Altered Glycolysis and Mitochondrial Respiration in a Zebrafish Model of Dravet Syndrome

Abstract

Altered metabolism is an important feature of many epileptic syndromes but has not been reported in Dravet syndrome (DS), a catastrophic childhood epilepsy associated with mutations in a voltage-activated sodium channel, Nav1.1 (SCN1A). To address this, we developed novel methodology to assess real-time changes in bioenergetics in zebrafish larvae between 4 and 6 days post fertilization (dpf). Baseline and 4-aminopyridine (4-AP) stimulated glycolytic flux and mitochondrial respiration were simultaneously assessed using a Seahorse Biosciences extracellular flux analyzer. Scn1Lab mutant zebrafish showed a decrease in baseline glycolytic rate and oxygen consumption rate (OCR) compared to controls. A ketogenic diet formulation rescued mutant zebrafish metabolism to control levels. Increasing neuronal excitability with 4-AP resulted in an immediate increase in glycolytic rates in wild-type zebrafish; whereas mitochondrial OCR increased slightly and quickly recovered to baseline values. In contrast, scn1Lab mutant zebrafish showed a significantly slower and exaggerated increase of both glycolytic rates and OCR after 4-AP. The underlying mechanism of decreased baseline OCR in scn1Lab mutants was not due to altered mitochondrial DNA content or dysfunction of enzymes in the electron transport chain (ETC) or tricarboxylic acid (TCA) cycle. Examination of glucose metabolism using a PCR array identified five glycolytic genes that were down-regulated in scn1Lab mutant zebrafish. Our findings in scn1Lab mutant zebrafish suggest that glucose and mitochondrial hypometabolism contribute to the pathophysiology of DS.

Significance Statement: These studies demonstrate that metabolism can be studied in zebrafish, and that this novel approach can be used (i) to evaluate chemoconvulsant or genetic zebrafish models of epilepsy or (ii) in metabolism-based drug screening efforts to identify compounds that modulate glycolysis or mitochondrial function. As more models of epilepsy become available, the array of techniques demonstrated here can be used to rapidly characterize metabolic contributions to disease states.