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Functional imaging of brain organoids using high-density microelectrode arrays
ABSTRACT: Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474390/ https://www.ncbi.nlm.nih.gov/pubmed/36120104 http://dx.doi.org/10.1557/s43577-022-00282-w |
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author | Schröter, Manuel Wang, Congwei Terrigno, Marco Hornauer, Philipp Huang, Ziqiang Jagasia, Ravi Hierlemann, Andreas |
author_facet | Schröter, Manuel Wang, Congwei Terrigno, Marco Hornauer, Philipp Huang, Ziqiang Jagasia, Ravi Hierlemann, Andreas |
author_sort | Schröter, Manuel |
collection | PubMed |
description | ABSTRACT: Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization. IMPACT STATEMENT: Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1557/s43577-022-00282-w. |
format | Online Article Text |
id | pubmed-9474390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-94743902022-09-16 Functional imaging of brain organoids using high-density microelectrode arrays Schröter, Manuel Wang, Congwei Terrigno, Marco Hornauer, Philipp Huang, Ziqiang Jagasia, Ravi Hierlemann, Andreas MRS Bull Impact Article ABSTRACT: Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization. IMPACT STATEMENT: Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1557/s43577-022-00282-w. Springer International Publishing 2022-06-30 2022 /pmc/articles/PMC9474390/ /pubmed/36120104 http://dx.doi.org/10.1557/s43577-022-00282-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Impact Article Schröter, Manuel Wang, Congwei Terrigno, Marco Hornauer, Philipp Huang, Ziqiang Jagasia, Ravi Hierlemann, Andreas Functional imaging of brain organoids using high-density microelectrode arrays |
title | Functional imaging of brain organoids using high-density microelectrode arrays |
title_full | Functional imaging of brain organoids using high-density microelectrode arrays |
title_fullStr | Functional imaging of brain organoids using high-density microelectrode arrays |
title_full_unstemmed | Functional imaging of brain organoids using high-density microelectrode arrays |
title_short | Functional imaging of brain organoids using high-density microelectrode arrays |
title_sort | functional imaging of brain organoids using high-density microelectrode arrays |
topic | Impact Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474390/ https://www.ncbi.nlm.nih.gov/pubmed/36120104 http://dx.doi.org/10.1557/s43577-022-00282-w |
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