Monitoring autophagy using super-resolution structured illumination and direct stochastic optical reconstruction microscopy.

Autophagosome Autophagy Direct stochastic optical reconstruction Fluorescence microscopy Lysosome Structured illumination

Journal

Methods in cell biology
ISSN: 0091-679X
Titre abrégé: Methods Cell Biol
Pays: United States
ID NLM: 0373334

Informations de publication

Date de publication:
2021
Historique:
entrez: 27 7 2021
pubmed: 28 7 2021
medline: 26 11 2021
Statut: ppublish

Résumé

Autophagy is a major protein degradation pathway responsible for the removal of primarily long-lived and misfolded proteins, contributing to cellular homeostasis. Autophagy dysfunction has been associated with the onset of various human pathologies. Visualizing key proteins that govern autophagy pathway activity, the molecular machinery and cargo is essential to elucidate roles and mechanisms of autophagy function. Although multiple fluorescence-based microscopy approaches exist to assess autophagy, the limit of resolution associated with light microscopy makes precise intracellular protein localization, interaction and molecular distribution challenging. Here we describe a detailed protocol for both super-resolution structured illumination microscopy (SR-SIM) as well as direct stochastic optical reconstruction microscopy (dSTORM) for the visualization of key proteins associated with the autophagy molecular machinery and cargo. The presented method enables to achieve increased resolving power to assess localization and molecular density profiles, typically not achievable with standard confocal or wide field fluorescence microcopy.

Identifiants

pubmed: 34311863
pii: S0091-679X(20)30211-9
doi: 10.1016/bs.mcb.2020.12.005
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

139-152

Informations de copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Auteurs

Dumisile Lumkwana (D)

Microscopy and Imaging Translational Technology Platform, Cancer Research UK, University College London, London, United Kingdom.

Lize Engelbrecht (L)

Central Analytical Facility, Fluorescence Microscopy Unit, Stellenbosch University, South Africa.

Ben Loos (B)

Department of Physiological Sciences, Stellenbosch University, South Africa. Electronic address: bloos@sun.ac.za.

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Classifications MeSH