Signaling dependent transcriptional control of neural plasticity in Drosophila
The major goal of the laboratory is to study molecular and cellular changes that underlie learning and memory. We use Drosophila as a model system to investigate signaling networks that operate in neurons during long-term plasticity. Essentially, long-term changes require synthesis of new proteins either through translation of pre-existing mRNA at synaptic sites or through activation of transcription. We have established that conserved signaling cascades such as those mediated by cAMP, PKA and MAPK operate in our model system to cause long-term change. These signaling cascades finally impinge on transcription factors to drive expression of “plasticity genes”. Among several broad questions in the field that interest us are studying signaling cross-talk during plasticity and the identification and functional validation of target genes. The final aim would be to ascertain how these genes regulate learning and memory in intact organisms, thus uncovering conserved principles of learning across species.
Synaptic plasticity is typically assayed by measuring two parameters at the neuromuscular junctions of Drosophila larvae, synapse size and synapse strength. This synapse is a glutamatergic synapse (similar to vertebrate central nervous system synapses) that undergoes activity dependent growth through the lifetime of the animals. As such, mechanisms and proteins shown to play a role in long-term plasticity in both vertebrate and invertebrate model organisms are utilized during this process of developmental plasticity. My research is aimed at studying the role of gene transcription during long-term plasticity and uses the NMJ as a model system. For instance, using this system we have shown that the IE transcription factor, AP1 (a heterodimer of Fos and Jun) positively regulates both synapse size and strength. This is in contrast to the role of CREB, which serves primarily to affect synaptic strength. Ongoing research aims to uncover both cellular signaling cascades that impinge on these transcription factors as well as identify their downstream targets. Thus, while on one hand we would like to describe the signaling network that transduces neural activity into changes in size and strength, on the other hand, we want to functionally characterize the ultimate effectors of such signaling.
