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High-content analysis of neuronal morphology in human iPSC-derived neurons

We present a high-content analysis (HCA) protocol for monitoring the outgrowth capacity of human neurons derived from induced pluripotent stem cells (iPSCs). We describe steps to perform HCA imaging, followed by quantifying the morphology of dendrites and axons within a high-throughput system to eva...

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Detalles Bibliográficos
Autores principales: Lickfett, Selene, Menacho, Carmen, Zink, Annika, Telugu, Narasimha Swamy, Beller, Mathias, Diecke, Sebastian, Cambridge, Sidney, Prigione, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386098/
https://www.ncbi.nlm.nih.gov/pubmed/35990743
http://dx.doi.org/10.1016/j.xpro.2022.101567
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author Lickfett, Selene
Menacho, Carmen
Zink, Annika
Telugu, Narasimha Swamy
Beller, Mathias
Diecke, Sebastian
Cambridge, Sidney
Prigione, Alessandro
author_facet Lickfett, Selene
Menacho, Carmen
Zink, Annika
Telugu, Narasimha Swamy
Beller, Mathias
Diecke, Sebastian
Cambridge, Sidney
Prigione, Alessandro
author_sort Lickfett, Selene
collection PubMed
description We present a high-content analysis (HCA) protocol for monitoring the outgrowth capacity of human neurons derived from induced pluripotent stem cells (iPSCs). We describe steps to perform HCA imaging, followed by quantifying the morphology of dendrites and axons within a high-throughput system to evaluate neurons obtained through various differentiation approaches. This protocol can be used to screen for modulators of neuronal morphogenesis or neurotoxicity. The approach can be applied to patient-derived iPSCs to identify patient-specific defects and possible therapeutic strategies. For complete details on the use and execution of this protocol, please refer to Zink et al. (2020) and Inak et al. (2021). The protocol can be used in combination with Zink et al. (2022).
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spelling pubmed-93860982022-08-19 High-content analysis of neuronal morphology in human iPSC-derived neurons Lickfett, Selene Menacho, Carmen Zink, Annika Telugu, Narasimha Swamy Beller, Mathias Diecke, Sebastian Cambridge, Sidney Prigione, Alessandro STAR Protoc Protocol We present a high-content analysis (HCA) protocol for monitoring the outgrowth capacity of human neurons derived from induced pluripotent stem cells (iPSCs). We describe steps to perform HCA imaging, followed by quantifying the morphology of dendrites and axons within a high-throughput system to evaluate neurons obtained through various differentiation approaches. This protocol can be used to screen for modulators of neuronal morphogenesis or neurotoxicity. The approach can be applied to patient-derived iPSCs to identify patient-specific defects and possible therapeutic strategies. For complete details on the use and execution of this protocol, please refer to Zink et al. (2020) and Inak et al. (2021). The protocol can be used in combination with Zink et al. (2022). Elsevier 2022-08-06 /pmc/articles/PMC9386098/ /pubmed/35990743 http://dx.doi.org/10.1016/j.xpro.2022.101567 Text en © 2022 The Author(s) 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
Lickfett, Selene
Menacho, Carmen
Zink, Annika
Telugu, Narasimha Swamy
Beller, Mathias
Diecke, Sebastian
Cambridge, Sidney
Prigione, Alessandro
High-content analysis of neuronal morphology in human iPSC-derived neurons
title High-content analysis of neuronal morphology in human iPSC-derived neurons
title_full High-content analysis of neuronal morphology in human iPSC-derived neurons
title_fullStr High-content analysis of neuronal morphology in human iPSC-derived neurons
title_full_unstemmed High-content analysis of neuronal morphology in human iPSC-derived neurons
title_short High-content analysis of neuronal morphology in human iPSC-derived neurons
title_sort high-content analysis of neuronal morphology in human ipsc-derived neurons
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386098/
https://www.ncbi.nlm.nih.gov/pubmed/35990743
http://dx.doi.org/10.1016/j.xpro.2022.101567
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