Measurements of morphological properties of mitochondria e.g. length or numbers using built-in pipelines

This protocol describes how to record and analyze fluorescence images to determine shapes of (visually) individual mitochondria. Generic guidelines are given for setting up confocal or wide-field microscopy for image acquisition and a step-by-step approach to analyze recorded images. Segmented images can be used to measure morphological parameters, such as length, width and roundness, and how these properties change in time. Results can be graphed to show how do mean properties of a population of mitochondria the view field or bounded by ROIs change in time, or spreadsheet output includes morphological parameters for each mitochondrion in each frame or select parameters as population means or for individual mitochondria.

Another protocol describing further analysis options is also provided: Measurements of mitochondrial morphological properties, velocities and intensities in populations or individual mitochondria

Equipment

Microscopy requirement:

The assay works with wide-field (epifluorescence),  and confocal microscopy.  The epifluorescence microscope has to be capable recording of z-stacks and low-light level time lapse imaging, e.g. equipped with a fast shutter and high quantum efficiency cooled monochromatic camera. Confocal microscopes trivially work in low-light level mode. Recording of z-volumes is recommended, but the analysis on 2D projection images provides sufficiently reliable results.

Microscopy guidelines:

• Image cell cultures in coverglass bottomed dishes.

• If looking mitochondrial dynamics in mammalian cells, thermostat the sample to 37C using heated environment chamber or heated stage and lens.

• Use the highest available NA (numerical aperture) immersion lens.

• Record sparse z-stacks (1.5-2 µm spacing) in order to reduce photo damage. This spacing will be sufficient to capture all mitochondria in a cell and work with projection images.

• Use at least 0.2 µm/pixel resolution or higher (slight oversampling will help image segmentation)

• Never saturate the image (saturated mitochondria will have a hole after high pass filtering and segmentation)

• Record frames for a time lapse not more often than the biology dictates, excessive number of frames will cause photodamage

• Save recordings in the native file format of the microscope, if compatible with Image Analyst MKII (e.g. czi, lsm, nd2, nd, lif, ... see a list here)

Image analysis in Image Analyst MKII

Tutorial data set: Mitochondrial motion assay / Metamorph (use position 7 only this is included to this zip file!)

1. Open the recording in Image Analyst MKII using the main toolbar button or File main menu. Alternatively use drag and drop. If loading lsm files, select Zeiss Multi Time Lapse as file type to provide control over projection.
2. In the Multi-Dimensional Open dialog:
   1. In the Open tab select the stage position and channel to be opened.
   2. If the recording has a z-dimension, in the Settings tab select the way z-projection. For this analysis mean or maximum projection can be used.
   3. Note: this method does not use filtering before the z-projection during opening, therefore do not turn spatial filtering on.
   4. Press the Open button.

A) Measurements of all morphological parameters of all mitochondria in all frames

To print all morphological parameters of all mitochondria in all frames to a spreadsheet use the Morphological Measurements / Measure mitochondrial shape parameters pipeline. Use this pipeline on the raw images. The measured morphological properties are described here. Note: that individual mitochondria in consecutive frames with identical serial number do not correspond to each other, unless the segmented images is tracked first.

1. To invoke the pipeline go to the Pipelines main menu and select: Morphological Measurements / Measure mitochondrial shape parameters. Set its parameters as follows:
   1. Largest mitochondrion size (width in pixels): Give an approximate width of the largest mitochondria. This value controls the high pass filter to suppress larger than mitochondrial details. It does not act as a classifier for mitochondria, so slightly larger objects will also appear in the image. Decrease this value if smaller mitochondria are lost during segmentation. Increase this value if noise passes through from background. It's value for the tutorial data set is 5.
   2. Sensitivity (top range scaling, percentile): A percentile value, typically between 95-99.99 percentile. Decrease this value to increase sensitivity, if dimmer mitochondria are lost during analysis, or if bright debris is present in the image. Increase this value if noise passes through from background.  It's value for the tutorial data set is 99.5.
   3. Minimum size (area, pixels): Minimum size of mitochondria to detect. This is an object classifier, smaller objects than the specified size will be removed. Decrease this value if smaller mitochondria are lost during the analysis. Increase this value if noise passes through from background.  It's value for the tutorial data set is 5.
2. To process a loaded recording either right-click the image and select "Process this with Segment Mitochondria" or press the  or main toolbar buttons.
3. If needed, adjust the analysis considering point #1 above.
   • To re-run the analysis use the button in the main toolbar or on the bottom of the Multi-Dimensional Open dialog and select "Clear and Run Pipeline...". This will perform both loading and processing.
4. Use the File/Save Excel Data main menu item to save the results.

B) Measurement of the mean length or total number of mitochondria

To measure the mean length of mitochondria (as skeletal length - the length in the centerline) use the Morphological Measurements / Measure mitochondrial skeletal length pipeline. This will plot the mean length of all mitochondria in the view field as a time course. Use this pipeline on the raw images.

1. To invoke the pipeline go to the Pipelines main menu and select: Morphological Measurements / Measure mitochondrial skeletal length. Set its parameters as follows:
   1. Largest mitochondrion size (width in pixels): Give an approximate width of the largest mitochondria. This value controls the high pass filter to suppress larger than mitochondrial details. It does not act as a classifier for mitochondria, so slightly larger objects will also appear in the image. Decrease this value if smaller mitochondria are lost during segmentation. Increase this value if noise passes through from background. It's value for the tutorial data set is 5.
   2. Sensitivity (top range scaling, percentile): A percentile value, typically between 95-99.99 percentile. Decrease this value to increase sensitivity, if dimmer mitochondria are lost during analysis, or if bright debris is present in the image. Increase this value if noise passes through from background.  It's value for the tutorial data set is 99.5.
   3. Minimum size (area, pixels): Minimum size of mitochondria to detect. This is an object classifier, smaller objects than the specified size will be removed. Decrease this value if smaller mitochondria are lost during the analysis. Increase this value if noise passes through from background.  It's value for the tutorial data set is 5.
   4. Place positions into columns: This parameter affects how the data is printed into the spreadsheet. When multi stage position recordings are analyzed,  time courses from consecutive positions will appear next to each other if yes, rather than appending results below the data corresponding the previous position.
2. To process a loaded recording either right-click the image and select "Process this with ..." or press the  or main toolbar buttons.
3. If needed, adjust the analysis considering point #1 above.
   • To re-run the analysis use the button in the main toolbar or on the bottom of the Multi-Dimensional Open dialog and select "Clear and Run Pipeline...". This will perform both loading and processing.
4. To constrain the analysis of of mitochondrial length to a specific area of the image:
   1. Draw one or more area-type ROI:
   2. Select the Plotting/Plot Morphological Parameters of Segments function, and set its parameters as follows:
      1. Morphological parameter: area
      2. Plot type: Mean
      3. Constrain to ROIs: Yes
   3. Press the main toolbar buttons or right-click the image and select "Process this with...".
5. Use the File/Save Excel Data main menu item to save the results.
6. To measure number of mitochondria repeat #4 with setting number as morphological parameter.

C) Measurement of the mean properties in mitochondrial populations

To measure the mean of a mitochondrial morphological parameter use the Morphological Measurements / Measure mitochondrial MEAN shape parameters pipeline. This will plot the chosen morphological parameter as a mean of all mitochondria in the view field as a time course. Run this pipeline on the raw images.

1. To invoke the pipeline go to the Pipelines main menu and select: Morphological Measurements / Measure mitochondrial MEAN shape parameters. Set its parameters as follows:
   1. Largest mitochondrion size (width in pixels): Give an approximate width of the largest mitochondria. This value controls the high pass filter to suppress larger than mitochondrial details. It does not act as a classifier for mitochondria, so slightly larger objects will also appear in the image. Decrease this value if smaller mitochondria are lost during segmentation. Increase this value if noise passes through from background. It's value for the tutorial data set is 5.
   2. Sensitivity (top range scaling, percentile): A percentile value, typically between 95-99.99 percentile. Decrease this value to increase sensitivity, if dimmer mitochondria are lost during analysis, or if bright debris is present in the image. Increase this value if noise passes through from background.  It's value for the tutorial data set is 99.5.
   3. Minimum size (area, pixels): Minimum size of mitochondria to detect. This is an object classifier, smaller objects than the specified size will be removed. Decrease this value if smaller mitochondria are lost during the analysis. Increase this value if noise passes through from background.  It's value for the tutorial data set is 5.
   4. Morphological parameter: Select the morphological parameter of interest: "number", "area", "perimeter", "diameter", "filament length", "branch points", "shape factor", "fiber length", "fiber breadth", "distance from ROI". Note: to measure distance from ROI, draw an ROI before running the pipeline.
   5. Place positions into columns: This parameter affects how the data is printed into the spreadsheet. When multi stage position recordings are analyzed,  time courses from consecutive positions will appear next to each other if yes, rather than appending results below the data corresponding the previous position.
2. To process a loaded recording either right-click the image and select "Process this with ..." or press the  or main toolbar buttons.
3. If needed, adjust the analysis considering point #1 above.
   • To re-run the analysis use the button in the main toolbar or on the bottom of the Multi-Dimensional Open dialog and select "Clear and Run Pipeline...". This will perform both loading and processing.
4. To constrain the analysis of mitochondrial length to a specific area of the image:
   1.  Draw one or more area-type ROI:
   2. Select the Plotting/Plot Morphological Parameters of Segments function, and set its parameters as follows:
      1. Morphological parameter: set this as above
      2. Plot type: Mean
      3. Constrain to ROIs: Yes
   3. Press the main toolbar buttons or right-click the image and select "Process this with...".
5. Use the File/Save Excel Data main menu item to save the results.

Protocol by Akos A. Gerencser 03/22/2016 V1.0        

These or similar approaches were described used in the following papers:

1. Gerencser A. A. and Nicholls D. G. (2008) Measurement of Instantaneous Velocity Vectors of Organelle Transport: Mitochondrial Transport and Bioenergetics in Hippocampal Neurons. Biophys J. 2008 Sep 15;95(6):3079-99.

2. Choi S.W., Gerencser A.A., Nicholls D.G. (2009) Bioenergetic analysis of isolated cerebrocortical nerve terminals on a microgram scale: spare respiratory capacity and stochastic mitochondrial failure. J Neurochem. 2009 May;109(4):1179-91

3. Choi SW, Gerencser AA, Lee DW, Rajagopalan S, Nicholls DG, Andersen JK & Brand MD. Intrinsic bioenergetic properties and stress-sensitivity of dopaminergic synaptosomes. J. Neurosci. 2011 Mar 23;31(12):4524-34