Biological sensors and molecular signatures
Determine transcriptional networks/signatures that underlie development & function of dopaminergic neurons (integrating molecular biology, genetically-encoded sensors, microfluidics, computation, and mathematical modeling)…
Team Coordinator: Brian Nelms, PhD (Subproject PI)
Fisk Collaborators: R Mu (Fisk/TSU, physics/nanomaterials/microfluidics), S Hussain (Fisk CS);
Vanderbilt Collaborators: Deyu Li (Biomedical Engineering), Donna Webb (Biological Sciences)
Scientific Impact: The approach of combined transcriptional network analysis, microfluidics tools for sensing changes in response to added stimuli or genetic variation, and mathematical/ computational modeling will result in gaining valuable new knowledge and pose new research questions towards a better understanding of dopaminergic neuron function.
Innovation: We will bring together established cutting-edge techniques from multiple fields (next generation sequencing, microfluidics, and computational modeling) and apply these to the directed study of dopaminergic neuron function in living organisms to ask and answer questions in a new way.
Objective 1: Probe the misregulation of genes in the absence of the transcription factor FKH-8 as a window into transcriptional regulatory signatures needed for the development and sustained differentiation of dopaminergic (DA) neurons.
Objective 2: Develop a suite of microfluidic tools (“worms-on-chips”) leveraging genetically-encoded sensors to sense in vivo dopaminergic neuron responses (at the cellular and organismal level) to genetic changes and chemical exposure.
Objective 3: Use bioinformatics approaches to discover transcriptional networks, and develop, test, and iteratively optimize computational and mathematical models of C. elegans dopaminergic neuron function.