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Quantification of mitochondrial morphology in neurites of dopaminergic neurons using multiple parameters.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Functional Pharmacology.
Ohio Univ, Dept Biol Sci, Neurosci Program, Athens, OH 45701 USA.
2016 (English)In: Journal of Neuroscience Methods, ISSN 0165-0270, E-ISSN 1872-678X, Vol. 262, 56-65 p.Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Studies of mitochondrial morphology vary in techniques. Most use one morphological parameter while others describe mitochondria qualitatively. Because mitochondria are so dynamic, a single parameter does not capture the true state of the network and may lead to erroneous conclusions. Thus, a gestalt method of analysis is warranted.

NEW METHOD: This work describes a method combining immunofluorescence assays with computerized image analysis to measure the mitochondrial morphology within neuritic projections of a specific population of neurons. Six parameters of mitochondrial morphology were examined utilizing ImageJ to analyze colocalized signals.

RESULTS: Using primary neuronal cultures from Drosophila, we tested mitochondrial morphology in neurites of dopaminergic (DA) neurons. We validate our model using mutants with known defects in mitochondrial morphology. Furthermore, we show a difference in mitochondrial morphology between cells treated as control or with a neurotoxin inducing PD (Parkinson's Disease in humans)-like pathology. We also show interactions between morphological parameters and experimental treatment.

COMPARISON WITH EXISTING METHODS: Our method is a significant improvement of previously described methods. Six morphometric parameters are quantified, providing a gestalt analysis of mitochondrial morphology. Also it can target specific populations of mitochondria using immunofluorescence assay and image analysis.

CONCLUSIONS: We found that our method adequately detects differences in mitochondrial morphology between treatment groups. We conclude that some parameters may be unique to a mutation or a disease state, and the relationship between parameters is altered by experimental treatment. We suggest at least four variables should be considered when using mitochondrial structure as an experimental endpoint.

Place, publisher, year, edition, pages
2016. Vol. 262, 56-65 p.
National Category
URN: urn:nbn:se:uu:diva-279696DOI: 10.1016/j.jneumeth.2016.01.008ISI: 000372379400006PubMedID: 26777473OAI: oai:DiVA.org:uu-279696DiVA: diva2:908678
NIH (National Institute of Health)
Available from: 2016-03-03 Created: 2016-03-03 Last updated: 2016-05-04Bibliographically approved

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