Animal movement depends on specific circuits in which interneurons from the brain drive the activity of motor neurons in the axial nerve cord. In C. elegans, command interneurons synapse with specific classes of ventral cord motor neurons. For example, the command interneurons AVA, AVD, and AVE synapse with A-type motor neurons (DA/VA), whereas AVB and PVC synapse with B-type motor neurons (DB/VB). Coordinated movement depends on these connections; in
unc-4 mutants, VAs are miswired with inputs normally reserved for their VB sisters (i.e. from AVB and PVC) and are unable to execute backward locomotion. To identify molecular differences between command interneurons that synapse with A-type vs. B-type motor neurons, we are using a 2-color Fluorescence-Activated Cell Sorting (FACS) strategy to profile gene expression in these cells. In this approach, two promoters are selected such that their expression patterns overlap only in the interneuron of interest. For example,
rig-3::GFP and
glr-1::dsRed2 are each expressed in several neurons in the head but are uniquely co-expressed in AVA (L+R). Cultured cells from this strain show the expected populations of GFP-only, DsRed2-only, and GFP-DsRed2 expressing cells. By FACS isolation of the GFP-DsRed2 expressing cells, we have achieved high enrichment for embryonic AVA neurons thereby enabling isolation of RNA for microarray analysis. This approach will be utilized to profile each pair of command interneurons (AVA, AVD, AVE, AVB, PVC) in the motor circuit. We expect that these data will reveal genes with key roles in the function and connectivity of these neurons. To extend this approach to other embryonic neurons, we have developed NeuProfiler, a program that mines WormBase for expression patterns of promoter pairs that uniquely overlap in a single neuron. This approach revealed a surprisingly large number of potential promoter pairs (2631 for single neurons and 10315 for L+R neuron pairs) that could be used to isolate 26 single neurons or 65 neuron pairs from the embryo. In the future, we will exploit selected promoter pairs from these lists to profile additional embryonic neurons. These data sets will be analyzed with newly developed computational algorithms to search for gene combinations that are highly correlated with synaptic connectivity (Varadan, et al., 2006). This approach has the potential of shedding light on the biological mechanisms of synaptogenesis. Varadan, V., Anastassiou, D., Miller, D.M. 2006. Computational inference of the molecular logic for synaptic connectivity in C. elegans. Bioinformatics, Jul 15;22(14).