Lyle Wiemerslage1, Daewoo Lee2. 1. Functional Pharmacology, Department of Neuroscience, Biomedicinska Centrum, Uppsala University, Husargatan 3, Box 593, 75124 Uppsala, Sweden. Electronic address: lyle.wiemerslage@neuro.uu.se. 2. Neuroscience Program, Department of Biological Sciences, Ohio University, Athens, OH 45701, United States. Electronic address: leed1@ohio.edu.
Abstract
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.
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.
Authors: Anthony P Leonard; Robert B Cameron; Jaime L Speiser; Bethany J Wolf; Yuri K Peterson; Rick G Schnellmann; Craig C Beeson; Bärbel Rohrer Journal: Biochim Biophys Acta Date: 2014-11-13
Authors: Abdel Aouacheria; Stephen Baghdiguian; Heather M Lamb; Jason D Huska; Fernando J Pineda; J Marie Hardwick Journal: Neurochem Int Date: 2017-04-28 Impact factor: 3.921
Authors: Bereketeab Haileselassie; Riddhita Mukherjee; Amit U Joshi; Brooke A Napier; Liliana M Massis; Nicolai Patrick Ostberg; Bruno B Queliconi; Denise Monack; Daniel Bernstein; Daria Mochly-Rosen Journal: J Mol Cell Cardiol Date: 2019-04-11 Impact factor: 5.000