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NC3Rs: National Centre for the Replacement Refinement & Reduction of Animals in Research
PhD Studentship

An alternative approach for assessing drug-induced seizures, using non-protected larval zebrafish

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At a glance

In progress
Award date
October 2018
Grant amount
Principal investigator
Professor Charles Tyler
University of Exeter


  • Replacement
Read the abstract
View the grant profile on GtR

Application abstract

Seizures comprise rhythmic and synchronised abnormal central nervous system (CNS) activity.

They have many causes, including as an unwanted side effect of some drugs. The standard approach for assessing new drugs for seizure liability is the electroencephalogram (EEG). This involves surgical implantation of electrodes into the brain of rats or mice, following drug treatment, and assessment of resultant electrical patterns to determine if a seizure has occured. EEGs are highly invasive, and costly, meaning they are often applied late in drug development. As a consequence large investments, including in other animal studies, can be made on new drugs that may subsequently fail due to seizure liability. Considerable effort has been made to develop earlier screens such as those that measure larval zebrafish behaviour associated with the induction of seizures (i.e. convulsions). This methodology, however, still employs protected life stages (7 days old) and only detects mechanisms that result in altered behaviour. To address this, we have developed an imaging-based approach, using a non-protected life stage (4 days old, circa. 3mm in length) of a transgenic zebrafish, in which we can non-invasively measure drug-induced activity across the whole brain. These transgenic larval zebrafish possess a fluorescent molecule in all neurons in the brain which allows visualisation of electrical activity using fluorescent microscopy. We have demonstrated the principle that mechanism-specific fingerprints of brain activity arise from treatment with different classes of drug giving this project a strong start. The student will build on these findings to generate neural activity data for a broad range of pharmacological mechanisms that produce seizures and (s)he will address the following three main objectives of the project: 1) Test the hypothesis that patterns of neural activity in the brain, are linked to specific types of drug. This will allow the student to generate a reference set of fingerprints for unambiguously identifying the occurrence of seizures in new drugs, as well as identifying the pharmacological mechanism of action; 2) To establish why certain types of drug result in altered behaviour, whereas others do not through comparing existing larval zebrafish behavioural data with imaging data for drug-exposed larvae. This work will also provide data for identifying neural activity patterns (and concomitant behavioural phenotypes) in zebrafish that may represent equivalents of certain classes of seizure/convulsion in mammals; 3) To demonstrate concordance between the non-invasive imaging data, and direct measurement of electrical activity via EEG in 4 day old larval zebrafish. This will allow confirmation of the electrical basis of observed fingerprints, and provide data to help translate for responses between zebrafish and more established seizure models. The approach proposed offers clear refinement over existing models by employing non-invasive imaging in a larval form of a lower vertebrate, and replacement of protected, with non-protected (younger) larvae. Direct measures of neural activity should also prove more sensitive than current behavioural approaches using larval zebrafish, potentially allowing refinement of drug treatment levels and a reduction in the number of animals required to achieve statistically-significant results. The general approach used here has many applications in neuroscience beyond the detection of drug-induced seizures, for example for the assessment of the effects of other types of neuroactive drugs (e.g. anaesthetics and analgesics), and assessment of the neural functional effects of altering genes associated with an increased risk of disorders such as Alzheimer’s and Parkinson’s diseases. This studentship project will provide an outstanding training in a wide range of research methods, including cutting edge imaging modalities and analyses of complex datasets.


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