Brain activity patterns in high-throughput electrophysiology screen predict both drug efficacies and side effects

Abstract

Neurological drugs are often associated with serious side effects, yet drug screens typically focus only on efficacy. We demonstrate a novel paradigm utilizing high-throughput in vivo electrophysiology and brain activity patterns (BAPs). A platform with high sensitivity records local field potentials (LFPs) simultaneously from many zebrafish larvae over extended periods. We show that BAPs from larvae experiencing epileptic seizures or drug-induced side effects have substantially reduced complexity (entropy), similar to reduced LFP complexity observed in Parkinson’s disease. To determine whether drugs that enhance BAP complexity produces positive outcomes, we used light pulses to trigger seizures in a model of Dravet syndrome, an intractable genetic epilepsy. The highest-ranked compounds identified by BAP analysis exhibit far greater anti-seizure efficacy and fewer side effects during subsequent in-depth behavioral assessment. This high correlation with behavioral outcomes illustrates the power of brain activity pattern-based screens and identifies novel therapeutic candidates with minimal side effects.

A simple and effective F0 knockout method for rapid screening of behaviour and other complex phenotypes

“…This two-step approach assumes that the phenotyping requires substantial time or resources, for instance video tracking behaviour over multiple days. If phenotyping is rapid and/or largely automated (Eimon et al, 2018;Kokel et al, 2010), genotyping can be performed directly on a sample of the phenotyped animals. If a gRNA is found not to generate enough mutations, it can be replaced, and the experiment repeated.…”

Summary: Order and Disorder in Brains and Behavior

“…These approaches facilitate relating neuron types across species at the transcriptomic level. Dravet syndrome, a severe pediatric epilepsy caused by a mutation in voltage-gated sodium channels, can now be studied using high-throughput approaches to screen for drugs in a dish with patient-derived cells, shown by Dolmetsch, in a transgenic fish model described by Yanik (Eimon et al 2018).…”

Evolution of Epileptiform Activity in Zebrafish by Statistical-Based Integration of Electrophysiology and 2-Photon Ca2+ Imaging

“…Studies that rely on only one modality are intrinsically limited and cannot capture the full complexity of epileptic activity. Recent developments include multi-electrodes platforms for the parallel LFP recording from multiple larvae [15,17,18,20]. These methods are extremely useful for the screening of antiepileptic drugs, but the presence of a large LFP transient is not sufficient to define an epileptic event.…”

“…Therefore, electrophysiology requires additional information for the unequivocal identification of the mutant phenotypes and for the evaluation of anti-epileptic compounds.Recently, deep learning classifiers have been employed to identify electrophysiological events [19] and, although these methods are very fast and effective, they are unavoidably affected by the need of an a priori classification of epilepsy features and by the degree of completeness of the training dataset. A high-throughput local field potential (LFP) recording platform has also recently been used to analyze high-order statistical moments for an unsupervised detection of seizures [20]. However, these electrophysiological methods for seizure identification and classification are still prone to be affected by motion artefacts.…”