Automatically tracking feeding behavior in populations of foraging C. elegans

Area of Science:

• * Neuroscience and behavioral biology
• * Genetics and developmental biology

Background:

• * Accurate measurement of feeding behavior in *Caenorhabditis elegans* (a model organism) is crucial for understanding its biology.
• * Current methods for measuring worm feeding are often low-throughput, indirect, or require restraining the animals, limiting detailed behavioral analysis.

Purpose of the Study:

• * To develop a high-throughput imaging protocol and analysis tool, PharaGlow, for precise, single-worm measurement of feeding behavior in unrestrained, crawling *C. elegans*.
• * To enable simultaneous observation of locomotion and feeding dynamics in multiple worms on standard agarose plates.

Main Methods:

• * Development of a novel imaging protocol to capture simultaneous video of up to 50 unrestrained, crawling *C. elegans*.
• * Creation of PharaGlow, a Python-based image analysis workflow to extract locomotion and feeding (pharyngeal pumping) data from videos.
• * Validation of the system across various conditions, including developmental stages, genetic/chemical perturbations, and food availability.

Main Results:

• * PharaGlow successfully quantifies feeding and locomotion behaviors in unrestrained, crawling *C. elegans* at single-worm resolution.
• * The tool demonstrates robustness and high-throughput capabilities across diverse experimental scenarios, including long-term imaging of mating and genetically distinct worms.
• * The methodology utilizes readily available low-resolution fluorescence microscopes, making it broadly accessible to *C. elegans* research labs.

Conclusions:

• * PharaGlow provides an accessible, user-friendly system for high-throughput, precise analysis of temporal feeding and locomotory dynamics in *C. elegans*.
• * This tool significantly advances the ability to study feeding behavior in response to various biological and environmental factors.