Machine learning-based classification of mitochondrial morphology in primary neurons and brain.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
04 03 2021
04 03 2021
Historique:
received:
25
11
2020
accepted:
17
02
2021
entrez:
5
3
2021
pubmed:
6
3
2021
medline:
15
12
2021
Statut:
epublish
Résumé
The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeostatic mitochondrial profile can change morphologic distribution in response to various stressors. Therefore, it is imperative to develop a method that robustly measures mitochondrial morphology with high accuracy. Here, we developed a semi-automated image analysis pipeline for the quantitation of mitochondrial morphology for both in vitro and in vivo applications. The image analysis pipeline was generated and validated utilizing images of primary cortical neurons from transgenic mice, allowing genetic ablation of key components of mitochondrial dynamics. This analysis pipeline was further extended to evaluate mitochondrial morphology in vivo through immunolabeling of brain sections as well as serial block-face scanning electron microscopy. These data demonstrate a highly specific and sensitive method that accurately classifies distinct physiological and pathological mitochondrial morphologies. Furthermore, this workflow employs the use of readily available, free open-source software designed for high throughput image processing, segmentation, and analysis that is customizable to various biological models.
Identifiants
pubmed: 33664336
doi: 10.1038/s41598-021-84528-8
pii: 10.1038/s41598-021-84528-8
pmc: PMC7933342
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
5133Subventions
Organisme : NHLBI NIH HHS
ID : T32 HL007853
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS091242
Pays : United States
Organisme : NINDS NIH HHS
ID : F31 NS124280
Pays : United States
Organisme : NIH HHS
ID : T32HL007853
Pays : United States
Organisme : NIH HHS
ID : R42NS105238
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS120322
Pays : United States
Organisme : NINDS NIH HHS
ID : R42 NS105238
Pays : United States
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