Adam Michael Stewart1, Fabrizio Grieco2, Ruud A J Tegelenbosch2, Evan J Kyzar3, Michael Nguyen1, Aleksandra Kaluyeva1, Cai Song4, Lucas P J J Noldus5, Allan V Kalueff6. 1. ZENEREI Research Center, 309 Palmer Court, Slidell, LA 70458, USA; The International Zebrafish Neuroscience Research Consortium, ZNRC, Slidell, LA 70458, USA. 2. Noldus Information Technology BV, Nieuwe Kanaal 5, 6709 PA Wageningen, Netherlands. 3. Department of Psychiatry, College of Medicine, University of Illinois at Chicago, Chicago, IL 60608, USA. 4. Research Institute for Marine Drugs and Nutrition (RIMDN), CFST, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China; College of Food Science and Technology, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China; Neuroscience Graduate Program, China Medical University Hospital, Taichung, Taiwan. 5. The International Zebrafish Neuroscience Research Consortium, ZNRC, Slidell, LA 70458, USA; Noldus Information Technology BV, Nieuwe Kanaal 5, 6709 PA Wageningen, Netherlands. 6. Research Institute for Marine Drugs and Nutrition (RIMDN), CFST, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China; College of Food Science and Technology, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China; Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia; Laboratory of Anatomy and Physiology, Institute of Natural Sciences, Ural Federal University, Ekaterinburg, 620002, Russia. Electronic address: avkalueff@gmail.com.
Abstract
BACKGROUND: Expanding the spectrum of organisms to model human brain phenotypes is critical for our improved understanding of the pathobiology of neuropsychiatric disorders. Given the clear limitations of existing mammalian models, there is an urgent need for low-cost, high-throughput in-vivo technologies for drug and gene discovery. NEW METHOD: Here, we introduce a new automated method for generating 3D (X,Y,Z) swim trajectories in adult zebrafish (Danio rerio), to improve their neurophenotyping. RESULTS: Based on the Track3D module of EthoVision XT video tracking software (Noldus Information Technology), this tool enhances the efficient, high-throughput 3D analyses of zebrafish behavioral responses. Applied to adult zebrafish behavior, this 3D method is highly sensitive to various classes of psychotropic drugs, including selected psychostimulant and hallucinogenic agents. COMPARISON WITH EXISTING METHODS: Our present method offers a marked advance in the existing 2D and 3D methods of zebrafish behavioral phenotyping, minimizing research time and recording high-resolution, automatically synchronized videos with calculated, high-precision object positioning. CONCLUSIONS: Our novel approach brings practical simplicity and 'integrative' capacity to the often complex and error-prone quantification of zebrafish behavioral phenotypes. Illustrating the value of 3D swim path reconstructions for identifying experimentally-evoked phenotypic profiles, this method fosters innovative, ethologically relevant, and fully automated small molecule screens using adult zebrafish.
BACKGROUND: Expanding the spectrum of organisms to model human brain phenotypes is critical for our improved understanding of the pathobiology of neuropsychiatric disorders. Given the clear limitations of existing mammalian models, there is an urgent need for low-cost, high-throughput in-vivo technologies for drug and gene discovery. NEW METHOD: Here, we introduce a new automated method for generating 3D (X,Y,Z) swim trajectories in adult zebrafish (Danio rerio), to improve their neurophenotyping. RESULTS: Based on the Track3D module of EthoVision XT video tracking software (Noldus Information Technology), this tool enhances the efficient, high-throughput 3D analyses of zebrafish behavioral responses. Applied to adult zebrafish behavior, this 3D method is highly sensitive to various classes of psychotropic drugs, including selected psychostimulant and hallucinogenic agents. COMPARISON WITH EXISTING METHODS: Our present method offers a marked advance in the existing 2D and 3D methods of zebrafish behavioral phenotyping, minimizing research time and recording high-resolution, automatically synchronized videos with calculated, high-precision object positioning. CONCLUSIONS: Our novel approach brings practical simplicity and 'integrative' capacity to the often complex and error-prone quantification of zebrafish behavioral phenotypes. Illustrating the value of 3D swim path reconstructions for identifying experimentally-evoked phenotypic profiles, this method fosters innovative, ethologically relevant, and fully automated small molecule screens using adult zebrafish.
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