Engineering a High Throughput Method for Quantitative Analysis of Behavioral Neuromodulation in C. Elegans

For years, Caenorhabditis elegans has been a primary model organism for the study of biological processes, from development to aging. This species was the first multicellular organism to have its genome mapped and it is estimated that 60-80% of human genes have orthologs in C. elegans. The species has forty genes that code for different insulin-like-peptides (ILPs) which have been shown to influence various developmental and physiological processes, including lifespan and neural plasticity, but the specific roles of many of these peptides remain unknown. My research involves designing a high throughput platform to analyze the role that ILPs play in the behavior of C. elegans. This platform will allow for the quantitative analysis of movement, a downstream output of the nervous system, of a large number of organisms. The platform will be used to analyze the change in behavioral output of C. elegans lacking each one of the forty ILPs. RNA interference will be used to silence expression of the genes that code for the ILPs. This method involves feeding the worms bacteria that express double stranded RNA of the gene of interest and thus prevents the translation of the gene into protein. Videos of swimming animals will be acquired and analyzed by using specialized code in Matlab to quantify the differences in movement. This will be taking a step towards discovering what role each of the forty ILPs plays in modulating the state of the nervous system and learning about the ILP to ILP regulatory network.