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  • Title: Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.
    Author: Schuch KN, Govindarajan LN, Guo Y, Baskoylu SN, Kim S, Kimia B, Serre T, Hart AC.
    Journal: J Neurogenet; 2020; 34(3-4):453-465. PubMed ID: 32811254.
    Abstract:
    Following prolonged swimming, Caenorhabditis elegans cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for C. elegans and here we suggest that inactive bouts are a recovery state akin to fatigue. It is known that cGMP-dependent kinase (PKG) activity plays a conserved role in sleep, rest, and arousal. Using C. elegans EGL-4 PKG, we first validate a novel learning-based computer vision approach to automatically analyze C. elegans locomotory behavior and an edge detection program that is able to distinguish between activity and inactivity during swimming for long periods of time. We find that C. elegans EGL-4 PKG function impacts timing of exercise-induced quiescent (EIQ) bout onset, fractional quiescence, bout number, and bout duration, suggesting that previously described pathways are engaged during EIQ bouts. However, EIQ bouts are likely not sleep as animals are feeding during the majority of EIQ bouts. We find that genetic perturbation of neurons required for other C. elegans sleep states also does not alter EIQ dynamics. Additionally, we find that EIQ onset is sensitive to age and DAF-16 FOXO function. In summary, we have validated behavioral analysis software that enables a quantitative and detailed assessment of swimming behavior, including EIQ. We found novel EIQ defects in aged animals and animals with mutations in a gene involved in stress tolerance. We anticipate that further use of this software will facilitate the analysis of genes and pathways critical for fatigue and other C. elegans behaviors.
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