A robotic system for automated genetics of Caenorhabditis elegans

The roundworm Caenorhabditis elegans is one of the widely used genetic systems in biology due to its compact anatomy, rapid development and optical transparency. Genetic manipulation and analysis of C. elegans depend on labor-intensive and low-throughput manual procedures, imposing a significant challenge to many studies. Here, I describe a general-purpose tool, WormPicker, a robotic system capable of genetically manipulating C. elegans by imaging, phenotyping, and transferring animals on standard agar media. The automated system uses a 3D motorized stage to move an imaging system and a robotic arm over a set of agar plates. Machine vision tracks individual animals and assays fundamental phenotypes. Based on the recognized phenotypes, the robotic arm selectively transfers individual C. elegans using an electrically self-sterilized wire loop, guided by machine vision and capacitive touch sensing. The robotic C. elegans manipulation shows reliability and speed comparable to that of the experienced researchers. I developed custom software for the system to carry out complex genetic procedures. To validate the versatility and effectiveness of WormPicker, I used the robotic system to automate a collection of standard genetic protocols. To further demonstrate WormPicker’s capabilities, I employed the automation tools to conduct a genetic screen for modifiers of stress-induced sleep (SIS) in C. elegans, a task that would be challenging using manual methods. The robotic system reliably maintained a library of mutagenized strains, prepared sleep assays, and performed other manipulations. Using the resulting sleep data, I developed statistical methods for determining the associations between the genes and the sleep phenotypes. My analysis has unveiled a set of novel candidate genes associated with SIS in C. elegans. Further analysis of these genes holds the promise to deepen our understanding of sickness sleep. In summary, WormPicker accelerates a wide range of C. elegans research and opens opportunities for genetic and pharmacological screens that would be impractical using manual methods.

Author dc:creator

• Li, Zihao

Advisor dc:contributor.advisor

• Fang-Yen, Christopher

• Engineering
• Genetics and Genomics
• Electrical Engineering

Language dc:language.iso

en

Repository record dc:identifier.uri

https://repository.upenn.edu/handle/20.500.14332/59511

OAI identifier oai:identifier

oai:repository.upenn.edu:20.500.14332/59511