14 average number of shortest paths crossing each node in the network. The mean connected 414 component number is the average number of disconnected subgraphs within the network. 415 416 Accession numbers 417 All analysis code and data is available from Github at 418 https://github.com/StochasticBiology/plant-mito-dynamics 419 420 Acknowledgments 421 422 J.M.C. is supported by the BBSRC and University of Birmingham via the MIBTP doctoral 423 training scheme (grant number BB/M01116X/1). This project has received funding from the 424 European Research Council (ERC) under the European Union’s Horizon 2020 research and 425 innovation programme (grant
Open resource ↗StochasticBiology/plant-mito-dynamics · pdf-raw-page:14 lines:1-67Unverified paper record
Altered collective mitochondrial dynamics in an Arabidopsis msh1 mutant compromising organelle DNA maintenance
bioRxiv · 24 Oct 2021 · 10.1101/2021.10.22.465420
Abstract
Summary Mitochondria form highly dynamic populations in the cells of plants (and all eukaryotes). The characteristics of this collective behaviour, and how it is influenced by nuclear features, remain to be fully elucidated. Here, we use a recently-developed quantitative approach to reveal and analyse the physical and collective “social” dynamics of mitochondria in an Arabidopsis msh1 mutant where organelle DNA maintenance machinery is compromised. We use a newly-created line combining the msh1 mutant with mitochondrially-targeted GFP, and characterise mitochondrial dynamics with a combination of single-cell timelapse microscopy, computational tracking and network analysis. The collective physical behaviour of msh1 mitochondria is altered from wildtype in several ways: mitochondria become less evenly spread, and networks of inter-mitochondrial encounters become more connected with greater potential efficiency for inter-organelle exchange. We find that these changes are similar to those observed in friendly , where mitochondrial dynamics are altered by a physical perturbation, suggesting that this shift to higher connectivity may reflect a general response to mitochondrial challenges.
Plant phenotyping relevance
単なる生物学的測定ではなく、タイムラプス顕微鏡、計算追跡、ネットワーク解析を組み合わせて植物細胞内ミトコンドリアの動態状態を定量化する手法の実質的な適用である。
abstractwe use a recently-developed quantitative approach to reveal and analyse the physical and collective “social” dynamics of mitochondria
abstractcharacterise mitochondrial dynamics with a combination of single-cell timelapse microscopy, computational tracking and network analysis
Code and data availability
The paper explicitly states that all analysis code and data are available on the authors' GitHub repository, and a supplementary time-lapse microscopy video (phenotyping input) is hosted publicly. The Arabidopsis msh1 seed stock (N3372) used for the phenotyping is also publicly available from the NASC stock centre.
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