Zebrafish Behavioral Profiling Links Drugs to Biological Targets and Rest/Wake Regulation
Published: 01-15-2016 In Publication
A major obstacle for the discovery of psychoactive drugs is the inability to predict how small molecules will alter complex behaviors. We report the development and application of a high-throughput, quantitative screen for drugs that alter the behavior of larval zebrafish. We found that the multidimensional nature of observed phenotypes enabled the hierarchical clustering of molecules according to shared behaviors. Behavioralprofiling revealed conserved functions of psychotropic molecules and predicted the mechanisms of action of poorly characterized compounds. In addition, behavioralprofiling implicated new factors such as ether-a-go-go-related gene (ERG) potassium channels and immunomodulators in the control of rest and locomotor activity. These results demonstrate the power of high-throughput behavioralprofiling in zebrafish to discover and characterize psychotropic drugs and to dissect the pharmacology of complex behaviors.
Larval zebrafish locomotor activity assay
(A) At four days post fertilization (dpf), an individual zebrafish larva is pipetted into each well of a 96-well plate with small molecules. Automated analysis software tracks the movement of each larva for 3 days. Each compound is tested on 10 larvae. (B) Locomotor activity of a representative larva. The rest and wake dynamics were recorded, including the number and duration of rest bouts (i.e. a continuous minute of inactivity, (7)), the timing of the first rest bout following a light transition (rest latency), the average waking activity (average activity excluding rest bouts), and the average total activity. Together, these measurements generate a behavioral fingerprint for each compound.
Hierarchical clustering reveals the diversity of drug-induced behaviors
(A) Behavioral profiles are hierarchically clustered to link compounds to behaviors. Each square of the clustergram represents the average relative value (in standard deviations; yellow = higher than controls, blue = lower than controls) for a single behavioral measurement. Dark bars indicate specific clusters analyzed in subsequent figures. (B–F) Normalized waking activity and rest graphs are plotted for behavior-altering compounds (red trace; average of 10 larvae) and representative controls (10 blue traces; average of 10 larvae each). Compounds that altered behavior include the mood stabilizer and anti-epileptic drug sodium valproate (B), the psychotomimetic NMDA antagonist L-701324 (C), the sodium channel agonist pesticide DDT (D), the anti-malarial halofantrine (E), and the calcium channel blocker methoxyverapamil (F).
Unexpected regulators of zebrafish rest/wake states
(A) Podocarpatrien-3-one analogs increase rest latency, the time from light transition to the first rest bout, relative to controls. Error bars represent +/− SEM (B) Many wake-promoting anti-inflammatory and immunomodulating compounds co-cluster (blue—NSAIDs; green—glucocorticoids; pink—PDE inhibitors; yellow—miscellaneous; white—no anti-inflammatory annotation). See Figure S17 for an extended list. (C) A cluster of ERG-blocking compounds specifically increases waking activity at night. (D) Rank sorting the data set by correlation to the ERG blocking cluster results in a significant enrichment of ERG blockers in the top ranks [p<10–13 by the Kolmogorov-Smirnov statistic (see methods)]. Black lines indicate known ERG blockers; red indicates high correlation, green indicates low correlation to the ERG cluster. This analysis also detected potential indirect regulators of ERG function, for example the organophosphate coumaphos (marked with an asterisk), which causes long QT through an unknown mechanism (20).
Rihel J, Prober DA, Arvanites A, Lam K, Zimmerman S, Jang S, Haggarty SJ, Kokel D, Rubin LL, Peterson RT, Schier AF.