Agonists of the mu opioid receptor (MOR) are currently the most effective pain-relieving drugs, but opioid abuse and overdose continues to plague the USA. The long history of clinical opioid use provides evidence that these drugs differ in underlying biology. For instance, a lack of complete cross tolerance between analgesics and that specific side effects are more intense in response to one drug compared to another (Smith and Peppin, 2014) suggests that they do not function identically at the level of neural circuits. Further, recent animal studies demonstrate a lack of cross tolerance between morphine and fentanyl when these drugs are microinjected directly into the pain modulation circuit (Bobeck et al., 2012, 2019). Ligand bias is the current, dominant hypothesis for how this might happen, however this idea is at best incomplete (Austin Zamarripa et al., 2018; Conibear and Kelly, 2019; Yudin and Rohacs, 2019). The overarching objective of this proposal is to lay a new groundwork for understanding these compounds using responses in neurons from the circuits that contribute to the different in vivo effects of opioids. I have previously demonstrated with whole cell recordings from brain slices, neurons in the ventral tegmental area (VTA) show independent responding to delta opioid receptor agonists that lack in vivo cross tolerance and differentially affect alcohol consumption (Jiang et al., 1991; Mitchell et al., 2014; Margolis et al., 2017). This study provides proof of concept observations that electrophysiology can be used to detect differences in pharmacologies. To enable profiling and comparison of a larger number of molecules, here I propose to use multielectrode extracellular recording from acute brain slices to greatly increase the number of neurons we can record from, thereby increasing the statistical power of the approach. We will investigate the neuronal responses to 4 clinical compounds (morphine, fentanyl, oxycodone, and buprenorphine) and use DAMGO, a highly selective MOR agonist used widely in preclinical studies, as an additional comparator. The majority of neurons in brain regions in the reward circuit (VTA), pain-aversion circuit (habenula), and respiration circuit (Pre-Btzinger Complex) fire spontaneously in acute brain slices, and these brain regions also highly express the MOR. Therefore, we can use this higher throughput approach to measure potency and efficacy of different MOR agonists in each of these brain regions, as well as compare the responses to sequential application of each ligand in individual neurons in each brain region. Further, we will compare results between nave animals and those made morphine dependent. By improving our understanding of opioid responses of individual neurons in the specific circuits that underly in vivo opioid effects, this work will (1) demonstrate the viability of using this approach to characterize compounds quickly and (2) identify biological variation of MOR function that will enable more effective therapeutic development for clinical problems that involve opioid signaling, including opioid use disorder, alcohol use disorder, and tolerance to pain medications.
Behavioral preclinical studies and clinical experience with mu opioid receptor agonists indicate that potency and pharmacokinetics are not sufficient to explain various phemonema, such as less-than-expected cross- tolerance and uncorrelated dose response relationships for analgesia, reward or ?high?, constipation, and respiratory depression. Investigating the ways responses to these different MOR agonists diverge in individual neurons will enable new understanding of the cellular mechanisms underlying these differences. Our focus is on three brain structures that are highly sensitive to mu opioid receptor activation: the ventral tegmental area, a critical site for opioid reward; the habenula, which mediates the aversiveness of pain; and the Pre-Btzinger complex, which controls respiration.
