混合成像分析显示线粒体相关基因扰动的病原形态学特征。

Colin Kremitzki, Jason Waligorski, Graham Bachman, Lina Mohammed Ali, John Bramley, Maria Vakaki, Vinay Chandrasekaran, Purva Patel, Dhruv Mathur, Paul Hime, Robi Mitra, Jeff Milbrandt, William Buchser
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摘要

线粒体相关基因的突变是许多神经退行性疾病的基础,但大多数变异在疾病表型方面的意义仍不确定。数千个基因已被证明调节真核细胞中的线粒体,但这些基因中哪些是线粒体正常功能和动力学所必需的?我们研究了线粒体基因沉默细胞的形态破坏程度,以了解预期线粒体表型的遗传贡献,并鉴定潜在的致病变异,如MFN2的致病突变。我们分析了由基于图像的池分析平台Raft-Seq产生的高维表型数据集中的5835个grna。利用mfn2突变细胞表型,我们确定了几个基因,包括TMEM11、TIMM8A、NDUFAF4、NDUFAF7和NDUFS5 (NADH泛醌氧化还原酶相关基因),对人类U2OS细胞正常线粒体动力学至关重要。此外,我们发现SLC25A19和ATAD3A基因中的一些错义和UTR变体是线粒体聚集的驱动因素。通过检查多个特征而不是单个读数,该分析能够检测具有与mfn2突变表型一致的形态“特征”的基因。再分析和异常检测发现了其他关键基因,包括APOOL、MCEE、NIT、PHB和SLC16A7,它们以与MFN2不同的方式扰乱线粒体网络形态。这些研究表明,基因敲除和基因特异性变异与线粒体动力学的组装或维持之间存在因果关系,并有望导致对线粒体相关疾病的更好理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pathogenic morphological signatures of perturbations in mitochondrial-related genes revealed by pooled imaging assay.

Mutations in mitochondrial-related genes underlie numerous neurodegenerative diseases, yet the significance of most variants remains uncertain concerning disease phenotypes. Several thousand genes have been shown to regulate mitochondria in eukaryotic cells, but which of these genes are necessary for proper mitochondrial function and dynamics? We investigated the degree of morphological disruptions in mitochondrial gene-silenced cells to understand the genetic contribution to the expected mitochondrial phenotype and to identify potentially pathogenic variants like pathogenic mutations in MFN2. We analyzed 5835 gRNAs in a high dimensional phenotypic dataset produced by the image-based pooled analysis platform Raft-Seq. Using the MFN2-mutant cell phenotype, we identified several genes, including TMEM11, TIMM8A, NDUFAF4, NDUFAF7, and NDUFS5 (NADH ubiquinone oxidoreductase-related genes), as crucial for normal mitochondrial dynamics in human U2OS cells. Additionally, we found several missense and UTR variants within the genes SLC25A19 and ATAD3A as drivers of mitochondrial aggregation. By examining multiple features instead of a single readout, this analysis was powered to detect genes which had morphological 'signatures' aligned with MFN2-mutant phenotypes. Reanalysis with anomaly detection revealed other critical genes, including APOOL, MCEE, NIT, PHB, and SLC16A7, which perturb mitochondrial network morphology in a manner divergent from MFN2. These studies show causal links between gene knockouts and gene-specific variants into the assembly or maintenance of mitochondrial dynamics and can hopefully lead to a better understanding of mitochondrial related diseases.

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