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Single neurons on microelectrode array chip: manipulation and analyses
- Source :
- Frontiers in Bioengineering and Biotechnology, Vol 11 (2023)
- Publication Year :
- 2023
- Publisher :
- Frontiers Media S.A., 2023.
-
Abstract
- Chips-based platforms intended for single-cell manipulation are considered powerful tools to analyze intercellular interactions and cellular functions. Although the conventional cell co-culture models could investigate cell communication to some extent, the role of a single cell requires further analysis. In this study, a precise intercellular interaction model was built using a microelectrode array [microelectrode array (MEA)]-based and dielectrophoresis-driven single-cell manipulation chip. The integrated platform enabled precise manipulation of single cells, which were either trapped on or transferred between electrodes. Each electrode was controlled independently to record the corresponding cellular electrophysiology. Multiple parameters were explored to investigate their effects on cell manipulation including the diameter and depth of microwells, the geometry of cells, and the voltage amplitude of the control signal. Under the optimized microenvironment, the chip was further evaluated using 293T and neural cells to investigate the influence of electric field on cells. An examination of the inappropriate use of electric fields on cells revealed the occurrence of oncosis. In the end of the study, electrophysiology of single neurons and network of neurons, both differentiated from human induced pluripotent stem cells (iPSC), was recorded and compared to demonstrate the functionality of the chip. The obtained preliminary results extended the nature growing model to the controllable level, satisfying the expectation of introducing more elaborated intercellular interaction models.
Details
- Language :
- English
- ISSN :
- 22964185
- Volume :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Bioengineering and Biotechnology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.203bb012b9cc4f32b9a3d9fa87b88acd
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fbioe.2023.1258626