Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays Article Swipe
Anne Gresch
,
Jan David Hüwel
,
Jennifer S. Briggs
,
Tim Berger
,
Ruben Koch
,
Thomas Deickert
,
Christian Beecks
,
Richard K.P. Benninger
,
Martina Düfer
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.10.24.563843
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.10.24.563843
Glucose-stimulated beta-cells synchronize calcium waves across the islet to recruit more beta-cells for insulin secretion. Compared to calcium dynamics, the formation and cell-to-cell propagation of electrical signals within the islet are poorly characterized. To determine factors that influence the propagation of electrical activity across the islet underlying calcium oscillations and beta-cell synchronization, we used high-resolution CMOS multielectrode arrays (MEA) to measure voltage changes associated with the membrane potential of individual cells within intact mouse islets. We measured both fast (milliseconds, spikes) and slow (seconds, waves) voltage changes and analyzed the spatiotemporal voltage dynamics. Treatment of islets from C57BL6 mice with increasing glucose concentrations revealed that single spike activity and wave signal velocity were both glucose-dependent. A repeated glucose stimulus involved a highly active subset of cells in terms of spike activity. When islets were pretreated for 72 hours with glucolipotoxic medium, the wave velocity was significantly reduced. Network analysis confirmed that the synchrony of islet cells was affected due to slower propagating electrical waves and not due to altered spike activity. In summary, this approach provided novel insight regarding the propagation of electrical activity and opens a wide field for further studies on signal transduction in the islet cell network. Article Highlights This study presents a new method for characterizing islet spatiotemporal electrical dynamics and subpopulations of beta-cells. We asked whether a high-resolution CMOS-MEA is suited to detect electrical signals on a level close to single cells, and whether we can track the propagation of electrical activity through the islet on a cellular scale. A highly active subpopulation of islet cells was identified by action potential-like spike activity, whereas slower waves were a measure for synchronized electrical activity. Further, propagating waves were slowed by glucolipotoxicity. The technique is a useful tool for exploring the pancreatic islet network in health and disease.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.10.24.563843
- https://www.biorxiv.org/content/biorxiv/early/2023/10/29/2023.10.24.563843.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388006219
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388006219Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.10.24.563843Digital Object Identifier
- Title
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Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arraysWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-10-29Full publication date if available
- Authors
-
Anne Gresch, Jan David Hüwel, Jennifer S. Briggs, Tim Berger, Ruben Koch, Thomas Deickert, Christian Beecks, Richard K.P. Benninger, Martina DüferList of authors in order
- Landing page
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https://doi.org/10.1101/2023.10.24.563843Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2023/10/29/2023.10.24.563843.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2023/10/29/2023.10.24.563843.full.pdfDirect OA link when available
- Concepts
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Islet, Microelectrode, Multielectrode array, Calcium signaling, Neuroscience, Chemistry, Biology, Biophysics, Signal transduction, Insulin, Cell biology, Endocrinology, Electrode, Physical chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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