Loss of motor control is a hallmark of many neurodegenerative diseases and correlates with onset, severity, and progression of the disease. A full understanding of the mechanisms by which these disease phenotypes occur requires integration of molecular, cellular, and pathway information over time -- an undoubtedly complex task. Towards this goal, I will carry out a large-scale study of an extensive library of genetic strains of the model organism C. elegans. These strains enable controlled experiments which can relate, for example, disruptions in specific neuronal signaling pathways or progressive protein aggregation to movement phenotypes over time. Although smaller scale studies have shed light on the roots of specific disease phenotypes, a systematic large-scale study is needed. To relate strain-specific mutations to fine- grained movement phenotypes, I will use high-resolution cameras to simultaneously observe a large number of worms and record their shapes, paths of crawling, and relationships between body segments. First, motion characteristics will be used to cluster worm strains with similar phenotypes to create a high-resolution phenotype categorization (Aim 1). While most of the library strains are annotated with gross phenotypes, such as decreased motility or paralysis, relatively few have been characterized with respect to more subtle changes in motor control such as stiffness and twitching. Custom software automatically screens my collected data for subtle differences in motion. Next, library strain information will be used to systematically link each phenotype to the molecular and cellular structures known to be involved (Aim 2). Then, this tool will be used to predict and experimentally validate testable hypotheses about the collapse of heath in currently uncharacterized disease models (Aim 3). The systematic linkage between phenotype and genetic, molecular and cellular underpinnings in C. elegans would be highly valuable step toward advanced diagnostic tools for humans.
Loss of motor control is a hallmark of many neurodegenerative diseases and correlates with onset, severity, and progression of the disease. I will systematically cluster hundreds of C. elegans strains into high- resolution phenotype classes describing movement and then link each class to a set of known genetic, molecular, and cellular defects. This high-throughput, high-content phenotypic collection will serve as a tool to track the progression of disease in several uncharacterized disease model strains, and this linkage will be a tool to predict the set of disruptions occurring in each worm.
|Winter, Peter B; Brielmann, Renee M; Timkovich, Nicholas P et al. (2016) A network approach to discerning the identities of C. elegans in a free moving population. Sci Rep 6:34859|