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3D clusters of brain cells are emerging as essential tools for understanding neural networks and studying neurological diseases in the lab. EPFL’s e-Flower, a flower-shaped 3D microelectrode array (MEA), allows researchers to monitor the electrical activity of these spheroids in a way that was previously impossible.
This breakthrough, published in Science Advances, lays the groundwork for more sophisticated research on brain organoids, which are complex, miniaturized models of brain tissues.
“The e-Flower lets us record neural activity from much more of the surface of neural spheroids in real-time—something that wasn’t possible with earlier tools. Our flexible technology makes it possible to get accurate recordings without damaging the 3D neural models, giving us a better understanding of how their complex circuits work,” says Stéphanie Lacour, lead author of the paper and head of the Laboratory for Soft Bioelectronic Interfaces (LSBI) at the Neuro X Institute.
Why neural spheroids?
“We focused on neural spheroids for this study because they provide a straightforward and accessible model,” says Eleonora Martinelli, one of the lead researchers on the project.
Neural spheroids are three-dimensional clusters of neurons that replicate some of the key functions of brain tissue. They are simpler than organoids, which contain multiple cell types and more closely mimic the brain. The LSBI team at Campus Biotech worked in collaboration with Luc Stoppini and Adrien Roux at the Tissue Engineering Laboratory (HEPIA-HESGE), researchers with long-standing experience with neural spheroids electrophysiology.
“Spheroids are relatively easy to produce and manipulate in the lab, which makes them ideal for early-stage testing,” Martinelli continues. “However, our goal is to eventually apply the e-Flower to brain organoids, which more accurately model brain development and disorders.”
“Organoids represent an exciting interface both for neuroscience research and next-generation neurotechnology,” says Stéphanie Lacour. “They bridge the gap between simplified in vitro models and the complexities of the human brain. Our work with the e-Flower is a critical step toward being able to explore these 3D models.”
The serendipity behind the innovation
Interestingly, the e-Flower was born out of an unexpected discovery. Outman Akouissi, a collaborator on the project, encountered a challenge while working on soft implants for peripheral nerves: the hydrogels he used caused his devices to curl unpredictably when exposed to water.
What started as a frustration turned into a breakthrough when Akouissi and Martinelli realized this curling mechanism could be harnessed for a completely different application—wrapping around neural spheroids.
“This was a perfect example of how serendipity can lead to innovation,” says Martinelli. “What was originally a problem for one project became the solution for another.”
A new approach to neural electrophysiology
The device consists of four flexible petals equipped with platinum electrodes, which curl around the spheroid when exposed to the liquid that supports the cell structure. This actuation is driven by the swelling of a soft hydrogel, making the device both gentle on the tissue and easy to use.
Designed to be compatible with existing electrophysiological systems, the e-Flower offers a plug-and-play solution for researchers, avoiding the need for complex external actuators or harmful solvents.
Once the technology is applied to organoids, the ability to record electrical activity from all sides will provide a much more comprehensive understanding of brain processes. Researchers hope this will lead to new insights into neurodevelopment, brain injury recovery, and neurological diseases.
More information:
Eleonora Martinelli et al, The e-Flower: a hydrogel-actuated 3D MEA for brain spheroid electrophysiology, Science Advances (2024). DOI: 10.1126/sciadv.adp8054. www.science.org/doi/10.1126/sciadv.adp8054
Citation:
Researchers develop a device called e-Flower that records neuronal activity with electronic petals (2024, October 16)
retrieved 16 October 2024
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