High brain-iron accumulation in BPAN is caused by dysfunction of the autophagy protein. But underlying molecular mechanisms are unknown. This protocol provides an assessment for lysosomal ferritin degradation, such as ferritinophagy.
This technique offers the quantitative, image-based analysis method to measure lysosomal ferritin degradation in single cells. Conveniently, the multiplex approach can be extended by including appropriate antibodies or dyes to measure additional cellular parameters. This method can identify and differentiate autophagy dependent and independent pathways for lysosomal ferritin degradation.
It is important for understanding dysfunctional iron homeostasis in BPAN at the cellular level. Our PhD student, Carmen Pastor-Maldonado, will demonstrate the method for analyzing lysosomal ferritin degradation, such as ferritinophagy. Begin the self-fixation by aspirating the treatment medium from the patient-derived, beta-propeller-associated neuro-degeneration cells seated in a glass-bottom 96-well plate, and washing them two times with Dulbecco's phosphate-buffered saline, or DPBS.
Add 100 microliters of 3.7%paraformaldehyde, or PFA, per well before fixing the cells for 20 minutes at room temperature in the darkness. After 20 minutes, remove the PFA and wash the cells two times with PBST before blocking the cells in PBST containing 1%bovine serum albumin, or BSA, for one hour at four degrees Celsius. Next, wash the cells two times with PBST before applying 50 microliters of the primary antibody mix prepared in PBST per well.
Wrap the plates with parafilm, and incubate overnight at four degrees Celsius. The following morning, prepare the secondary antibody mix in PBST at a one-to-200 ratio. After washing the cells two times with PBST, apply 50 microliters of the freshly-prepared secondary antibody mix per well.
Incubate the cells at four degrees Celsius for one hour in the dark. Again, give two washes with PBST, and add 100 microliters of freshly-prepared five micrograms-per-microliters of 4'6-diamidino-2-phenylindole, or DAPI, solution per well and incubate the plate. Give two PBS washes before adding 50 microliters of PBS to each well, then incubate the wrapped plates at four degrees in the dark.
For automated imaging of the cells, replace the PBS in the plate with 50 microliters of fresh PBS at room temperature. Cover the plate with aluminum foil to transfer it to the microscopy room. Turn the confocal laser-scanning microscope on, set a sample-holder for 96-well plates on the microscope table, and select a 40x objective.
Adjust the imaging settings by selecting the lasers and filters in Smart Setup, and assigning the tracks for optimal image quality and speed. To select the type of experiment, click on Tiles"to enable the selecting option and save the determined XY positions on the plate. In the Imaging Setup"module, visualize the acquisition channels, the assigned tracks, and their excitation and emission wavelengths.
In the Acquisition Mode"module, select Scan Speed"as six, Direction"as bidirectional, Averaging"as 2x, and Bits per Pixel"as eight. In the channels module, fine-tune the laser power, pinhole, and master gain for each channel individually to achieve properly-exposed images without over-saturating them. Next, click on the Focus Strategy"module and select Combine Software Autofocus and Definite Focus.
Under Reference Channel and Offsets, select the most stable, brightest channel as a reference. Under Stabilization Event Repetitions and Frequency, select Standard. In the Software Autofocus"module, select Mode"as Intensity, Search"as Smart, Sampling"as Fine"and Relative Range.
Next, click on the Tiles"module. Select positions as Single Positions. Under Advanced Setup, navigate through the plate, identify a position for imaging, and click on the button under the Position Setup"tab.
To label each position with additional information, open the Properties"tab and click on the wheel icon next to the category dropdown menu, then click on New"to open a new dialogue box to enter a new category name. To assign a category to a certain position, select the position, click on the Properties"tab, go to the categories dropdown menu and select the corresponding label. Under Sample Carrier, select Multiwell 96 Cellvis glass bottom 0.
Click on Calibrate"to calibrate the microscope to the plate surface. Choose between one point or seven-point calibration depending on the system's specifications. Under Options, select a tile overlap of 10%Under Travel in Tile Regions, select Comb"and tick Use Stage Speed from Stage Control, Use Stage Acceleration from Stage Control"and Image Pyramid During Acquisition.
Once done, run image acquisition, save the image results as CZI file, and the image metadata as CSV files on a portable hard drive. Export the images as TIF files. Create a separate metadata-spreadsheet file for high-throughput image analysis with the position, well, condition, series, and set columns.
Retrieve the appropriate data from the original metadata file that comes from confocal laser-scanning microscopy, and fill these columns. Launch CellProfiler 4.2.4 by double-clicking and import the CellProfiler pipeline by drag and drop. Before adapting the CellProfiler pipeline, drag and drop individual CZI image files, or a folder containing multiple CZI image files, to the image module.
In the NamesAndTypes"module, replace the C1-C3 code with a code that allows the software to identify and sort the single-channel images to be analyzed. To optimize the numeric entries in the modules, tune the pipeline settings for the IdentifyPrimaryObjects"and IdentifySecondaryObjects"modules. To track the adjustments, select the test-mode option by clicking on the Start Test Mode"button, or, alternatively, the Step"button between modules A.This will result in a pop-up window showing how an image would be analyzed with those settings.
Fine-tune the settings for optimal recognition. Once the pipeline is optimized, end the test mode and execute the analysis by activating the Exit Test Mode"before clicking on the Analyze Images"button. After the analysis, verify the cell and puncta detection accuracy by comparing the input images with the overlay outputs generated by CellProfiler.
If not satisfactory, adjust the numerical values in the different modules until the analysis result is sufficiently accurate. This technique made the software-based cell recognition and the ferritin and LAMP2 recognition possible. When the lysosomal degradation of ferritin was blocked by adding bafilomycin A1, the co-localization of endogenous ferritin in LAMP2 increased.
The increase was consistent with its ability to inhibit lysosomal V-ATPase enzymes blocking ferritinophagy. High-quality immunostaining is mandatory to analyze images accurately and automatically, it is therefore advisable to conduct preliminary experiment to test things like antibody dilutions and cell densities. This protocol can be extended to perform correlative light and electron microscopy analysis.
For this, precise conclusions can be drawn, but the type of lysosomal ferritin degradation, for example, via ferritinophagy or autophagy-independent pathways. These strategies are being tested to determine whether they can capture the specific cellular behavior of BPAN patient-derived cells, and the difference from cells where. Is not mutated.
This method is part of such development.
