Validation, optimization, and quality assessment of a neuro-behavioral in vivo assay for phenotypic high-content evaluation of anesthetics

In vivo assays based on aquatic model organisms have played a pivotal role in the development of anesthetics and their pharmacological and physiological characterization. They have been designed primarily as cost-effective tools for initial screening of compounds, prioritizing high throughput and simple measurement of a behavioral readout. Common limitations include manual recoding and analysis of behavioral readouts, thereby introducing potential bias; focus on the binary endpoints of a single behavior; restriction of the assessment of drug effects to the behavioral level, thus being agnostic of neural and/or molecular targets; and low content overall. The Neuro-Behavioral Assay presented here overcomes these restrictions. It is based on the non-invasive recording of the electric organ discharge of an electric fish, serving as a proxy of the neural activity of an endogenous brainstem oscillator, the pacemaker nucleus. From the single recording of the discharge, three behavioral readouts (reflecting the fish's locomotor activity as well as the frequency and the rate of amplitude-frequency modulations of the synchronized neural pacemaker oscillations) are extracted and analyzed automatically, thereby eliminating the operator's bias. The behavioral output is recorded on a continuous scale, thus enabling assessment of gradual changes in behavior induced by anesthetics and during recovery from anesthesia. By testing the effects of three anesthetics (tricaine methanesulfonate, eugenol, and urethane), protocols for running the assay have been optimized and validated through in vitro electrophysiology. Assessment of the results by statistical analysis and measures of assay performance, such as the Signal-to-Noise Ratio and the Z-Factor, have demonstrated a high quality of the Neuro-Behavioral Assay. Overall, while keeping the costs at a moderate level, the Neuro-Behavioral Assay generates high content and offers the opportunity for target deconvolution. It is, therefore, uniquely suited for bridging the current gap in anesthetic drug discovery between the identification of candidate molecules through high-throughput screening assays and the preclinical testing of lead compounds through assays employing mammalian model systems.