MIRO1 mutation leads to metabolic maladaptation resulting in Parkinson's disease-associated dopaminergic neuron loss.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Alise Zagare, Thomas Sauter, Kyriaki Barmpa, Maria Pacheco, Rejko Krüger, Jens Christian Schwamborn, Claudia Saraiva
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Abstract

MIRO1 is a mitochondrial outer membrane protein important for mitochondrial distribution, dynamics and bioenergetics. Over the last decade, evidence has pointed to a link between MIRO1 and Parkinson's disease (PD) pathogenesis. Moreover, a heterozygous MIRO1 mutation (p.R272Q) was identified in a PD patient, from which an iPSC-derived midbrain organoid model was derived, showing MIRO1 mutant-dependent selective loss of dopaminergic neurons. Herein, we use patient-specific iPSC-derived midbrain organoids carrying the MIRO1 p.R272Q mutation to further explore the cellular and molecular mechanisms involved in dopaminergic neuron degeneration. Using single-cell RNA sequencing (scRNAseq) analysis and metabolic modeling we show that the MIRO1 p.R272Q mutation affects the dopaminergic neuron developmental path leading to metabolic deficits and disrupted neuron-astrocyte metabolic crosstalk, which might represent an important pathogenic mechanism leading to their loss.

MIRO1突变导致代谢失调,导致帕金森病相关多巴胺能神经元丢失。
MIRO1是线粒体外膜蛋白,对线粒体分布、动力学和生物能量学具有重要意义。在过去的十年中,有证据表明MIRO1与帕金森病(PD)发病机制之间存在联系。此外,在PD患者中发现了一个杂合的MIRO1突变(p.R272Q),由此衍生出ipsc衍生的中脑类器官模型,显示出MIRO1突变依赖于多巴胺能神经元的选择性损失。在此,我们使用携带MIRO1 p.R272Q突变的患者特异性ipsc衍生的中脑类器官来进一步探索涉及多巴胺能神经元变性的细胞和分子机制。通过单细胞RNA测序(scRNAseq)分析和代谢模型,我们发现MIRO1 p.R272Q突变影响多巴胺能神经元的发育路径,导致代谢缺陷和神经元-星形胶质细胞代谢串扰中断,这可能是导致其丢失的重要致病机制。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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