Quantifying small molecule phenotypic effects using mitochondrial morpho-functional fingerprinting and machine learning.
Quantifying small molecule phenotypic effects using mitochondrial morpho-functional fingerprinting and machine learning.
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DOI：
10.1038/srep08035
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发表时间：
2015-01-26
影响因子：
4.6
通讯作者：
Koopman WJ
中科院分区：
文献类型：
--
作者：
Blanchet L;Smeitink JA;van Emst-de Vries SE;Vogels C;Pellegrini M;Jonckheere AI;Rodenburg RJ;Buydens LM;Beyrath J;Willems PH;Koopman WJ
In primary fibroblasts from Leigh Syndrome (LS) patients, isolated mitochondrial complex I deficiency is associated with increased reactive oxygen species levels and mitochondrial morpho-functional changes. Empirical evidence suggests these aberrations constitute linked therapeutic targets for small chemical molecules. However, the latter generally induce multiple subtle effects, meaning that in vitro potency analysis or single-parameter high-throughput cell screening are of limited use to identify these molecules. We combine automated image quantification and artificial intelligence to discriminate between primary fibroblasts of a healthy individual and a LS patient based upon their mitochondrial morpho-functional phenotype. We then evaluate the effects of newly developed Trolox variants in LS patient cells. This revealed that Trolox ornithylamide hydrochloride best counterbalanced mitochondrial morpho-functional aberrations, effectively scavenged ROS and increased the maximal activity of mitochondrial complexes I, IV and citrate synthase. Our results suggest that Trolox-derived antioxidants are promising candidates in therapy development for human mitochondrial disorders.
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通讯作者：
Cooper, JM
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POOL, WR
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通讯作者：
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