Biology
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Oligomerization Dynamics of Cell Surface Receptors in Living Cells by Total Internal Reflection Fluorescence Microscopy Combined with Number and Brightness Analysis
Chapters
Summary November 6th, 2019
We describe an imaging approach for the determination of the average oligomeric state of mEGFP-tagged-receptor oligomers induced by ligand binding in the plasma membrane of living cells. The protocol is based on Total Internal Reflection Fluorescence (TIRF) microscopy combined with Number and Brightness (N&B) analysis.
Transcript
Receptor clustering is ubiquitous and often necessary for the signaling a cascade activation. However, few methods are available to measure the degree of clustering. We use total internal reflection fluorescence, TIRF microscopy, to follow the diffusion of FGFR1-mEGFP molecules in the plasma membrane of live cells.
Then we apply number brightness, the N&B analysis, to describe the dynamics of stimulated receptor clustering. TIRF is ideal for fast temporal imaging of molecular events that occur near the cell surface, while N&B determines the average oligomeric state of fluorescent molecules based on where diffusion in and out the illumination volume of the microscope. Indeed, this is a tool to connect the spatial temporal organization of the receptors at the cell surface where they are signaling.
N&B only needs the access to a microscope with a fast acquisition module. You can analyze large area of live cells having just the basic knowledge of fluorescence fluctuation methods. This method can be applied to proteins that form dimers or clusters and can be stoichiometrically labeled with the fluorescent dye.
If the proteins are in intracellular compartments, other types of microscopes are used for acquiring the images. It is important to prepare a construct that expresses the monomeric form of the fluorophore for measuring under experimental conditions the pure monomeric brightness as a control. On the first day, seed HeLa cells in 1.5 milliliters of complete medium at a concentration of 100, 000 to 200, 000 cells per milliliter in glass-bottom dishes.
Seed six to eight replicate dishes, and incubate in an incubator at 37 degrees Celsius. On the second or third day, cells have reached subconfluency. Add serum-free medium with protein plasmid to half of the dishes, and add reference plasmids with the monomer and dimer to the second half of dishes to transfect the cells.
After one day, check that the transfected cells are adherent to the bottom of the dishes and the cell membrane is fluorescent. Discard dishes with overgrown cells or with very low fluorescence. Four hours before the experiment, activate the temperature incubator of the microscope at 37 degrees Celsius.
Turn on the microscope, computers, and cameras, and wait for the cameras to reach the proper working temperature of minus 75 degrees Celsius. Place a small drop of oil on the objective lens. Put a sample dish into the incubator of the microscope, and close the doors of the incubator to let the temperature of the dish equilibrate for 10 minutes.
Turn on the epifluorescence lamp and the 488-nanometer laser. Select the epifluorescence contrast mode to explore the sample, searching a cell to focus from the ocular lens. Select the proper filter for collecting the green emission through the microscope camera with bandpass Ex 490/20 500 and bandpass Em 525/50 or similar.
Switch from the ocular to the cam report in epifluorescence mode. Refine the focus, and change to TIRF mode. Then activate the auto alignment following the instructions of the TIRF microscope.
Choose a suitable illumination depth, and optimize the direction of the evanescent field. Switch to a second camera. Define a region of interest of at least 256 by 256 pixels.
Set the exposure to one millisecond and the EM gain to 1, 000. Adjust the laser power to 0.5 milliwatts. It is necessary to have some information about the diffusion coefficient of the protein because the exposure time must be shorter than the average time spent by the fluorescent molecules in the luminated volume.
Run a first trial sequence under initial conditions, and roughly estimate the signal-to-noise value. The conditions are acceptable at signal-to-noise equal to two to three or higher as measured in the first time series. Then use the slider of the emission splitting system connecting camera number two to the microscope for masking a side of the image.
Select the camera file auto save option. Start the acquisition of the image series for a minimum of 700 frames at a minimum signal-to-noise ratio of two. Without taking the dish out of the microscope, add the ligand.
Select a cell with a bright fluorescence membrane, and quickly start the first time series of the kinetic run. Search a second cell, and acquire the second time point of the kinetics. Capture a new cell for each time point of the kinetic run.
For each new dish, repeat the alignment of the laser line and optimization of TIRF illumination. Now convert and save the image files acquired with the camera software as tif files. Import tif files in the analysis software routine by activating the N&B graphical user interphase MATLAB.
Discard series for which the average intensity profile shows more than 10%photobleaching and series in which there has been an evident cell membrane distortion or translation during acquisition. Crop frames that are evidently out of focus. Keep for the analysis only series with at least 500 timeframes.
First determine the camera parameters. Activate the routine calibrate camera. Select an area of at least 20 by 50 pixels in the detector noise region.
In the log frequency versus digital level plot, move the linear red cursor to delimit the Gaussian in the linear part of the curve. Activate the B key. Apply a minimum binning of 2.2 to reduce the dispersion of the data and to generate the B-I histogram.
Use the iterative square cursor to inspect the B-I histogram. Select a square ROI for the analysis, and generate the B-map of the selected ROI. Then save the ASCII file of the B-values associated to the selection.
Import the ASCII in a graphics software to compute the frequency distribution of the data and obtain the average B-value plus or minus S.E.Apply the epsilon equation to derive the average brightness for each cell at each time point of the kinetic run. Normalize the data according to the normalization equation, where B't is the average B-value measured at time t after ligand addition and B'0 is the average B-value measured at the time t equals zero, which is 10 to 20 seconds after ligand additino. Plot the normalized average brightness versus acquisition time to build the kinetic run.
In this study, representative results from two HeLa cells in the same dish expressing mEGFP-FGR1 captured at time zero and seven, after addition of 20 nanograms per milliliter of FGF2, are shown here. Compared with the reference constructs, GPI-mEGFP and GPI-mEGFP-mEGFP dimer, the entire analysis sequence shows the average intensity of the time series. Plot of all B-values.
B-I histogram. B-map of the chosen ROI. And the associated B-distribution histogram.
After stimulation with 20 nanograms per milliliter of FGF2, representative kinetic runs showing the average brightness as function of time describes the slow process of dimerization that persists for several minutes at the cell surface. When stimulated with 50 micrograms per milliliter of NCAM-Fc, the kinetic profile reveals fast and cyclic transitions of the receptor in oligomeric mixtures, which also reaches brightness values above that of the dimer. A normalized average value of three is repeatedly observed.
It is important to minimize the extra variants due to no molecular fluctuations and bleaching. And cells must be well-adhered to the glass-bottom dish, not overgrown, and not piled up. If we are interested in a protein that diffuses faster inside intracellular compartments, we can apply faster zero times and use scanning on focal or multiphoton microscopes to image inside the cell.
With our approach, we minimize the detrimental effects of photobleaching when we want to explore the dynamics of events such as dimerization. These events control a variety of cellular responses and are very difficult to prove in live cells with other techniques.
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