Opioid research in amphibians: An alternative pain model yielding insights on the evolution of opioid receptors

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Abstract

This review summarizes the work from our laboratory investigating mechanisms of opioid analgesia using the Northern grass frog, Rana pipiens. Over the last dozen years, we have accumulated data on the characterization of behavioral effects after opioid administration on radioligand binding by using opioid agonist and antagonist ligands in amphibian brain and spinal cord homogenates, and by cloning and sequencing opioid-like receptor cDNA from amphibian central nervous system (CNS) tissues. The relative analgesic potency of mu, delta, and kappa opioids is highly correlated between frogs and other mammals, including humans. Radioligand binding studies using selective opioid agonists show a similar selectivity profile in amphibians and mammals. In contrast, opioid antagonists that are highly selective for mammalian mu, delta, and kappa opioid receptors were not selective in behavioral and binding studies in amphibians. Three opioid-like receptor cDNAs were cloned and sequenced from amphibian brain tissues and are orthologs to mammalian mu, delta, and kappa opioid receptors. Bioinformatics analysis of the three types of opioid receptor cDNAs from all vertebrate species with full datasets gave a pattern of the molecular evolution of opioid receptors marked by the divergence of mu, delta, and kappa opioid receptor sequences during vertebrate evolution. This divergence in receptor amino acid sequence in later-evolved vertebrates underlies the hypothesis that opioid receptors are more type-selective in mammals than in nonmammalian vertebrates. The apparent order of receptor type evolution is kappa, then delta, and, most recently, the mu opioid receptor. Finally, novel bioinformatics analyses suggest that conserved extracellular receptor domains determine the type selectivity of vertebrate opioid receptors.

Original languageEnglish
Pages (from-to)204-215
Number of pages12
JournalBrain Research Reviews
Volume46
Issue number2
DOIs
StatePublished - Oct 2004

Keywords

  • Analgesia
  • Bioinformatics
  • Domain
  • Selectivity

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