Giannakis Konstantinos, Chustecki Joanna M, Johnston Iain G
Department of Mathematics, University of Bergen, Bergen, Norway.
School of Biosciences, University of Birmingham, Birmingham, United Kingdom.
Quant Plant Biol. 2022 Sep 9;3:e18. doi: 10.1017/qpb.2022.15. eCollection 2022.
Mitochondria in plant cells usually contain less than a full copy of the mitochondrial DNA (mtDNA) genome. Here, we asked whether mitochondrial dynamics may allow individual mitochondria to 'collect' a full set of mtDNA-encoded gene products over time, by facilitating exchange between individuals akin to trade on a social network. We characterise the collective dynamics of mitochondria in hypocotyl cells using a recent approach combining single-cell time-lapse microscopy, video analysis and network science. We use a quantitative model to predict the capacity for sharing genetic information and gene products through the networks of encounters between mitochondria. We find that biological encounter networks support the emergence of gene product sets over time more readily than a range of other possible network structures. Using results from combinatorics, we identify the network statistics that determine this propensity, and discuss how features of mitochondrial dynamics observed in biology facilitate the collection of mtDNA-encoded gene products.
植物细胞中的线粒体通常所含的线粒体DNA(mtDNA)基因组不到完整的一份。在此,我们探讨线粒体动力学是否可能随着时间推移,通过促进个体间类似于社交网络交易的交换,使单个线粒体“收集”一整套mtDNA编码的基因产物。我们采用一种结合单细胞延时显微镜、视频分析和网络科学的最新方法,来表征下胚轴细胞中线粒体的集体动力学。我们使用定量模型来预测通过线粒体间的相遇网络共享遗传信息和基因产物的能力。我们发现,与一系列其他可能的网络结构相比,生物相遇网络更易于随着时间推移促成基因产物集的出现。利用组合数学的结果,我们确定了决定这种倾向的网络统计量,并讨论了生物学中观察到的线粒体动力学特征如何促进mtDNA编码基因产物的收集。