulbecco's Modified Eagle's Medium Sigma Aldrich D6429
Inverted Fluorescent Microscope Olympus IX83
JMP Pro Software SAS
Lambda 10-3 Motorized Filter Wheels Sutter Instruments LB10-NW
LambdaLS Arc Lamp with 300W Ozone-Free Xenon Bulb Sutter Instruments LS/OF30
Lipofectamine 2000 Invitrogen 11668-027
MATLAB Software Mathworks
MEM Non-Essential Amino Acids Thermo Fisher 11140050
MetaMorph for Olympus Olympus
Micro-Humidification System Bioptechs 130708
MoFlo Astrios EQ Cell Sorter Beckman Coulter B25982
Objective Heater Medium Bioptechs 150819-13
OptiMEM Thermo Fisher 31985070
Phosphate Buffered Saline Sigma Aldrich D8537
pMD2.G Envelope Plasmid Addgene 12259
pRRL Vector gift from Dr. Kam Leong (Columbia University)
psPax2 Packaging Plasmid Addgene 12260
sCMOS ORCA-Flash4.0 V2 Camera Hamamatsu Photonics C11440-22CU
Sorvall Legend XT/XF Centrifuge Thermo Fisher 75004505
Stable Z Stage Warmer Bioptechs 403-1926
Venus Emission Filter Semrock FF01-571/72

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References

  1. DuFort, C. C., Paszek, M. J., Weaver, V. M. Balancing forces: architectural control of mechanotransduction. Nature Reviews Molecular Cell Biology. 12 (5), 308-319 (2011).
  2. Mammoto, T., Ingber, D. E. Mechanical control of tissue and organ development. Development. 137 (9), 1407-1420 (2010).
  3. Sun, Y., Chen, C. S., Fu, J. Forcing stem cells to behave: a biophysical perspective of the cellular microenvironment. Annual Review of Biophysics. 41, 519-542 (2012).
  4. Wozniak, M. A., Chen, C. S. Mechanotransduction in development: a growing role for contractility. Nature Reviews Molecular Cell Biology. 10 (1), 34-43 (2009).
  5. Broders-Bondon, F., Nguyen Ho-Bouldoires, T. H., Fernandez-Sanchez, M. E., Farge, E. Mechanotransduction in tumor progression: The dark side of the force. The Journal of cell biology. 217 (5), 1571-1587 (2018).
  6. Simmons, R. D., Kumar, S., Jo, H. The role of endothelial mechanosensitive genes in atherosclerosis and omics approaches. Archives of Biochemistry and Biophysics. 591, 111-131 (2016).
  7. Wells, R. G. Tissue mechanics and fibrosis. Biochimica et Biophysica Acta. 1832 (7), 884-890 (2013).
  8. Lele, T. P., et al. Mechanical forces alter zyxin unbinding kinetics within focal adhesions of living cells. Journal of Cellular Physiology. 207 (1), 187-194 (2006).
  9. Hoffman, B. D., Grashoff, C., Schwartz, M. A. Dynamic molecular processes mediate cellular mechanotransduction. Nature. 475 (7356), 316-323 (2011).
  10. Dembo, M., Torney, D. C., Saxman, K., Hammer, D. The reaction-limited kinetics of membrane-to-surface adhesion and detachment. Proceedings of the Royal Society of London B: Biological Sciences. 234 (1274), 55-83 (1988).
  11. LaCroix, A. S., Rothenberg, K. E., Hoffman, B. D. Molecular-Scale Tools for Studying Mechanotransduction. Annual Review of Biomedical Engineering. 17, 287-316 (2015).
  12. Neuman, K. C., Nagy, A. Single-molecule force spectroscopy: optical tweezers, magnetic tweezers and atomic force microscopy. Nature Methods. 5 (6), 491-505 (2008).
  13. Kong, F., Garcia, A. J., Mould, A. P., Humphries, M. J., Zhu, C. Demonstration of catch bonds between an integrin and its ligand. The Journal of Cell Biology. 185 (7), 1275-1284 (2009).
  14. Rakshit, S., Zhang, Y., Manibog, K., Shafraz, O., Sivasankar, S. Ideal catch, and slip bonds in cadherin adhesion. Proceedings of the National Academy of Sciences. 109 (46), 18815-18820 (2012).
  15. del Rio, A., et al. Stretching Single Talin Rod Molecules Activates Vinculin Binding. Science. 323 (5914), 638-641 (2009).
  16. Seddiki, R., et al. Force-dependent binding of vinculin to alpha-catenin regulates cell-cell contact stability and collective cell behavior. Molecular Biology of the Cell. 29 (4), 380-388 (2018).
  17. Huang, D. L., Bax, N. A., Buckley, C. D., Weis, W. I., Dunn, A. R. Vinculin forms a directionally asymmetric catch bond with F-actin. Science. 357 (6352), 703-706 (2017).
  18. Chrzanowska-Wodnicka, M., Burridge, K. Rho-stimulated contractility drives the formation of stress fibers and focal adhesions. The Journal of Cell Biology. 133 (6), 1403-1415 (1996).
  19. Choquet, D., Felsenfeld, D. P., Sheetz, M. P. Extracellular matrix rigidity causes strengthening of integrin-cytoskeleton linkages. Cell. 88 (1), 39-48 (1997).
  20. Liu, Z., et al. Mechanical tugging force regulates the size of cell-cell junctions. Proceedings of the National Academy of Science. 107 (22), 9944-9949 (2010).
  21. Riveline, D., et al. Focal contacts as mechanosensors: externally applied local mechanical force induces growth of focal contacts by an mDia1-dependent and ROCK-independent mechanism. The Journal of Cell Biology. 153 (6), 1175-1186 (2001).
  22. Brevier, J., Vallade, M., Riveline, D. Force-extension relationship of cell-cell contacts. Physical Review Letters. 98 (26), 268101 (2007).
  23. Bershadsky, A., Kozlov, M., Geiger, B. Adhesion-mediated mechanosensitivity: a time to experiment, and a time to theorize. Current opinion in cell biology. 18 (5), 472-481 (2006).
  24. Chan, C. E., Odde, D. J. Traction dynamics of filopodia on compliant substrates. Science. 322 (5908), 1687-1691 (2008).
  25. Wu, Z., Plotnikov, S. V., Moalim, A. Y., Waterman, C. M., Liu, J. Two distinct actin networks mediate traction oscillations to confer focal adhesion mechanosensing. Biophysical Journal. 112 (4), 780-794 (2017).
  26. Fritzsche, M., Charras, G. Dissecting protein reaction dynamics in living cells by fluorescence recovery after photobleaching. Nature Protocols. 10 (5), 660-680 (2015).
  27. McNally, J. G. Quantitative FRAP in analysis of molecular binding dynamics in vivo. Methods of Cell Biology. 85, 329-351 (2008).
  28. Wehrle-Haller, B. Analysis of integrin dynamics by fluorescence recovery after photobleaching. Methods in Molecular Biology. 370, 173-202 (2007).
  29. Carisey, A., Stroud, M., Tsang, R., Ballestrem, C. Fluorescence recovery after photobleaching. Methods of Molecular Biology. 769, 387-402 (2011).
  30. Carisey, A., et al. Vinculin regulates the recruitment and release of core focal adhesion proteins in a force-dependent manner. Current Biology. 23 (4), 271-281 (2013).
  31. Wolfenson, H., Bershadsky, A., Henis, Y. I., Geiger, B. Actomyosin-generated tension controls the molecular kinetics of focal adhesions. Journal of Cell Science. 124, 1425-1432 (2011).
  32. Dumbauld, D. W., et al. How vinculin regulates force transmission. Proceedings of the National Academy of Sciences. 110 (24), 9788-9793 (2013).
  33. Zaidel-Bar, R., Itzkovitz, S., Ma'ayan, A., Iyengar, R., Geiger, B. Functional atlas of the integrin adhesome. Nature Cell Biology. 9 (8), 858-867 (2007).
  34. Grashoff, C., et al. Measuring mechanical tension across vinculin reveals regulation of focal adhesion dynamics. Nature. 466 (7303), 263-266 (2010).
  35. LaCroix, A. S., Rothenberg, K. E., Berginski, M. E., Urs, A. N., Hoffman, B. D. Construction, imaging, and analysis of FRET-based tension sensors in living cells. Biophysical Methods in Cell Biology. 125, 161-186 (2015).
  36. Meng, F., Suchyna, T. M., Sachs, F. A fluorescence energy transfer-based mechanical stress sensor for specific proteins in situ. The FEBS Journal. 275 (12), 3072-3087 (2008).
  37. Rothenberg, K. E., Scott, D. W., Christoforou, N., Hoffman, B. D. Vinculin Force-Sensitive Dynamics at Focal Adhesions Enable Effective Directed Cell Migration. Biophysical journal. 114 (7), 1680-1694 (2018).
  38. Austen, K., et al. Extracellular rigidity sensing by talin isoform-specific mechanical linkages. Nature Cell Biology. 17 (12), 1597-1606 (2015).
  39. Kumar, A., et al. Talin tension sensor reveals novel features of focal adhesion force transmission and mechanosensitivity. The Journal of Cell Biology. 213 (3), 371-383 (2016).
  40. Acharya, B. R., et al. Mammalian Diaphanous 1 Mediates a Pathway for E-cadherin to Stabilize Epithelial Barriers through Junctional Contractility. Cell Reports. 18 (12), 2854-2867 (2017).
  41. Borghi, N., et al. E-cadherin is under constitutive actomyosin-generated tension that is increased at cell-cell contacts upon externally applied stretch. Proceedings of the National Academy of Sciences. 109 (31), 12568-12573 (2012).
  42. Conway, D. E., Williams, M. R., Eskin, S. G., McIntire, L. V. Endothelial cell responses to atheroprone flow are driven by two separate flow components: low time-average shear stress and fluid flow reversal. American Journal of Physiology-Heart and Circulatory Physiology. 298 (2), H367-H374 (2010).
  43. Arsenovic, P. T., et al. Nesprin-2G, a Component of the Nuclear LINC Complex, Is Subject to Myosin-Dependent Tension. Biophysical Journal. 110 (1), 34-43 (2016).
  44. Ye, N., et al. Direct observation of alpha-actinin tension and recruitment at focal adhesions during contact growth. Experimental Cell Research. 327 (1), 57-67 (2014).
  45. Paszek, M. J., et al. The cancer glycocalyx mechanically primes integrin-mediated growth and survival. Nature. 511 (7509), 319-325 (2014).
  46. Gayrard, C., Borghi, N. FRET-based Molecular Tension Microscopy. Methods. 94, 33-42 (2016).
  47. de Beco, S., Gueudry, C., Amblard, F., Coscoy, S. Endocytosis is required for E-cadherin redistribution at mature adherens junctions. Proceedings of the National Academy of Sciences. 106 (17), 7010-7015 (2009).
  48. Östlund, C., et al. Dynamics and molecular interactions of linker of nucleoskeleton and cytoskeleton (LINC) complex proteins. Journal of Cell Science. 122 (22), 4099-4108 (2009).
  49. Coffin, J. M., Hughes, S. H., Varmus, H. E. The interactions of retroviruses and their hosts. , Cold Spring Harbor Laboratory Press. Cold Spring Harbor (NY). (1997).
  50. Komatsubara, A. T., Matsuda, M., Aoki, K. Quantitative analysis of recombination between YFP and CFP genes of FRET biosensors introduced by lentiviral or retroviral gene transfer). Scientific Reports. 5, 13283 (2015).
  51. Nasri, M., Karimi, A., Farsani, M. A. Production purification and titration of a lentivirus-based vector for gene delivery purposes. Cytotechnology. 66 (6), 1031-1038 (2014).
  52. Addgene, Generating Stable Cell Lines with Lentivirus. , Available from: https://www.addgene.org/protocols/generating-stable-cell-lines (2016).
  53. Roederer, M. Spectral compensation for flow cytometry: visualization artifacts, limitations, and caveats. Cytometry: The Journal of the International Society for Analytical Cytology. 45 (3), 194-205 (2001).
  54. Malkani, N., Schmid, J. A. Some secrets of fluorescent proteins: distinct bleaching in various mounting fluids and photoactivation of cyan fluorescent proteins at YFP-excitation. PLoS One. 6 (4), e18586 (2011).
  55. Chen, H., Puhl, H. L. 3rd, Koushik, S. V., Vogel, S. S., Ikeda, S. R. Measurement of FRET efficiency and ratio of donor to acceptor concentration in living cells. Biophysical journal. 91 (5), L39-L41 (2006).
  56. Rothenberg, K. E., Neibart, S. S., LaCroix, A. S., Hoffman, B. D. Controlling Cell Geometry Affects the Spatial Distribution of Load Across Vinculin. Cellular and Molecular Bioengineering. 8 (3), 364-382 (2015).
  57. Carnell, M., Macmillan, A., Whan, R. Fluorescence recovery after photobleaching (FRAP): acquisition, analysis, and applications. Methods of Molecular Biology. 1232, 255-271 (2015).
  58. Trembecka, D. O., Kuzak, M., Dobrucki, J. W. Conditions for using FRAP as a quantitative technique--influence of the bleaching protocol. Cytometry A. 77 (4), 366-370 (2010).
  59. Lavelin, I., et al. Differential effect of actomyosin relaxation on the dynamic properties of focal adhesion proteins. PLoS One. 8 (9), e73549 (2013).
  60. Foote, H. P., Sumigray, K. D., Lechler, T. FRAP analysis reveals stabilization of adhesion structures in the epidermis compared to cultured keratinocytes. PLoS One. 8 (8), e71491 (2013).
  61. Zal, T., Gascoigne, N. R. Photobleaching-corrected FRET efficiency imaging of live cells. Biophysical Journal. 86 (6), 3923-3939 (2004).
  62. Hodgson, L., Shen, F., Hahn, K. Biosensors for characterizing the dynamics of rho family GTPases in living cells. Current Protocols in Cell Biology. 46 (1), (2010).
  63. Day, R. N. Measuring protein interactions using Förster resonance energy transfer and fluorescence lifetime imaging microscopy. Methods. 66 (2), 200-207 (2014).
  64. Rapsomaniki, M. A., et al. easyFRAP: an interactive, easy-to-use tool for qualitative and quantitative analysis of FRAP data. Bioinformatics. 28 (13), 1800-1801 (2012).
  65. Zamir, E., et al. Molecular diversity of cell-matrix adhesions. Journal of cell science. 112 (11), 1655-1669 (1999).
  66. Bakolitsa, C., et al. Structural basis for vinculin activation at sites of cell adhesion. Nature. 430 (6999), 583-586 (2004).
  67. De Los Santos, C., Chang, C. W., Mycek, M. A., Cardullo, R. FRAP, FLIM, and FRET: Detection and analysis of cellular dynamics on a molecular scale using fluorescence microscopy. Molecular Reproduction and Development. 82 (7-8), 587-604 (2015).
  68. Periasamy, A., Wallrabe, H., Chen, Y., Barroso, M. Chapter 22: Quantitation of protein-protein interactions: confocal FRET microscopy. Methods in Cell Biology. 89, 569-598 (2008).
  69. Stehbens, S., Pemble, H., Murrow, L., Wittmann, T. Imaging intracellular protein dynamics by spinning disk confocal microscopy. Methods in Enzymology. , 293-313 (2012).
  70. Zeug, A., Woehler, A., Neher, E., Ponimaskin, E. G. Quantitative intensity-based FRET approaches--a comparative snapshot. Biophysical Journal. 103 (9), 1821-1827 (2012).
  71. Ehrlicher, A. J., Nakamura, F., Hartwig, J. H., Weitz, D. A., Stossel, T. P. Mechanical strain in actin networks regulates FilGAP and integrin binding to filamin A. Nature. 478 (7368), 260-263 (2011).
  72. Guo, B., Guilford, W. H. Mechanics of actomyosin bonds in different nucleotide states are tuned to muscle contraction. Proceedings of the National Academy of Sciences. 103 (26), 9844-9849 (2006).
  73. Lee, C. Y., et al. Actin depolymerization under force is governed by lysine 113:glutamic acid 195-mediated catch-slip bonds. Proceedings of the National Academy of Sciences. 110 (13), 5022-5027 (2013).
  74. Cost, A. L., Ringer, P., Chrostek-Grashoff, A., Grashoff, C. How to Measure Molecular Forces in Cells: A Guide to Evaluating Genetically-Encoded FRET-Based Tension Sensors. Cellular and Molecular Bioengineering. 8 (1), 96-105 (2015).
  75. Bertocchi, C., et al. Nanoscale architecture of cadherin-based cell adhesions. Nature Cell Biology. 19 (1), 28-37 (2017).
  76. Case, L. B., et al. Molecular mechanism of vinculin activation and nanoscale spatial organization in focal adhesions. Nature Cell Biology. 17 (7), 880-892 (2015).
  77. Chen, H., Cohen, D. M., Choudhury, D. M., Kioka, N., Craig, S. W. Spatial distribution and functional significance of activated vinculin in living cells. The Journal of Cell Biology. 169 (3), 459-470 (2005).
  78. Kim, T. J., et al. Dynamic visualization of alpha-catenin reveals rapid, reversible conformation switching between tension states. Current Biology. 25 (2), 218-224 (2015).
  79. Yao, M., et al. Mechanical activation of vinculin binding to talin locks talin in an unfolded conformation. Scientific reports. 4, 4610 (2014).

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Force-sensitive Protein Dynamics Living Cells Fluorescent Techniques Mechanobiology Forces Transmission Protein Response To Mechanical Forces Focal Adhesion Protein Vinculin Talin Cadherins Nesprin Tension Sensor Construct Cell Seeding Glass-bottomed Dishes Fibronectin Solution
Measurement of Force-Sensitive Protein Dynamics in Living Cells Using a Combination of Fluorescent Techniques
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Rothenberg, K. E., Puranam, I.,… More

Rothenberg, K. E., Puranam, I., Hoffman, B. D. Measurement of Force-Sensitive Protein Dynamics in Living Cells Using a Combination of Fluorescent Techniques. J. Vis. Exp. (141), e58619, doi:10.3791/58619 (2018).

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