Microfluidics, image analysis, neurodegeneration, neuronal development
I was born and raised in Texas, completing my B.S. in Electrical Engineering at the University of Texas at Austin.
Since its introduction in 1974, the model organism Caenorhabditis elegans has played a crucial role towards discoveries in the fields of neural development and genetics. With genes homologous to many vertebrates, the animal provides an opportunity to study complex neural and genetic pathways in a comparatively simple environment. However, studying these mechanisms using current technologies such as quantitative microscopy is difficult. This is because standard methods (phenotypic screens) are performed manually and introduce bias into experimental analysis. In addition, animals with subtle phenotypes make classification more difficult for experimenters, requiring more time for analysis, and decreasing the throughput and efficacy of phenotypic screens. These issues together play roles in limiting the discovery of novel genes involved in neural development and neurodegeneration and bottleneck the advancement of C. elegans research. The long-term goal of many engineering advances, therefore, is to eliminate some of these bottlenecks. My thesis work aims to develop a method for high-throughput and automated phenotypic screens of C. elegans in order to identify neural-development and neurodegeneration mutants. To achieve this goal I will improve upon existing methods for imaging, immobilizing, and sorting worms in microfluidic chips, simplifying devices for operation by scientists, not engineers. The proposed device will be constructed from polydimethylsiloxane (PDMS) using the well-established soft lithography process and will immobilize nematodes by constricting their movement within an imaging chamber without the use of anesthetics. This will be accomplished by limiting the animal’s range of motion in conjunction with physical compression within the device. In parallel, I will develop image analysis software to quantify characteristics of specific neuronal features to phenotype animals. Software will make use of existing segmentation and detection algorithms. The contribution of my proposed work will be to refine these methods for analyzing animals on-chip, improving computational run time for high throughput phenotyping applications. I expect to increase the throughput of manual screening methods by 100 fold. Lastly, to validate the proposed technology I will screen with the goal of discovering at least three novel genes that effect neuronal development (specifically neuronal polarity and axon guidance) and neurodegeneration. The screen will be performed using a C. elegans strain which expresses green fluorescent protein (GFP) in a tail sensory neuron. I plan to identify mutants by searching for irregularities in neuron morphology. The proposed work is significant because it can dramatically increase current capabilities of screening small animals with subtle fluorescent phenotypes. The project will also advance neural development and neurodegeneration research by discovering novel mutants and investigating new genetic and protein networks specific to these processes. With the ability to analyze numerous C. elegans genotypes, this technology is relevant to many fields. In general, understanding the mechanisms behind behavior in any organism will help to further explain the mysteries of the human brain and potentially aid in the discovery of therapeutic treatments for various diseases.