Imaging and Analysis of Mitochondrial Dynamics in Living Cells

Ekanayake, Sanjaya B.; Zawily, Amr M. El; Paszkiewicz, Gaël; Rolland, Aurélia; Logan, David C.

doi:10.1007/978-1-4939-2639-8_16

Cited by 11 publications

(4 citation statements)

References 27 publications

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“…The physics of mitochondrial motion has been characterized by elegant previous work ( Logan and Leaver, 2000 ; Logan, 2003 , 2006 ; Arimura et al., 2004 ; Scott and Logan, 2008 ; Arimura, 2018 ) using mitochondrial GFP lines, staining, and live imaging. This work has demonstrated the use of actin filaments by mitochondria as a means of transport within the plant cell ( Van Gestel et al., 2002 ; Doniwa et al., 2007 ; Avisar et al., 2009 ; Wang and Hussey, 2015 ; Breuer et al., 2017 ) and consequent cytoplasmic streaming ( Shimmen and Yokota, 2004 ; Ekanayake et al., 2015 ; Peremyslov et al., 2015 ; Tominaga and Ito, 2015 ). Logan et al.…”

Section: Introductionmentioning

confidence: 99%

Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity

2021

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Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity Graphical abstract Highlights d Dynamic social networks of plant mitochondria reflect physical organellar encounters d Network analysis and modeling show priorities and tradeoffs for mitochondrial motion d Mitochondria in plant cells trade off physical spacing against social connectivity d Plant cells favor efficient networks with high potential for information exchange

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Section: Introductionmentioning

confidence: 99%

Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity

2021

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“…Over the past decade, the significance of the mitochondrial network has been increasingly appreciated, motivating the development of various approaches to analyze it. Protocols enabling imaging of mitochondrial morphological network are currently available for both wide-field epifluorescence microscopy and high-resolution laser scanning confocal microscopy ( Mitra and Lippincott-Schwartz, 2010 ; Chevrollier et al, 2012 ; Nikolaisen et al, 2014 ; Ekanayake et al, 2015 ). A custom-built super-resolution microscope has also been used to image submitochondrial distribution of voltage-dependent anion channel isoforms, but only in fixed cells ( Neumann et al, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

Meshed neuronal mitochondrial networks empowered by AI-powered classifiers and immersive VR reconstruction

Liu

et al. 2023

Front. Neurosci.

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Mitochondrial networks are defined as a continuous matrix lumen, but the morphological feature of neuronal mitochondrial networks is not clear due to the lack of suitable analysis techniques. The aim of the present study is to develop a framework to capture and analyze the neuronal mitochondrial networks by using 4-step process composed of 2D and 3D observation, primary and secondary virtual reality (VR) analysis, with the help of artificial intelligence (AI)-powered Aivia segmentation an classifiers. In order to fulfill this purpose, we first generated the PCs-Mito-GFP mice, in which green fluorescence protein (GFP) could be expressed on the outer mitochondrial membrane specifically on the cerebellar Purkinje cells (PCs), thus all mitochondria in the giant neuronal soma, complex dendritic arborization trees and long projection axons of Purkinje cells could be easily detected under a laser scanning confocal microscope. The 4-step process resolved the complicated neuronal mitochondrial networks into discrete neuronal mitochondrial meshes. Second, we measured the two parameters of the neuronal mitochondrial meshes, and the results showed that the surface area (μm2) of mitochondrial meshes was the biggest in dendritic trees (45.30 ± 53.21), the smallest in granular-like axons (3.99 ± 1.82), and moderate in soma (27.81 ± 22.22) and silk-like axons (17.50 ± 15.19). These values showed statistically different among different subcellular locations. The volume (μm3) of mitochondrial meshes was the biggest in dendritic trees (9.97 ± 12.34), the smallest in granular-like axons (0.43 ± 0.25), and moderate in soma (6.26 ± 6.46) and silk-like axons (3.52 ± 4.29). These values showed significantly different among different subcellular locations. Finally, we found both the surface area and the volume of mitochondrial meshes in dendritic trees and soma within the Purkinje cells in PCs-Mito-GFP mice after receiving the training with the simulating long-term pilot flight concentrating increased significantly. The precise reconstruction of neuronal mitochondrial networks is extremely laborious, the present 4-step workflow powered by artificial intelligence and virtual reality reconstruction could successfully address these challenges.

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“…Intact 7 to 10 day-old seedlings were incubated in the red fluorescent potentiometric dye tetramethylrhodamine methyl ester (TMRM) that accumulates reversibly in mitochondria in response to the inner membrane potential (Brand and Nicholls, 2011). Following incubation in freshly prepared 50 nM TMRM for 15 minutes, seedlings were mounted in TMRM between slide and cover slip within a chamber created using thin double-sided adhesive tape (Ekanayake et al ., 2015). Microscopy was performed using a Zeiss Axioimager Z2 equipped with a Plan-Apochromat 100x/1.40 oil immersion objective and 63HE filter set (Ex: 572/25 nm, Em: 629/62 nm).…”

Section: Methodsmentioning

confidence: 99%

Assessing mitochondrial function in angiosperms with highly divergent mitochondrial genomes

et al. 2018

Preprint

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Angiosperm mitochondrial (mt) genes are generally slow-evolving, but multiple lineages have undergone dramatic accelerations in rates of nucleotide substitution and extreme changes in mt genome structure. While molecular evolution in these lineages has been investigated, very little is known about their mt function. Here, we develop a new protocol to characterize respiration in isolated plant mitochondria and apply it to species of Silene with mt genomes that are rapidly evolving, highly fragmented, and exceptionally large (∼11 Mbp). This protocol, complemented with traditional measures of plant fitness, cytochrome c oxidase activity assays, and fluorescence microscopy, was used to characterize inter-and intraspecific variation in mt function. Contributions of the individual “classic” OXPHOS complexes, the alternative oxidase, and external NADH dehydrogenases to overall mt respiratory flux were found to be similar to previously studied angiosperms with more typical mt genomes. Some differences in mt function could be explained by inter-and intraspecific variation, possibly due to local adaptation or environmental effects. Although this study suggests that these Silene species with peculiar mt genomes still show relatively normal mt function, future experiments utilizing the protocol developed here can explore such questions in a more detailed and comparative framework.

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Imaging and Analysis of Mitochondrial Dynamics in Living Cells

Cited by 11 publications

References 27 publications

Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity

Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity

Meshed neuronal mitochondrial networks empowered by AI-powered classifiers and immersive VR reconstruction

Assessing mitochondrial function in angiosperms with highly divergent mitochondrial genomes

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