Mitochondrial branch and thickness

Introduction

The purpose to this Fiji macro is analyzing the mitochondrial complexity in C. elegans. Comparing to the previous case study in Drosophila[1], the 3D thickness is also included in this analysis. We employed plugins of Local Thickness[2,3], BoneJ [4] in conjunction with 3D object counter to construct the analysis results. The measurements in the autosaved excel file include the volume, intensity, local thickness, as well as the width, height, and depth of the bounding box The analyzed result can be inspected with any 3D modeling software packages such as Imaris.

#Examples

1. The confocal image of mitochondria in C.elegans (green channel).

#Description 

FIJI

1. Open the image with bioformat importer.
2. The local background is defined by applying a Gaussian blurring operation with a large sigma value and been subtracted from the raw image.
3. Subsequently, the threshold was adjusted first automatically by default and allowed to be manually fine tuned to generate a mitochondrial mask.
4. The thickness, branch complexity and basic 3D geometric analysis  of mitochondria is analyzed by Local Thickness plugin, BoneJ plugin and 3D Object Counter respectively.
5. In addition to the autosaved measurements, the analyzed image named “demo image_Results” was saved as well for data inspection.

Imaris

1. Open the Results folder in the Arena interface.
2. Convert the file type of analyzed image from .tiff to .ims by double-clicking on the image.
3. Three additional channels were created in the raw image dataset—mito mask, tagged mitochondrial skeleton and local thickess. Mito mask was the binarized image based on the fine-tuned threshold for further analysis of thickness and complexity. The branch, center and the terminal of microchondria skeleton was tagged by different gray values in this additional channel while the 3D local thickness of each mitochondria was stored as the gray value as well in another generated channel.
4.  Here is the setting for easier inspection.

5. Generate 3D model from the analyzed image.

Instruction

1. Install Fiji is just ImageJ and Imaris. Fiji Download
2. Download the IJM script and demo image.
3. Open the Fiji software.
4. Make sure you have the BoneJ plugin installed. If not, please install it. BoneJ Installed
5. Drag and drop the image and IJM script to Fiji, then execute it.
6. Fine tune the threshold value according to the hint.
7. The final results are saved to an Excel file for further statistics.
8. Open the analyzed image in Imaris for 3D modeling.

Tutorial

Published with

(Submitting information about publication or project)

Acknowledgements

• We thank Dr. Chun-Liang Pan (Institute of Molecular Medicine, College of Medicine, National Taiwan University) for offering the demo image in developing this workflow.

References