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Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis

In vitro derivation of human neurons in the autonomic nervous system (ANS) is an important technology, given its regulatory roles in maintaining homeostasis in the human body. Although several induction protocols for autonomic lineages have been reported, the regulatory machinery remains largely und...

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Detalles Bibliográficos
Autores principales: Takayama, Yuzo, Akagi, Yuka, Kida, Yasuyuki S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10219521/
https://www.ncbi.nlm.nih.gov/pubmed/37240399
http://dx.doi.org/10.3390/ijms24109053
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author Takayama, Yuzo
Akagi, Yuka
Kida, Yasuyuki S.
author_facet Takayama, Yuzo
Akagi, Yuka
Kida, Yasuyuki S.
author_sort Takayama, Yuzo
collection PubMed
description In vitro derivation of human neurons in the autonomic nervous system (ANS) is an important technology, given its regulatory roles in maintaining homeostasis in the human body. Although several induction protocols for autonomic lineages have been reported, the regulatory machinery remains largely undefined, primarily due to the absence of a comprehensive understanding of the molecular mechanism regulating human autonomic induction in vitro. In this study, our objective was to pinpoint key regulatory components using integrated bioinformatics analysis. A protein–protein interaction network construction for the proteins encoded by the differentially expressed genes from our RNA sequencing data, and conducting subsequent module analysis, we identified distinct gene clusters and hub genes involved in the induction of autonomic lineages. Moreover, we analyzed the impact of transcription factor (TF) activity on target gene expression, revealing enhanced autonomic TF activity that could lead to the induction of autonomic lineages. The accuracy of this bioinformatics analysis was corroborated by employing calcium imaging to observe specific responses to certain ANS agonists. This investigation offers novel insights into the regulatory machinery in the generation of neurons in the ANS, which would be valuable for further understanding and precise regulation of autonomic induction and differentiation.
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spelling pubmed-102195212023-05-27 Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis Takayama, Yuzo Akagi, Yuka Kida, Yasuyuki S. Int J Mol Sci Article In vitro derivation of human neurons in the autonomic nervous system (ANS) is an important technology, given its regulatory roles in maintaining homeostasis in the human body. Although several induction protocols for autonomic lineages have been reported, the regulatory machinery remains largely undefined, primarily due to the absence of a comprehensive understanding of the molecular mechanism regulating human autonomic induction in vitro. In this study, our objective was to pinpoint key regulatory components using integrated bioinformatics analysis. A protein–protein interaction network construction for the proteins encoded by the differentially expressed genes from our RNA sequencing data, and conducting subsequent module analysis, we identified distinct gene clusters and hub genes involved in the induction of autonomic lineages. Moreover, we analyzed the impact of transcription factor (TF) activity on target gene expression, revealing enhanced autonomic TF activity that could lead to the induction of autonomic lineages. The accuracy of this bioinformatics analysis was corroborated by employing calcium imaging to observe specific responses to certain ANS agonists. This investigation offers novel insights into the regulatory machinery in the generation of neurons in the ANS, which would be valuable for further understanding and precise regulation of autonomic induction and differentiation. MDPI 2023-05-21 /pmc/articles/PMC10219521/ /pubmed/37240399 http://dx.doi.org/10.3390/ijms24109053 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Takayama, Yuzo
Akagi, Yuka
Kida, Yasuyuki S.
Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title_full Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title_fullStr Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title_full_unstemmed Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title_short Deciphering the Molecular Mechanisms of Autonomic Nervous System Neuron Induction through Integrative Bioinformatics Analysis
title_sort deciphering the molecular mechanisms of autonomic nervous system neuron induction through integrative bioinformatics analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10219521/
https://www.ncbi.nlm.nih.gov/pubmed/37240399
http://dx.doi.org/10.3390/ijms24109053
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