Functional Genomics: Phenotypic Screening of Regeneration Associated Genes in Central Nervous System Neurons

Adult mammalian central nervous system (CNS) neurons are unable to extend axons after injury, partially owing to the inhibitory myelin and chondroitin sulfate proteoglycans (CSPGs) present in the environment. A neuron\u27s intrinsic state is also important for determining its regenerative potential. Peripheral nervous system (PNS) neurons, unlike their CNS counterparts, have increased ability to regrow their axons after injury, even in the presence of inhibitory molecules. With the goal of discovering novel regeneration associated genes, we have isolated the genes differentially expressed by PNS neurons. We then developed a high throughput neuronal transfection method to test whether these genes were sufficient to modify neurite growth in vitro. Using high content screening, we measured the ability of cerebellar neurons to initiate neurite outgrowth on inhibitory and permissive substrates. This combination of technologies (subtractive hybridization, microarray, high throughput electroporation and high content screening) allowed phenotypic examination of neurons after the overexpression of over a thousand genes. Additionally, kinases and phosphatases were assayed for their ability to modify neurite outgrowth in hippocampal neurons. Results from both of these large unbiased screens confirmed many of the existing candidates for neurite growth during development and regeneration. We also discovered many novel genes which promoted neurite outgrowth such as GPX3, EIF2B5, RBMX, CHKA, IRF6, and PKN2. To accurately interpret the large volume of data, new methods of analysis were performed. Finally, we developed novel techniques that took advantage of public databases to cluster genes and determine whether those clusters produced robust changes in neurite growth. In summary, we have provided a vast repository of functional data to study axon development and regeneration after injury as well as developing the tools needed to interpret that data