TITLE: Image_processing_to_investigate_mitophagy_in_HelaM_and_neurons
AUTHORS: OLIVIA  HARDING, Chantell Evans

[DESCRIPTION]
<div class = "text-blocks"><div class = "text-block">This is a method for imaging cells and quantifying subcellular structures in the resulting data. We developed this protocol for assessing clearance of mitochondria involving OPTN and TBK1, however the method could be used for other applications. </div></div>

[STEPS]
?. [Imaging]
Collect images of cells with a confocal microscope at 100X.
?. [Imaging]
Refer to https://svi.nl/NyquistCalculator in order to determine optimal collection parameters
?. [Imaging]
Depending on the analysis, you may collect 3D samples (XYZ or XYT)
?. [Imaging]
Try to maximize the number of cells in the field of view
?. [Image deconvolution]
Use a software such as Huygens to deconvolve the images
?. [Image deconvolution]
When there are multiple cells in one field of view, crop the image prior to deconvolution and save the pre-deconvolved cropped images as .tifs.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Open each image in ImageJ/FIJI
?. [Quantifying mitophagy rings (density, intensity, diameter)]
If applicable, maximally project deconvolved images
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Using channels collected for mitochondria and TBK1, manually draw regions of interest (ROIs) around mitophagy events and add each ROI to the manager
?. [Quantifying mitophagy rings (density, intensity, diameter)]
The criteria for a mitophagy event is: -ring must envelop a rounded mitochondria-ring must be visible around at least half of the mitochondria-if applicable, Parkin must also be present as a ring
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Draw an ROI around the whole cell area using TBK1 channel to delineate cell outline.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Save the set of ROIs for each image
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Open the corresponding pre-deconvolved image in ImageJ/FIJI
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Maximally project this image identically to the deconvolved image
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Project the ROI set onto the pre-deconvolved image in the TBK1 channel
?. [Quantifying mitophagy rings (density, intensity, diameter)]
In the ROI manager, highlight all ROIs, then select Multi-measure and generate measurements for the single channel.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Copy and paste the ROI measurements into an Excel document
?. [Quantifying mitophagy rings (density, intensity, diameter)]
To determine TBK1 recruitment extent, calculate the number of rings divided by the total area of the cell.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
To determine average intensity, calculate the average of the average gray value of all rings in the TBK1 channel
?. [Quantifying mitophagy rings (density, intensity, diameter)]
To determine average diameter, calculate the average of the Feret diameter of all rings
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Proceed to repeat for all cells.
?. [Ring tracking in live cells]
Assess the deconvolved timelapse images to identify events that are visible over the timelapse and remain in focus
?. [Ring tracking in live cells]
Use the Parkin and mitochondria channels to draw ROIs around the forming ring for each timepoint. Save each ROI to the manager.
?. [Ring tracking in live cells]
It is easiest to start at the end of the timelapse (or the end of the sequence when the ring is still visible) when the event is brightest, then move backward through the steps.
?. [Ring tracking in live cells]
Save each event's ROI's as its own set.
?. [Ring tracking in live cells]
Open the corresponding pre-deconvolved timelapse image.
?. [Ring tracking in live cells]
Project each saved ROI onto its corresponding timepoint and measure the intensity within the ROI for Parkin and TBK1 channels.
?. [Ring tracking in live cells]
The timepoint information should be saved in the ROI's data.
?. [Ring tracking in live cells]
Go to timepoint zero and draw an ROI around an area of the cell with no mitochondria, puncta, or aberrations. Save the average gray value measurements of the Parkin and TBK1 channels as the background.
?. [Ring tracking in live cells]
Copy and paste the intensity data from the events and the background to a new Excel document
?. [Ring tracking in live cells]
Subtract the average gray value of the background ROI from each of the mitophagy event ROIs in the respective channels.
?. [Ring tracking in live cells]
Determine the maximum value of Parkin intensity for each event and divide by two for Parkin half-max.
?. [Ring tracking in live cells]
Align all values to Parkin half-max, setting Parkin half-max as zero.
?. [Quantifying % mitochondria with LC3]
Import deconvolved images of mitochondria to Ilastik or other segmentation software.
?. [Quantifying % mitochondria with LC3]
Repeat steps 5-15 for LC3 channel.
?. [Quantifying % mitochondria with LC3]
If using ilastik, develop a segmentation algorithm to identify mitochondria from non-mitochondria. Export segmented images as .tifs
?. [Quantifying % mitochondria with LC3]
Open segmented mitochondria image in ImageJ/FIJI and perform particle analysis to determine the number of discrete mitochondria
?. [Quantifying % mitochondria with LC3]
Calculate % mitochondria that are LC3 positive by dividing the number of LC3 events by total number of mitochondria.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
Maintain a constant depth of projection, i.e. 4 um for each image.
?. [Quantifying mitophagy rings (density, intensity, diameter)]
These steps may also be applied to quantification of OPTN rings.