Novel Approach Opens New Research Opportunities
For his doctoral thesis at Â鶹¾«Æ·ÊÓƵ, Juan Lopez, Ph.D., needed a swarm of genetically modified flies. In order to conduct myriad experiments investigating synaptic activity in Drosophila neurons, he had to laboriously crossbreed mutants with mail-ordered modified animals — 10,000 to 15,000 because only 2 to 3% would survive into adulthood.
Today, as a postdoctoral researcher in the Charles E. Schmidt College of Science and the Stiles-Nicholson Brain Institute, under the mentorship of Rodrigo Pena, Ph.D., Lopez is building a computational model that can replace his painstaking work with live animals.
"If the model is successful, it’ll let us perform experiments modeling flies that have an incredibly low survival rate," he said.
Lopez’s model replicates a giant neuron that enables escape behavior in the fly. He mathematically formulates physiological parameters of the neuron, such as size, diameter and ion conductance, and divides them into four "compartments" representing different segments of the neuron and postsynaptic partner.
"The compartments are chained together to mimic an action potential traveling down the Giant Fiber’s length," he said.
Lopez and his team can assess the effect of the mutations they introduced into the fly by measuring whether it produced an action potential on the other side of the synapse.
Lopez’s novel approach makes his model an effective tool for both research and teaching. "It lets you do all sorts of things faster than it would take with a fly, and it can be used with undergrads, grad students — even people who’ve never been in the lab," he said.
Moreover, the "compartments" can be programmed to represent any part of the neuron, giving the model flexibility and breadth. "Not every compartment has to be the same. And just because right now it’s a Drosophila model doesn’t mean that it can’t be applied to other neurons as well," he said.