Genetic behavioral screen (in worm!!!) identifies an ophan anti-opioid system

In keeping with our gene-environment interactions theme, these GEITP pages are interested in genes (from any organism) that might “receive information” from any “environmental signal.” In today’s article [see attached], the worm genome (Caenorhabditis elegans, nematode; a roundworm) is the model animal being used to screen — and “an opioid” is the environmental signal. G protein–coupled receptors (GPCRs) constitute the largest class of cell-surface receptors; GPCRs mediate sensory perception and cellular communication by means of hormones and neurotransmitters. These GPCRs function in various clinical diseases, and therefore they are prominent drug targets.

Research over the past several decades has seen amazing progress in understanding the molecular mechanisms of GPCR-signaling, stemming from identification of key components — including G protein subunits, b-arrestins, downstream effectors, and regulatory proteins. Most of these components have been discovered serendipitously, leaving open many critical questions about GPCR organization and function. Many receptors are considered “orphan” (i.e. no known ligand that binds, and with poorly understood biology and unclear roles in cellular signaling); mechanisms that generate diverse physiological effects are not understood. Moreover, how each individual GPCR regulates signaling in response to changes in the environment or circuit activity remains unclear.

Insufficient understanding of GPCR-signaling, of course, hampers targeting them with the appropriate drug in a safe and effective manner; this is well illustrated by opioid analgesics that act on the mu (m)-opioid receptor (MOR) and offer incomparable efficacy for pain management (which is what causes so many opioid addicts). However, opioid drugs have substantial liabilities — including dependence, tolerance, and side-effects. Extensive investigation of MOR pharmacology led to the concept that activated MOR triggers distinct signaling-events that differentially control various physiological reactions; as a result, identification of molecules that control MOR-signaling in endogenous neural circuits remains critical and could provide new pharmacological targets for increasing the efficacy and safety of opioid analgesics.

Opioid stimulation of MOR affects the central nervous system and produces effects that are inherently behavioral in nature. Thus, screens for modulators of opioid-signaling that use behavior as an ultimate read-out — could accelerate the relevance and translatability of discoveries. Fortunately, GPCR-signaling is highly conserved and has been studied across mammalian and invertebrate (e.g. the nematode) model systems. Genetic studies in Caenorhabditis elegans have allowed discovery and evaluation of many conserved players in GPCR-signaling, elucidating their roles in neural circuits. Furthermore, transgenic expression of mammalian GPCRs is known to alter the behavior of C. elegans, and these heterologous GPCRs can be desensitized in response to ligands. C. elegans also has an opioid-like system that controls feeding behavior and responses to noxious painful stimuli; these considerations prompted the authors to develop a transgenic C. elegans platform that they used in an unbiased forward-genetics screen for regulators of MOR-controlled behavior.

Using forward genetics in the worm, authors [see attached article] therefore identified an evolutionarily conserved orphan receptor, GPR139, with anti-opioid activity. GPR139 is co-expressed with MOR in opioid-sensitive brain circuits, binds to MOR, and inhibits signaling to heterotrimeric guanine nucleotide–binding proteins (G proteins). Ablation of the Gpr139 gene in mice — enhanced opioid-induced inhibition of neuronal firing to modulate morphine-induced analgesia, reward, and withdrawal. Thus, GPR139 could be a useful target for increasing opioid safety. These data demonstrate the potential of C. elegans as a scalable platform for genetic discovery of G protein–coupled receptor signaling circuits.



· Science Sept 2019; 365: 1267-1273

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