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Lookup NU author(s): Jack Collier, Professor Robert Taylor
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2021 The Authors. Published under the terms of the CC BY 4.0 licenseMitochondria exist as dynamic networks whose morphology is driven by the complex interplay between fission and fusion events. Failure to modulate these processes can be detrimental to human health as evidenced by dominantly inherited, pathogenic variants in OPA1, an effector enzyme of mitochondrial fusion, that lead to network fragmentation, cristae dysmorphology and impaired oxidative respiration, manifesting typically as isolated optic atrophy. However, a significant number of patients develop more severe, systemic phenotypes, although no genetic modifiers of OPA1-related disease have been identified to date. In this issue of EMBO Molecular Medicine, supervised machine learning algorithms underlie a novel tool that enables automated, high throughput and unbiased screening of changes in mitochondrial morphology measured using confocal microscopy. By coupling this approach with a bespoke siRNA library targeting the entire mitochondrial proteome, the work described by Cretin and colleagues yielded significant insight into mitochondrial biology, discovering 91 candidate genes whose endogenous depletion can remedy impaired mitochondrial dynamics caused by OPA1 deficiency.
Author(s): Collier JJ, Taylor RW
Publication type: Article
Publication status: Published
Journal: EMBO Molecular Medicine
Year: 2021
Volume: 13
Print publication date: 07/06/2021
Online publication date: 27/05/2021
Acceptance date: 13/04/2021
Date deposited: 09/01/2024
ISSN (print): 1757-4676
ISSN (electronic): 1757-4684
Publisher: Blackwell Publishing Ltd
URL: https://doi.org/10.15252/emmm.202114316
DOI: 10.15252/emmm.202114316
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