Summary: The study reveals the molecular mechanism that allows neural networks to grow and branch.
Our nervous system is made up of billions of neurons that talk to each other through their axons and dendrites. As the human brain develops, these structures branch out in beautifully complex but poorly understood ways that allow nerve cells to form connections and send messages throughout the body. And now, Yale researchers have uncovered the molecular mechanism behind the growth of this complex system.
Their findings are published in Scientists progress.
“Neurons are highly branched cells, and they are that way because each neuron makes a connection with thousands of other neurons,” says Joe Howard, Ph.D., Eugene Higgins Professor of Molecular Biophysics and Biochemistry and Professor of physics, and senior researcher of the study.
“We are working on this branching process: how do branches form and grow? This is what underlies all the functioning of the nervous system.
The team studied neuronal growth in fruit flies as they transformed from embryos to larvae. To visualize this process, they labeled neurons with fluorescent markers and imaged them on a spinning disk microscope. Because neurons reside just below the cuticle [outermost layer]the researchers were able to observe this process in real time on living larvae.
After visualizing neurons at different stages of development, the team was able to create time-lapse movies of growth.
In the early stages of development, sensory neurons started out with only two or three dendrites. But in as little as five days, they blossomed into large tree-like structures with thousands of branches.
Analysis of dendritic spikes revealed their dynamic and stochastic (randomly determined) growth, which fluctuated between growing, shrinking, and paused states.
“Before our study, there was a theory that neurons could expand and deflate like a balloon,” says Sonal Shree, Ph.D., research associate and lead author of the study. “And we found that no, they don’t inflate like a balloon, but rather grow and branch their tips.”
“We found that we could completely explain neuronal growth and overall morphology in terms of what cell ends are doing,” says Sabyasachi Sutradhar, Ph.D., research associate and co-lead author of the study.
“That means we can now focus on the spikes, because if we can understand how they work, then we can understand how the whole shape of the cell is formed,” says Howard.
There is a whole world of offshoots in biology, from the veins and arteries of the circulatory system to the bronchioles of the lung. Howard’s lab hopes that a better understanding of branching at the cellular level will also shed light on these processes at the molecular and tissue levels.
About this neuroscience research news
Author: Isabelle Backman
Contact: Isabelle Backman-Yale
Image: Image is credited to Howard Lab
Original research: Free access.
“Dynamic instability of dendrite tips generates the highly branched morphologies of sensory neurons” by Sonal Shree et al. Scientists progress
Dynamic instability of dendrite tips generates the highly branched morphologies of sensory neurons
The highly branched arbors of neuronal dendrites provide the substrate for the brain’s high connectivity and computing power. Altered dendritic morphology is associated with neuronal diseases.
Many molecules have been shown to play crucial roles in the formation and maintenance of dendrite morphology. However, the underlying principles by which molecular interactions generate branching morphologies are not understood.
To elucidate these principles, we visualized the growth of dendrites throughout the larval development of the Drosophila sensory neurons and found that dendrite tips experience dynamic instability, rapidly and stochastically switching between growing, shrinking, and paused states.
By incorporating these measured dynamics into an agent-based computer model, we showed that the complex and highly variable dendritic morphologies of these cells are a consequence of the stochastic dynamics of their dendritic tips.
These principles can be generalized to branching of other neuronal cell types, as well as branching at the subcellular and tissue levels.