A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts
Summary: Autophagy measurement has been challenging due to the transient nature of autophagy vesicles, in which degradation of cargo occurs. Here, we present a protocol to monitor starvation-induced autophagy using a live high-throughput microscopy system in a fast and automated manner without the n...
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Elsevier
2021
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oai:doaj.org-article:4fd57986613f436d96f10c6836e8d5632021-11-18T04:51:44ZA high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts2666-166710.1016/j.xpro.2021.100966https://doaj.org/article/4fd57986613f436d96f10c6836e8d5632021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666166721006729https://doaj.org/toc/2666-1667Summary: Autophagy measurement has been challenging due to the transient nature of autophagy vesicles, in which degradation of cargo occurs. Here, we present a protocol to monitor starvation-induced autophagy using a live high-throughput microscopy system in a fast and automated manner without the need for sample preparation. We provide a detailed protocol describing the generation of turboGFP-LC3B expressing mouse embryonic fibroblasts (MEFs), the measurement of autophagy over time and the analysis of data.For complete details on the use and execution of this protocol, please refer to Nowosad et al. (2020, 2021).Ada NowosadArnaud BessonElsevierarticleCell BiologyCell-based AssaysHigh Throughput ScreeningMicroscopyScience (General)Q1-390ENSTAR Protocols, Vol 2, Iss 4, Pp 100966- (2021) |
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DOAJ |
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Cell Biology Cell-based Assays High Throughput Screening Microscopy Science (General) Q1-390 |
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Cell Biology Cell-based Assays High Throughput Screening Microscopy Science (General) Q1-390 Ada Nowosad Arnaud Besson A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
description |
Summary: Autophagy measurement has been challenging due to the transient nature of autophagy vesicles, in which degradation of cargo occurs. Here, we present a protocol to monitor starvation-induced autophagy using a live high-throughput microscopy system in a fast and automated manner without the need for sample preparation. We provide a detailed protocol describing the generation of turboGFP-LC3B expressing mouse embryonic fibroblasts (MEFs), the measurement of autophagy over time and the analysis of data.For complete details on the use and execution of this protocol, please refer to Nowosad et al. (2020, 2021). |
format |
article |
author |
Ada Nowosad Arnaud Besson |
author_facet |
Ada Nowosad Arnaud Besson |
author_sort |
Ada Nowosad |
title |
A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
title_short |
A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
title_full |
A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
title_fullStr |
A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
title_full_unstemmed |
A high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
title_sort |
high-throughput protocol for monitoring starvation-induced autophagy in real time in mouse embryonic fibroblasts |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://doaj.org/article/4fd57986613f436d96f10c6836e8d563 |
work_keys_str_mv |
AT adanowosad ahighthroughputprotocolformonitoringstarvationinducedautophagyinrealtimeinmouseembryonicfibroblasts AT arnaudbesson ahighthroughputprotocolformonitoringstarvationinducedautophagyinrealtimeinmouseembryonicfibroblasts AT adanowosad highthroughputprotocolformonitoringstarvationinducedautophagyinrealtimeinmouseembryonicfibroblasts AT arnaudbesson highthroughputprotocolformonitoringstarvationinducedautophagyinrealtimeinmouseembryonicfibroblasts |
_version_ |
1718424971603083264 |