Bioelectronic device achieves unprecedented control of cell membrane voltage

September 24, 2020

In an impressive proof-of-concept demonstration, an interdisciplinary team of scientists has developed a bioelectronic system driven by a machine learning algorithm that can shift the membrane voltage in living cells and maintain it at a set point for 10 hours.

Every living cell maintains a voltage across the cell membrane that results from differences in the concentrations of charged ions inside and outside the cell. Often called the membrane potential or resting potential, this voltage is regulated by ion channels in the cell membrane and plays important roles in cell physiology and functions such as proliferation and differentiation.

Controlling cells with bioelectronics is difficult due to the complex ways cells respond to changes in their environment and the natural self-regulating feedback process known as homeostasis. Cells regulate ion movements to maintain a steady membrane voltage, so the researchers had to develop a system that could counteract this natural response.

"Biological feedback systems are fundamental to life, and their malfunctioning is often involved in diseases. This work demonstrates that we can tweak this feedback using a combination of bioelectronic devices actuated by machine learning, and potentially restore its functioning," said Marco Rolandi, professor and chair of electrical and computer engineering at the UC Santa Cruz Baskin School of Engineering.

Rolandi is the senior corresponding author of the paper describing this work, published September 24 in the journal Advanced Intelligent Systems. The other corresponding authors who helped direct the project are Marcella Gomez, assistant professor of applied mathematics at UC Santa Cruz, and Michael Levin, director of the Center for Regenerative and Developmental Biology at Tufts University and associate faculty member of the Wyss Institute at Harvard University.

The researchers developed a system involving an array of bioelectronic proton pumps that add or remove hydrogen ions from solution in proximity to cultured human stem cells. The cells were genetically modified to express a fluorescent protein on the cell membrane that responds to changes in membrane voltage. The system is controlled by a machine learning algorithm that tracks how the membrane voltage responds to stimuli from the proton pumps.

"It is a closed-loop system, in that it records the behavior of the cells, determines what intervention to deliver using the proton pumps, sees how the cells react, then determines the next intervention needed to achieve and maintain the membrane voltage status we desire," Rolandi explained.

Gomez, who developed the machine learning algorithm, said the algorithm is not trained on any data in advance and does not rely on a model of the system. Instead, the "learning" happens in real time as the neural network responds to input regarding the current state of the membrane voltage.

"The adaptive nature of biology--that is, the ability of cells to change their response to external stimuli--calls for an adaptive approach in controls, where static models and past information can become obsolete," Gomez said.

Because the membrane voltage of stem cells is different from that of mature, differentiated cells, the researchers are interested in the possibility of using the system to induce and direct the differentiation of stem cells into specific cell types. They did not, however, explicitly look at cell differentiation in this proof-of-concept study.

More broadly, the combination of bioelectronics and machine learning in a closed-loop biohybrid system has many potential applications in regenerative medicine and synthetic biology, Rolandi said. He noted that the results of this study will inform the team's work on a major effort to develop a "smart bandage" providing bioelectronic intelligent control of wound regeneration.

"This study is an important proof of concept for the use of bioelectronics and machine learning to control cell functions," he said.
-end-
First author John Selberg, a graduate student in Rolandi's lab, designed the proton pumps and helped develop fabrication processes, characterize the devices, and perform experiments. Coauthor Mohammad Jafari, a postdoctoral researcher working with Gomez, designed the machine learning algorithm. Other coauthors include researchers in the Departments of Applied Mathematics and Electrical and Computer Engineering at UC Santa Cruz and at the Allen Discovery Center and Department of Biology at Tufts University.

This research was funded by the Defense Advanced Research Projects Agency (DARPA).

University of California - Santa Cruz

Related Stem Cells Articles from Brightsurf:

SUTD researchers create heart cells from stem cells using 3D printing
SUTD researchers 3D printed a micro-scaled physical device to demonstrate a new level of control in the directed differentiation of stem cells, enhancing the production of cardiomyocytes.

More selective elimination of leukemia stem cells and blood stem cells
Hematopoietic stem cells from a healthy donor can help patients suffering from acute leukemia.

Computer simulations visualize how DNA is recognized to convert cells into stem cells
Researchers of the Hubrecht Institute (KNAW - The Netherlands) and the Max Planck Institute in Münster (Germany) have revealed how an essential protein helps to activate genomic DNA during the conversion of regular adult human cells into stem cells.

First events in stem cells becoming specialized cells needed for organ development
Cell biologists at the University of Toronto shed light on the very first step stem cells go through to turn into the specialized cells that make up organs.

Surprising research result: All immature cells can develop into stem cells
New sensational study conducted at the University of Copenhagen disproves traditional knowledge of stem cell development.

The development of brain stem cells into new nerve cells and why this can lead to cancer
Stem cells are true Jacks-of-all-trades of our bodies, as they can turn into the many different cell types of all organs.

Healthy blood stem cells have as many DNA mutations as leukemic cells
Researchers from the Princess Máxima Center for Pediatric Oncology have shown that the number of mutations in healthy and leukemic blood stem cells does not differ.

New method grows brain cells from stem cells quickly and efficiently
Researchers at Lund University in Sweden have developed a faster method to generate functional brain cells, called astrocytes, from embryonic stem cells.

NUS researchers confine mature cells to turn them into stem cells
Recent research led by Professor G.V. Shivashankar of the Mechanobiology Institute at the National University of Singapore and the FIRC Institute of Molecular Oncology in Italy, has revealed that mature cells can be reprogrammed into re-deployable stem cells without direct genetic modification -- by confining them to a defined geometric space for an extended period of time.

Researchers develop a new method for turning skin cells into pluripotent stem cells
Researchers at the University of Helsinki, Finland, and Karolinska Institutet, Sweden, have for the first time succeeded in converting human skin cells into pluripotent stem cells by activating the cell's own genes.

Read More: Stem Cells News and Stem Cells Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.