The swimming plus-maze test: a novel high-throughput model for assessment of anxiety-related behaviour in larval and juvenile zebrafish (Danio rerio)
Larval zebrafish ( Danio rerio ) has the potential to supplement rodent models due to the availability of resource-efficient, high-throughput screening and high-resolution imaging techniques. Although behavioural models are available in larvae, only a few can be employed to assess anxiety. Here we p...
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Veröffentlicht in: | Scientific reports 2018-11, Vol.8 (1), p.16590-11, Article 16590 |
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Sprache: | eng |
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Zusammenfassung: | Larval zebrafish (
Danio rerio
) has the potential to supplement rodent models due to the availability of resource-efficient, high-throughput screening and high-resolution imaging techniques. Although behavioural models are available in larvae, only a few can be employed to assess anxiety. Here we present the swimming plus-maze (SPM) test paradigm, a tool to assess anxiety-related avoidance of shallow water bodies in early developmental stages. The “+” shaped apparatus consists of arms of different depth, representing different levels of aversiveness similarly to the rodent elevated plus-maze. The paradigm was validated (i) in larval and juvenile zebrafish, (ii) after administration of compounds affecting anxiety and (iii) in differentially aversive experimental conditions. Furthermore, we compared the SPM with conventional “anxiety tests” of zebrafish to identify their shared characteristics. We have clarified that the preference of deeper arms is ontogenetically conserved and can be abolished by anxiolytic or enhanced by anxiogenic agents, respectively. The behavioural readout is insensitive to environmental aversiveness and is unrelated to behaviours assessed by conventional tests involving young zebrafish. Taken together, we have developed a sensitive high-throughput test allowing the assessment of anxiety-related responses of zebrafish regardless of developmental stage, granting the opportunity to combine larva-based state-of-the-art methods with detailed behavioral analysis. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-018-34989-1 |