脑-体线粒体分布模式缺乏一致性,指向组织特异性调节机制。

Life metabolism Pub Date : 2025-04-12 eCollection Date: 2025-06-01 DOI:10.1093/lifemeta/loaf012
Jack Devine, Anna S Monzel, David Shire, Ayelet M Rosenberg, Alex Junker, Alan A Cohen, Martin Picard
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引用次数: 0

摘要

能量转换能力通常被认为是由遗传和环境因素驱动的一致的个体特征。这预示着一些个体的线粒体氧化磷酸化(OxPhos)能力在器官系统中应该一直很高,而另一些个体的线粒体氧化磷酸化(OxPhos)能力则一直很低。在这里,我们使用小鼠和人类的多组织分子和酶分析来测试这一假设。在多达22个小鼠组织中,线粒体OxPhos容量和线粒体DNA (mtDNA)密度在组织之间都不相关(中位数r = -0.01至0.16),这表明在一个组织中线粒体含量或容量高的动物在其他组织中可能含量或容量低。同样,基于RNA测序(RNAseq)的948名女性和男性45个组织的线粒体表达指数(基因型组织表达[GTEx])显示,某些组织之间只有很小到中等程度的一致性,例如脑区域之间(r = 0.26),但脑-体组织对之间没有一致性(r = 0.01)。mtDNA拷贝数(mtDNAcn)在人体组织中也缺乏一致性。在机制上,线粒体基因表达的组织特异性差异部分归因于(i)能量感应途径的组织特异性激活,包括转录辅助激活因子过氧化物酶体增殖体激活受体γ辅助激活因子1- α (PGC-1α)、综合应激反应(ISR)和线粒体生物学的其他分子调节因子,以及(ii)组织间的增殖活性。最后,我们确定了具有不同线粒体分布策略的个体亚群,这些策略映射到不同的临床表型。这些数据提出了一种可能性,即组织特异性能量感应途径可能有助于个体之间特殊的线粒体分布模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brain-body mitochondrial distribution patterns lack coherence and point to tissue-specific regulatory mechanisms.

Energy transformation capacity is generally assumed to be a coherent individual trait driven by genetic and environmental factors. This predicts that some individuals should have consistently high, while others show consistently low mitochondrial oxidative phosphorylation (OxPhos) capacity across organ systems. Here, we test this assumption using multi-tissue molecular and enzymatic assays in mice and humans. Across up to 22 mouse tissues, neither mitochondrial OxPhos capacity nor mitochondrial DNA (mtDNA) density was correlated between tissues (median r = -0.01 to 0.16), indicating that animals with high mitochondrial content or capacity in one tissue may have low content or capacity in other tissues. Similarly, RNA sequencing (RNAseq)-based indices of mitochondrial expression across 45 tissues from 948 women and men (genotype-tissue expression [GTEx]) showed only small to moderate coherence between some tissues, such as between brain regions (r = 0.26), but not between brain-body tissue pairs (r = 0.01). The mtDNA copy number (mtDNAcn) also lacked coherence across human tissues. Mechanistically, tissue-specific differences in mitochondrial gene expression were partially attributable to (i) tissue-specific activation of energy sensing pathways, including the transcriptional coactivator peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), the integrated stress response (ISR), and other molecular regulators of mitochondrial biology, and (ii) proliferative activity across tissues. Finally, we identify subgroups of individuals with distinct mitochondrial distribution strategies that map onto distinct clinical phenotypes. These data raise the possibility that tissue-specific energy sensing pathways may contribute to idiosyncratic mitochondrial distribution patterns among individuals.

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