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Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons
Chapters
Summary October 31st, 2020
This protocol shows how to employ super-resolution microscopy to study protein co-localization in primary neuronal cultures.
Transcript
Synapses are the functional elements of neurons and their defects or losses are at the basis of several neurodegenerative and neurological disorders. Imaging studies are widely used to investigate their function and plasticity in physiological and pathological conditions. Because of their size and structure, localization studies of proteins require high-resolution imaging techniques.
In this protocol, we describe a procedure to study in primary neurons the co-localization of target proteins with synaptic markers at a super-resolution level using structured illumination microscopy. SIM is a patterned light illumination technique that doubles the spatial resolution of widefield microscopy, reaching a detail of around 100 nanometers. The protocol indicates the required controls and settings for robust co-localization studies and an overview of the statistical methods to analyze the imaging data properly.
The key to allowing the analysis at a super-resolution level is, however, the reagents used during acquisition, such as chambered coverslips and mounting solutions compatible with the diffraction index of the objective. To obtain a mouse hippocampal primary neuron, isolate hippocampi from P1 to P4 pups. Plate cells at 70, 000 cells per well in a volume of 200 microliters per well.
Wait until hippocampal primary neurons are fully matured 12 to 14 days after plating to perform co-localization studies. Add 4%paraformaldehyde, PFA, in PBS 200 microliters per well to neurons to fix them quickly. Remove the solution and incubate the samples with 1%bovine serum albumin, BSA, in PBS at 200 microliters per well for one hour at room temperature to passively cover all free-binding surfaces of the plate with an irrelevant protein for the analysis.
A BSA-based blocking buffer without Triton X-100 reduces the antibody background more efficiently than the same buffer with 0.2%Triton X-100. Add the primary antibody. As a negative control, do not add any primary antibody to one of the wells.
Mount cells using a SIM-compatible mountant, e.g. ProLong Glass Antifade Mountant. Cover and protect the cells with a coverglass, for example, a round coverglass with a diameter of eight millimeters.
Square ones can also be used. Store the chambered coverslips at room temperature and wait at least 48 hours before acquiring images. Diamond glass requires at least two days of curing before super-resolution acquisitions.
Use two strategies to assure antibody specificity. The first one is the use of at least two different antibodies targeting the same substrate. The second strategy is antibody neutralization by incubation with the purified protein target, or the used to raise the antibody.
We routinely use an N-SIM super-resolution microscope manufactured by Nikon for our analysis. The instructions that follow are to be intended for the acquisition of SIM images independently of the microscope of use. It is also important to maximize the performance of the microscope to perform an accurate calibration of the instruments, including correction ring, laser alignment, and grating block focusing.
Before the acquisition of SIM images, the system requires a proper calibration with specific sub-resolution size fluorescent beads. An example are TetraSpeck microspheres. These beads are stained with different fluorescent dyes to allow the calibration of different lasers with one sample.
In a water bath, sonicate around 1.8 times 10 to the 8th fluorescent microspheres for 10 minutes. Dilute the fluorescent microspheres one in 500 in double distilled water. Sonicate a second time for an additional 10 minutes.
Pipette 15 microliters of the diluted beads into a well of a chambered coverslip. Let the solution dry for five minutes at room temperature. Add 10 microliters of the mounting solution, e.g.
ProLong Glass, and place an eight millimeter coverslip on top. Wait at least 48 hours to allow a proper curing. Turn on the microscope and lasers.
Let the system warm up to reach thermal equilibrium of all microscope components and the SIM super-resolution microscope system requires at least three hours. Select the 100X objective. Start the calibration by aligning the lasers to the center of the diffraction grating block.
In the N-SIM system, a micrometer knob and a dedicated camera allow centering of the light beams to the target. Insert the chambered coverslip of the microscope for viewing. Set the system to the chambered coverslip thickness by adjusting the objective correction cover.
NIS Software, the proprietary software provided with N-SIM super-resolution microscope systems, has an automatic function to regulate correction of colors. Adjust grating block focus for each channel to ensure focused structured pattern illumination on the sample. The software provides an automatic function for this task.
Acquire raw 3D SIM images of the multicolor microspheres. Calculate for each separate wavelength the Fourier transform of the super-resolved image. If the transformed image fails to obtain a correct flower-like pattern, restart calibration since super-resolution has not been achieved.
In the super-resolved image, select a single microsphere and calculate its intensity profile for each channel to measure the resolution achieved. It should now be close to 100 nanometers laterally. Perform channel registration by overlaying a multi-channel acquisition of the microspheres.
The goal is to collimate all channel signals laterally and axially. This will eliminate chromatic aberrations due to the misalignment of the different channels and help the co-localization analysis. Confirm the quality of calibration by using the functions illumination phase step and illumination patterned focus of SIMcheck, a suite of plugins for the open source application ImageJ.
Start analyzing the sample using a 40X objective in confocal or widefield mode. This allows navigation of the sample, maintaining good detail and a large field of view. Use MAP2 antibody signal to detect an area representing neuronal processes.
Acquire images of the sample in confocal mode to determine the quality of the staining. Switch to the objective 100X. Apply oil to the 100X objective.
Acquire a widefield or confocal image that will be used later to assess the quality of the super-resolved image. Switch to 3D SIM mode. Using dialogue windows to set the parameters for acquisition, select the highest bit depth setting available to maximize color information.
Typically, 16 bit is the standard choice. Moreover, to improve signal-to-noise ratio, select a low-frequency value for acquisition, such as one megahertz. Using histogram windows, set laser power to obtain a linear response of signal to avoid loss of information, limit saturated pixels in the images.
The N-SIM system uses an Andor iXon3 camera. When working at 16 bit, choose a target intensity of 16, 000 to ensure the linear response of the camera. Alternatively, choose a range between 30, 000 to 45, 000 to maximize the dynamic range of the acquisitions.
Set the laser power between 0.1%and 50%when imaging the samples and the exposure times between 50 milliseconds and two seconds. Laser powers above 50%may cause rapid photobleaching of the fluorophores in use. Start acquiring the images in 3D SIM mode.
Use SIMcheck, a suite of free plugins for ImageJ, to assess the quality of acquisitions of the raw images. If SIMcheck does not detect any artifacts or quality issues, acquire a minimum of 10 images from full technical replicates to allow statistical analysis. Acquired images are raw data that needs to be processed to obtain reconstructed SIM images that will be used for further analysis.
In the protocol, we suggest to use synaptophysin and PSD-95 as pre and post synaptic markers. Additional markers can, however, be used. A huge body of literature supports the use of other proteins, such as drebrin and bassoon as synaptic markers.
3D SIM acquired images are raw images that need to be processed to obtain reconstructed super-resolved images. Incorrect reconstruction of raw images can lead to artifacts that would affect the analysis of the samples. Great attention should therefore be paid to properly choosing reconstruction parameters.
Process the raw images using the microscope reconstruction analysis software to obtain a super-resolved image. Alternatively, use a freely available ImageJ plugin fairSIM to reconstruct the raw images. Calculate the Fourier transform of the super-resolved images using the microscope reconstruction software or ImageJ plugin SIMcheck.
A good reconstructed image should return, for each channel, a flower-like image. If the reconstructed images fail to recreate a flower-like shape, restart from the raw images and reconstruct them by modifying reconstruction parameters, such as linear filtering, apodization, and zero order suppression. In the NIS Software using the preview to monitor how changing the parameters affects the final resolved image, modify the parameter's illumination modulation contrast, high-resolution noise suppression, and out of focus suppression.
Analyze the reconstructed image to unbiasedly detect artifacts by using NanoJ-SQUIRREL, an ImageJ-based plugin, to assess the quality of super-resolved images. In our analysis of co-localization, we used two approaches. The first one is a visual approach based on the profile analysis that shows single events of co-localization and that identifies the contribution of each channel.
As a first step to study co-localization between synaptic markers and a protein of interest, take a super-resolved image and analyze a single locus to determine signal overlap. Identify a single locus on the super-resolved image. Obtain the intensity profiles of the fluorescent signals to the locus of interest.
If profile analysis has suggested single locus co-localization, a more general analysis of the whole image can be carried out by calculating Pearson's and Mander's coefficients. Use JACoP, an ImageJ plugin, to determine two parameters of co-localization, Pearson's and Mander's. After having calibrated the system and assessed the quality of the reconstructed images, we next started analyzing the primary neuronal cultures stained with an antibody against MAP2, a neuronal marker, PSD-95, a postsynaptic marker, and our target protein SUMO1.
We first analyzed the sample performing four-channel confocal microscopy with a 40X objective. Upon selecting an area representing neuronal processes, we switched to a 100X objective. We acquired both confocal and SIM images of the same area to assess quality of reconstruction with NanoJ-SQUIRREL and perform co-localization analysis.
Elucidating the structure and composition of the synapse is crucial for the understanding of both physiological and pathological processes that regulate memory and cognition. While in normal state synapses are the building blocks of memory, they are also at the basis of complex neurological disorders, such as one of the most common forms of dementia Alzheimer's disease. The protocol described here allows the study of protein composition of synapses with a super-resolution microscopy technique called structured illumination microscopy.
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