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Caenorhabditis elegans Show Preference for Stimulants and Potential as a Model Organism for Medications Screening

The nematode ( ) is a popular invertebrate model organism to study neurobiological disease states. This is due in part to the intricate mapping of all neurons and synapses of the entire animal, the wide availability of mutant strains, and the genetic and molecular tools that can be used to manipulat...

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Bibliographic Details
Published in:Frontiers in physiology 2018-08, Vol.9, p.1200-1200
Main Authors: Engleman, Eric A, Steagall, 2nd, Kevin B, Bredhold, Kristin E, Breach, Michaela, Kline, Hannah L, Bell, Richard L, Katner, Simon N, Neal-Beliveau, Bethany S
Format: Article
Language:English
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Summary:The nematode ( ) is a popular invertebrate model organism to study neurobiological disease states. This is due in part to the intricate mapping of all neurons and synapses of the entire animal, the wide availability of mutant strains, and the genetic and molecular tools that can be used to manipulate the genome and gene expression. We have shown that, develops a conditioned preference for cues that had previously been paired with either cocaine or methamphetamine exposure that is dependent on dopamine neurotransmission, similar to findings using place conditioning with rats and mice. In the current study, we show also display a preference for, and self-exposure to, cocaine and nicotine. This substance of abuse (SOA) preference response can be selectively blocked by pretreatment with naltrexone and is consistent with the recent discovery of an opioid receptor system in . In addition, pre-exposure to the smoking cessation treatment varenicline also inhibits self-exposure to nicotine. Exposure to concentrations of treatments that inhibit SOA preference/self-exposure did not induce any significant inhibition of locomotor activity or affect food or benzaldehyde chemotaxis. These data provide predictive validity for the development of high-throughput behavioral medication screens. These screens could enable fast and accurate generation of data to identify compounds that may be effective in treating human addiction. The successful development and validation of such models would introduce powerful and novel tools in the search for new pharmacological treatments for substance use disorders, and provide a platform to study the mechanisms that underlie addictions.
ISSN:1664-042X
1664-042X
DOI:10.3389/fphys.2018.01200