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Automatically tracking feeding behavior in populations of foraging worms

MPG-Autoren
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Bonnard,  Elsa       
Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;
International Max Planck Research School (IMPRS) for Brain and Behavior, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;

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Liu,  Jun       
Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;

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Zjacic,  Nicolina       
Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;
External Organizations;

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Alvarez,  Luis       
Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;
Emeritus Group Molecular Sensory Systems, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;

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Scholz,  Monika       
Max Planck Research Group Neural Information Flow, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society;

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Zitation

Bonnard, E., Liu, J., Zjacic, N., Alvarez, L., & Scholz, M. (2022). Automatically tracking feeding behavior in populations of foraging worms. bioRxiv: the preprint server for biology. doi:10.1101/2022.01.20.477072.


Zitierlink: https://hdl.handle.net/21.11116/0000-000A-EB4C-9
Zusammenfassung
C. elegans feeds on bacteria and other small microorganisms which it ingests using its pharynx, a neuromuscular pump. Currently, measuring feeding behavior requires tracking a single animal, indirectly estimating food intake from population-level metrics, or using restrained animals. Therefore, to enable large throughput feeding measurements of unrestrained, crawling worms on agarose plates, we developed an imaging protocol and a complementary image analysis tool called Pharaglow. We image up to 50 freely moving worms simultaneously and extract locomotion and feeding behaviors. Our tool reliably detects pharyngeal pumping in adult worms with a maximum deviation of 5% in the number of pumps compared to an expert annotator. We demonstrate the tool's robustness and high throughput capabilities by measuring feeding in different use-case scenarios. This includes tracing pharyngeal dynamics during development, revealing their highly conserved nature throughout all lifecycle stages. We also observed pumping after food deprivation, corroborating previous studies in which starvation time strongly influences pumping. Finally, we further validated our behavioral tracker by exploring two previously characterized pumping defective mutants: unc-31 and eat-18. Remarkably, our analysis of eat-18 mutants identified unreported defects in pumping and overall locomotion regulation, highlighting the potential of this toolkit. Pharaglow therefore enables the observation and analysis of the temporal dynamics of food intake with high-throughput and precision in a user-friendly system.