Machine learning algorithms reveal the secrets of mitochondrial dynamics

Mitochondria 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...

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Bibliographic Details
Published in:EMBO molecular medicine 2021-06, Vol.13 (6), p.e14316-n/a
Main Authors: Collier, Jack J, Taylor, Robert W
Format: Article
Language:English
Subjects:
Algorithms
Apoptosis
Atrophy
Automation
Clinical outcomes
Confocal microscopy
Cristae
EMBO16
EMBO27
EMBO57
Genotype & phenotype
GTP Phosphohydrolases - genetics
Humans
Learning algorithms
Machine Learning
Metabolism
Metabolites
Microscopy
Mitochondria
Mitochondria - genetics
Mitochondrial DNA
Mitochondrial Dynamics
Morphology
Mutation
News & Views
Optic atrophy
Patients
Phenotypes
Physiology
Proteins
Proteomes
siRNA
Views
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Summary:Mitochondria 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. Graphical Abstract J. Collier and R. Taylor discuss a high‐throughput screening approach to identify suppressors of mitochondrial fragmentation in OPA1 patient fibroblasts as reported by Cretin et al, in this issue of EMBO Mol Med .
ISSN:1757-4676
1757-4684
1757-4684
DOI:10.15252/emmm.202114316