Abstract
ABSTRACTCurrent treatments for anxiety and depression show limited efficacy in many patients indicating that research into new underlying mechanisms is needed. Inhibition of JNK1 has been shown to evoke an anxiolytic-and antidepressant-like phenotype in mice however the downstream effectors that elicit these behavioural effects are unknown. Here we employ a zebrafish (D. Rerio) larvae behavioural assay to identify an antidepressant-/anxiolytic-like phenotype based on 2759 measured stereotypic responses to clinically proven antidepressant and anxiolytic (AA) drugs. Employing machine learning, we classify an AA phenotype from behavioural features measured during and after a startle battery in fish exposed to AA drugs (fluoxetine, imipramine, diazepam, lithium chloride, ketamine). We demonstrate that structurally independent JNK inhibitors replicate the AA classification with high accuracy, consistent with findings in mice. We go on to identify signalling hubs downstream from JNK1 by comparing phosphoproteome data from wildtype andJnk1-/-mouse brains, and test these hubs as possible mediators of the AA phenotype in zebrafish larvae. Among these, we find that AKT, GSK-3, 14-3-3ζ/ε and PKCε, when pharmacologically targeted, phenocopy clinically proven AA drugs. This assay shows promise as an early phase screening for compounds with anti-stress-axis/anxiolytic-like properties, and for mode of action analysis.
Publisher
Cold Spring Harbor Laboratory