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Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research

Induced pluripotent stem cells and embryonic stem cells have revolutionized cellular neuroscience, providing the opportunity to model neurological diseases and test potential therapeutics in a pre-clinical setting. The power of these models has been widely discussed, but the potential pitfalls of st...

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Autores principales: Engel, Martin, Do-Ha, Dzung, Muñoz, Sonia Sanz, Ooi, Lezanne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5002043/
https://www.ncbi.nlm.nih.gov/pubmed/27154043
http://dx.doi.org/10.1007/s00018-016-2265-3
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author Engel, Martin
Do-Ha, Dzung
Muñoz, Sonia Sanz
Ooi, Lezanne
author_facet Engel, Martin
Do-Ha, Dzung
Muñoz, Sonia Sanz
Ooi, Lezanne
author_sort Engel, Martin
collection PubMed
description Induced pluripotent stem cells and embryonic stem cells have revolutionized cellular neuroscience, providing the opportunity to model neurological diseases and test potential therapeutics in a pre-clinical setting. The power of these models has been widely discussed, but the potential pitfalls of stem cell differentiation in this research are less well described. We have analyzed the literature that describes differentiation of human pluripotent stem cells into three neural cell types that are commonly used to study diseases, including forebrain cholinergic neurons for Alzheimer’s disease, midbrain dopaminergic neurons for Parkinson’s disease and cortical astrocytes for neurodegenerative and psychiatric disorders. Published protocols for differentiation vary widely in the reported efficiency of target cell generation. Additionally, characterization of the cells by expression profile and functionality differs between studies and is often insufficient, leading to highly variable protocol outcomes. We have synthesized this information into a simple methodology that can be followed when performing or assessing differentiation techniques. Finally we propose three considerations for future research, including the use of physiological O(2) conditions, three-dimensional co-culture systems and microfluidics to control feeding cycles and growth factor gradients. Following these guidelines will help researchers to ensure that robust and meaningful data is generated, enabling the full potential of stem cell differentiation for disease modeling and regenerative medicine.
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spelling pubmed-50020432016-09-13 Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research Engel, Martin Do-Ha, Dzung Muñoz, Sonia Sanz Ooi, Lezanne Cell Mol Life Sci Review Induced pluripotent stem cells and embryonic stem cells have revolutionized cellular neuroscience, providing the opportunity to model neurological diseases and test potential therapeutics in a pre-clinical setting. The power of these models has been widely discussed, but the potential pitfalls of stem cell differentiation in this research are less well described. We have analyzed the literature that describes differentiation of human pluripotent stem cells into three neural cell types that are commonly used to study diseases, including forebrain cholinergic neurons for Alzheimer’s disease, midbrain dopaminergic neurons for Parkinson’s disease and cortical astrocytes for neurodegenerative and psychiatric disorders. Published protocols for differentiation vary widely in the reported efficiency of target cell generation. Additionally, characterization of the cells by expression profile and functionality differs between studies and is often insufficient, leading to highly variable protocol outcomes. We have synthesized this information into a simple methodology that can be followed when performing or assessing differentiation techniques. Finally we propose three considerations for future research, including the use of physiological O(2) conditions, three-dimensional co-culture systems and microfluidics to control feeding cycles and growth factor gradients. Following these guidelines will help researchers to ensure that robust and meaningful data is generated, enabling the full potential of stem cell differentiation for disease modeling and regenerative medicine. Springer International Publishing 2016-05-06 2016 /pmc/articles/PMC5002043/ /pubmed/27154043 http://dx.doi.org/10.1007/s00018-016-2265-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Review
Engel, Martin
Do-Ha, Dzung
Muñoz, Sonia Sanz
Ooi, Lezanne
Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title_full Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title_fullStr Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title_full_unstemmed Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title_short Common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
title_sort common pitfalls of stem cell differentiation: a guide to improving protocols for neurodegenerative disease models and research
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5002043/
https://www.ncbi.nlm.nih.gov/pubmed/27154043
http://dx.doi.org/10.1007/s00018-016-2265-3
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