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Assessing persister awakening dynamics following antibiotic treatment in E. coli

Given the low fraction of antibiotic-tolerant persisters and the transient nature of the persister phenotype, identifying molecular mechanisms underlying persister state exit, also called "awakening," is challenging. Here, we describe how persister awakening kinetics can be quantified at t...

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Detalles Bibliográficos
Autores principales: Wilmaerts, Dorien, Govers, Sander K., Michiels, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234080/
https://www.ncbi.nlm.nih.gov/pubmed/35769931
http://dx.doi.org/10.1016/j.xpro.2022.101476
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author Wilmaerts, Dorien
Govers, Sander K.
Michiels, Jan
author_facet Wilmaerts, Dorien
Govers, Sander K.
Michiels, Jan
author_sort Wilmaerts, Dorien
collection PubMed
description Given the low fraction of antibiotic-tolerant persisters and the transient nature of the persister phenotype, identifying molecular mechanisms underlying persister state exit, also called "awakening," is challenging. Here, we describe how persister awakening kinetics can be quantified at the single-cell level, enabling the identification of genes that are important for persister survival following antibiotic treatment. We report step-by-step sample preparation, dynamic recording, and data analysis. Although the setup is flexible, time-lapse microscopy requires a minimal number of persisters being present. For complete details on the use and execution of this protocol, please refer to Wilmaerts et al. (2022).
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spelling pubmed-92340802022-06-28 Assessing persister awakening dynamics following antibiotic treatment in E. coli Wilmaerts, Dorien Govers, Sander K. Michiels, Jan STAR Protoc Protocol Given the low fraction of antibiotic-tolerant persisters and the transient nature of the persister phenotype, identifying molecular mechanisms underlying persister state exit, also called "awakening," is challenging. Here, we describe how persister awakening kinetics can be quantified at the single-cell level, enabling the identification of genes that are important for persister survival following antibiotic treatment. We report step-by-step sample preparation, dynamic recording, and data analysis. Although the setup is flexible, time-lapse microscopy requires a minimal number of persisters being present. For complete details on the use and execution of this protocol, please refer to Wilmaerts et al. (2022). Elsevier 2022-06-17 /pmc/articles/PMC9234080/ /pubmed/35769931 http://dx.doi.org/10.1016/j.xpro.2022.101476 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Wilmaerts, Dorien
Govers, Sander K.
Michiels, Jan
Assessing persister awakening dynamics following antibiotic treatment in E. coli
title Assessing persister awakening dynamics following antibiotic treatment in E. coli
title_full Assessing persister awakening dynamics following antibiotic treatment in E. coli
title_fullStr Assessing persister awakening dynamics following antibiotic treatment in E. coli
title_full_unstemmed Assessing persister awakening dynamics following antibiotic treatment in E. coli
title_short Assessing persister awakening dynamics following antibiotic treatment in E. coli
title_sort assessing persister awakening dynamics following antibiotic treatment in e. coli
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234080/
https://www.ncbi.nlm.nih.gov/pubmed/35769931
http://dx.doi.org/10.1016/j.xpro.2022.101476
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