JoVE Logo
Faculty Resource Center

Sign In





Representative Results






Optimized Automated Analysis of Live Neuronal Mitochondria Homeostasis Modulation by Isoform-Specific Retinoic Acid Receptors

Published: July 28th, 2023



1Neuroscience and Signalling Laboratory, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro

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....

Log in or to access full content. Learn more about your institution’s access to JoVE content here

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.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

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.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

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 .......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

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.


Log in or to access full content. Learn more about your institution’s access to JoVE content here

NameCompanyCatalog NumberComments
BDNF Thermo-FisherRP8642
BMS493Tocris Bioscience 3409
CD2314Tocris Bioscience3824
Ch55Tocris Bioscience 2020
Foetal Bovine SerumThermo-Fisher10270106
GraphPad Prism v4.0GraphPad Software, La Jollan/a
Ham’s F12 Nutrient MixThermo-Fisher21765029
MATLAB R2022a MathWorksn/a
Minimal Essential MediumThermo-Fisher31095
Nunc Glass Bottom DishesThermo-Fisher150680
Phosphate Buffer Saline SolutionThermo-Fisher28372
Retinoic acidSigma-Aldrich R2625
TMRM Thermo-FisherT668
Zeiss LSM 510Carl Zeissn/aEquiped with live-cell imaging culture chamber and 63x oil immersion objective 

  1. Trigo, D., Avelar, C., Fernandes, M., Sa, J., da Cruz, E. S. O. Mitochondria, energy, and metabolism in neuronal health and disease. FEBS Letters. 596 (9), 1095-1110 (2022).
  2. Zong, W. X., Rabinowitz, J. D., White, E. Mitochondria and cancer. Molecular Cell. 61 (5), 667-676 (2016).
  3. Clare, D. K., Saibil, H. R. ATP-driven molecular chaperone machines. Biopolymers. 99 (11), 846-859 (2013).
  4. Tourniaire, F., et al. All-trans retinoic acid induces oxidative phosphorylation and mitochondria biogenesis in adipocytes. Journal of Lipid Research. 56 (6), 1100-1109 (2015).
  5. Psarra, A. M., Sekeris, C. E. Nuclear receptors and other nuclear transcription factors in mitochondria: regulatory molecules in a new environment. Biochimica et Biophysica Acta. 1783 (1), 1-11 (2008).
  6. Trigo, D., Goncalves, M. B., Corcoran, J. P. T. The regulation of mitochondrial dynamics in neurite outgrowth by retinoic acid receptor beta signaling. FASEB Journal. 33 (6), 7225-7235 (2019).
  7. Mitra, K., Lippincott-Schwartz, J. Analysis of mitochondrial dynamics and functions using imaging approaches. Current Protocols in Cell Biology. Chapter 4 (Unit 4), 1-21 (2010).
  8. Sajic, M., et al. Impulse conduction increases mitochondrial transport in adult mammalian peripheral nerves in vivo. PLoS Biology. 11 (12), e1001754 (2013).
  9. Lefebvre, A., Ma, D., Kessenbrock, K., Lawson, D. A., Digman, M. A. Automated segmentation and tracking of mitochondria in live-cell time-lapse images. Nature Methods. 18 (9), 1091-1102 (2021).
  10. Chu, C. -. H., Tseng, W. -. W., Hsu, C. -. M., Wei, A. -. C. Image analysis of the mitochondrial network morphology with applications in cancer research. Frontiers in Physics. 10, 855775 (2022).
  11. Creed, S., McKenzie, M. Measurement of mitochondrial membrane potential with the fluorescent dye tetramethylrhodamine methyl ester (TMRM). Methods in Molecular Biology. 1928, 69-76 (2019).
  12. Kovalevich, J., Langford, D. Considerations for the use of SH-SY5Y neuroblastoma cells in neurobiology. Methods in Molecular Biology. 1078, 9-21 (2013).
  13. Sahin, M., Oncu, G., Yilmaz, M. A., Ozkan, D., Saybasili, H. Transformation of SH-SY5Y cell line into neuron-like cells: Investigation of electrophysiological and biomechanical changes. Neuroscience Letters. 745, 135628 (2021).
  14. Trigo, D., et al. Mitochondria dysfunction and impaired response to oxidative stress promotes proteostasis disruption in aged human cells. Mitochondrion. 69, 1-9 (2022).

This article has been published

Video Coming Soon

JoVE Logo


Terms of Use





Copyright © 2024 MyJoVE Corporation. All rights reserved