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The mitochondrial network is extremely complex, making it very challenging to analyze. A novel MATLAB tool analyzes live confocal imaged mitochondria in timelapse images but results in a large output volume requiring individual manual attention. To address this issue, a routine optimization was developed, allowing for speedy file analysis.
The complex mitochondrial network makes it very challenging to segment, follow, and analyze live cells. MATLAB tools allow the analysis of mitochondria in timelapse files, considerably simplifying and speeding up the process of image processing. Nonetheless, existing tools produce a large output volume, requiring individual manual attention, and basic experimental setups have an output of thousands of files, each requiring extensive and time-consuming handling.
To address these issues, a routine optimization was developed, in both MATLAB code and live-script forms, allowing for swift file analysis and significantly reducing document reading and data processing. With a speed of 100 files/min, the optimization allows an overall rapid analysis. The optimization achieves the results output by averaging frame-specific data for individual mitochondria throughout time frames, analyzing data in a defined manner, consistent with those output from existing tools. Live confocal imaging was performed using the dye tetramethylrhodamine methyl ester, and the routine optimization was validated by treating neuronal cells with retinoic acid receptor (RAR) agonists, whose effects on neuronal mitochondria are established in the literature. The results were consistent with the literature and allowed further characterization of mitochondrial network behavior in response to isoform-specific RAR modulation.
This new methodology allowed rapid and validated characterization of whole-neuron mitochondria network, but it also allows for differentiation between axon and cell body mitochondria, an essential feature to apply in the neuroscience field. Moreover, this protocol can be applied to experiments using fast-acting treatments, allowing the imaging of the same cells before and after treatments, transcending the field of neuroscience.
Cellular mitochondria sit at the center of all physiological states, and a thorough understanding of their homeostasis (mitostasis) and behavior is paramount to assist in identifying pharmacological treatment for a wide range of illnesses, including cancer and Alzheimer's disease1,2.
Mitochondria play crucial cellular roles in energy homeostasis, ATP generation, calcium buffering, and ROS regulation, and mitostasis is essential for maintaining protein homeostasis as molecular chaperones are energy-dependent3. These require a constant and dynamic network m....
NOTE: This protocol has two main steps: a wet lab step, involving cell culture and live confocal microscopy to obtain images of live mitochondria (Figure 1) and an in silico step to analyze obtained images (Figure 2). For automated data analysis of 3D live imaged mitochondria, the MATLAB application Mitometer was used as provided by Lefebvre et al.9. The Routine optimization is written in MATLAB. The software, updated versions an.......
To enhance and accelerate the analysis of output files in .txt format, a routine optimization was coded that reads data consistent with Mitometer .txt output files, with columns representing a frame and lines representing identified mitochondria. The routine optimization produces data in a single value per parameter by averaging the frames for each identified mitochondria and then averaging the results of all mitochondria per visual field. The developed routine reads files from folders numbered from 1 upwards. The Live S.......
Live cell imaging produces large files that require serious computing processing, but even the most recent tools require extensive manual input to process. This routine optimization is focused on simplifying the process of mitochondria analysis on the Mitometer because this tool presents a very good balance between user input and data output. A comprehensive comparison between different tools for mitochondria image analysis has previously been reviewed10. While other pipelines are more focused on .......
Image acquisition was performed in the LiM facility of iBiMED, a node of PPBI (Portuguese Platform of BioImaging): POCI-01-0145-FEDER-022122. This work was supported by FCT (EXPL/BTM-SAL/0902/2021) LCF (CI21-00276), a grant to DT from the Fundação para a Ciência e Tecnologia of the Ministério da Educação e Ciência (2020.02006.CEECIND), a grant from ATG-The Gabba Alumni Association to VP, and the Institute for Biomedicine-iBiMED, University of Aveiro.
....Name | Company | Catalog Number | Comments |
AM580 | Sigma-Aldrich | A8843 | |
BDNF | Thermo-Fisher | RP8642 | |
BMS493 | Tocris Bioscience | 3409 | |
CD2314 | Tocris Bioscience | 3824 | |
Ch55 | Tocris Bioscience | 2020 | |
Foetal Bovine Serum | Thermo-Fisher | 10270106 | |
GraphPad Prism v4.0 | GraphPad Software, La Jolla | n/a | |
Ham’s F12 Nutrient Mix | Thermo-Fisher | 21765029 | |
MATLAB R2022a | MathWorks | n/a | |
Minimal Essential Medium | Thermo-Fisher | 31095 | |
Nunc Glass Bottom Dishes | Thermo-Fisher | 150680 | |
Phosphate Buffer Saline Solution | Thermo-Fisher | 28372 | |
Retinoic acid | Sigma-Aldrich | R2625 | |
TMRM | Thermo-Fisher | T668 | |
Zeiss LSM 510 | Carl Zeiss | n/a | Equiped with live-cell imaging culture chamber and 63x oil immersion objective |
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