Abstract
The freshwater crayfish, Procambarus clarkii is an excellent aquatic animal model that is highly adaptable and tolerant. P. clarkii is widely used as a toxicity model to study various pharmaceutical exposure. This animal model has complex behavioral traits and is considered sensitive to environmental changes, making it an excellent candidate to study psychoactive drugs based on a behavioral approach. However, up to now, most behavioral studies on crayfish use manual observation and scoring that require panelists. In this study, we aim to develop an automation pipeline to analyze crayfish behavior automatically. We use a deep-learning approach to label body parts in multiple crayfish, and based on the trajectory results, the intra- or inter-individual crayfish were calculated. Reliable and fast results of several behavior endpoints in multiple crayfish were retrieved. We then validated the detection performance of numerous crayfish in specific gender groups (male-male and female-female). Based on the result, the male crayfish displayed significantly higher aggression than females. We also tested the antidepressant exposure on this animal model to evaluate the psychoactive effects of this drug. As male crayfish display more distinct agonistic behavior than females, we exposed them to sertraline (SRT) 1 ppb for 7 and 14 days. It was revealed that sertraline was able to alter several behavioral endpoints in crayfish. Significant increases in extend claw ratio, total distance moved, average speed, and rapid movement were displayed in sertraline-exposed crayfish but decreased interaction time and longest interaction time. In addition, SRT 14 days exposure could atler the aggressiveness and bold behavior In the present method, DeepLabCut (DLC) has been utilized to analyze the locomotion behavior of multiple crayfish. This established method provides rapid and accurate ecotoxicity measurements using freshwater crayfish, which beneficient and applicable for environmental research.
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