Our nervous system is continuously rebuilding itself. While nerve cells live for years, the proteins and molecules that make them up have to be replaced all the time. How does all this turnover happen without affecting how we think, remember, or learn?
To help solve this longstanding mystery, a team led by Timothy O’Leary and Eve Marder of Brandeis University built a simple biochemical model of neurons monitoring and self-regulating their cellular components. In particular, they were interested in the turnover rate of ion channels and receptors, and how cells avoid disrupting the electrical signaling of normal nervous system functions.
Ion channels are tiny gates found on the surface of nerve cells. These determine the various neuronal properties needed to regulate things ranging from the speed of limb movement to how sensory information is processed. And receptors are what neurons use to communicate with each other.
According to the researchers, neurons have an internal gauge that monitors electrical activity and adjusts ion channel expression accordingly. So, the team built a theoretical model of ion channel regulation based on that idea of an internal monitoring system. Their model generated a diversity of self-regulating cell types.
They discovered that cells don’t need to measure every detail of activity to keep the system functioning: Too much detail actually derails the process. “Certain target properties can contradict each other,” O’Leary explains in a news release. “You would not set your air conditioning to 64 degrees and your heat to 77 degrees.” Additionally, they also learned that cells with similar properties can have different ion channel expression rates.
On the flip side, the model showed that the very internal monitoring system designed to control runaway electrical activity can also cause “neuronal hyperexcitability.” That’s when there’s an excessive amount of activity, and the system’s overall homeostasis is lost. The result in that case is a seizure. “To understand and cure some diseases, we need to pick apart and understand how biological systems control their internal properties when they are in a normal healthy state,” O’Leary says. “And this model could help researchers do that.”
The work was published in Neuron last week.
[Via Brandeis]
Image: Brandeis University
