Researchers develop low-cost scalable sensors to study genetic brain disorders

Researchers have demonstrated a new class of low-cost, scalable sensors that can be used to monitor electrical activity in human cerebral organoids. Because electrical signals are key to understanding brain function, this advance facilitates research into both neurodevelopment and genetic disorders such as Angelman syndrome.

Human cerebral organoids are millimeter-sized tissues comprised of cell types typically found in the different regions of the brain. They are made by culturing stem cells. These organoids are important to many fields of research because they allow researchers to study the behavior of nervous system cells and tissues in ways that are not possible with animal models.

For example, Angelman syndrome is a genetic disorder associated with delayed development, intellectual disability, speech impairment and problems with movement. Because researchers cannot conduct research on a human's developing brain, human cerebral organoids are a valuable platform for understanding the genetic activity that causes the disorder and developing therapeutic treatments.

"Animal models don't really capture the complexity of the human brain, which is one reason why human cerebral organoids are attractive for brain research," says Amay Bandodkar, co-corresponding author of a paper on the work and an assistant professor of electrical and computer engineering at North Carolina State University.

"One challenge with human cerebral organoid research is that there can be significant variation across organoid samples," says Navya Mishra, first author of the paper and a Ph.D. student at NC State. "As a result, it's important to have a lot of samples in order to produce biologically meaningful results.

"However, the sensors currently used in organoid research are expensive, due to both the materials they are made from and the manufacturing process itself," says Mishra. "This creates financial constraints that result in researchers often using fewer than 10 organoids for a given study."

Our goal with this work was to develop a sensor that performs well, can be scaled up in an affordable way, and that is easy to use."

Albert Keung, co-corresponding author of the paper on the work and associate professor of chemical and biomolecular engineering, North Carolina State University

To address these challenges, the researchers developed a device they call CAMEO - Conformal Array for Monitoring Electrophysiology of Organoids. The device consists of 12 carbon nanotube strands suspended in the shape of a basket. The carbon nanotubes are processed in a way that preserves the material's flexibility and sensitivity to electrical signals. In practice, the organoid is suspended in the CAMEO, like an egg in a basket. The end of each strand is exposed, creating an electrode that can detect electrical signals from the organoid. The signals are then transmitted through the carbon nanotube strand to a device that can record electrical activity.

In proof-of-concept testing, the researchers demonstrated that CAMEO was capable of monitoring electrical activity in organoids, that it could detect the low-amplitude signals that are critical to biological research, and that it was able to detect signal changes that are triggered by chemicals that stimulate electrical activity in neurological systems.

"This work was very interdisciplinary and really benefited from Navya's adventurousness to integrate principles from electrical engineering and neurodevelopmental biology," says Keung.

"We have shown that CAMEO's performance is comparable to previous technologies used to monitor electrical activity in organoids," says Mishra. "The big difference is that our microelectrode array uses relatively inexpensive materials and is much less difficult to manufacture, making it substantially less costly. This should make it much easier to scale up, allowing researchers to conduct more large-scale studies.

"Hopefully, many labs will adopt CAMEO, because having a standardized data-collection format will make it much easier for the research community to share data effectively - because they'll be using the same plug-and-play system," says Mishra.