Biological sensors and molecular signatures
Determine transcriptional networks/signatures that underlie the 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.