Convergent, functionally independent signaling by mu and delta opioid receptors in hippocampal parvalbumin interneurons

  1. Xinyi Jenny He
  2. Janki Patel
  3. Connor E Weiss
  4. Xiang Ma
  5. Brenda L Bloodgood
  6. Matthew R Banghart  Is a corresponding author
  1. Division of Biological Sciences, Neurobiology Section, University of California, San Diego, United States

Abstract

Functional interactions between G protein-coupled receptors are poised to enhance neuronal sensitivity to neuromodulators and therapeutic drugs. Mu and delta opioid receptors (MORs and DORs) can interact when overexpressed in the same cells, but whether co-expression of endogenous MORs and DORs in neurons leads to functional interactions is unclear. Here, in mice, we show that both MORs and DORs inhibit parvalbumin-expressing basket cells (PV-BCs) in hippocampal CA1 through partially occlusive signaling pathways that terminate on somato-dendritic potassium channels and presynaptic calcium channels. Using photoactivatable opioid neuropeptides, we find that DORs dominate the response to enkephalin in terms of both ligand sensitivity and kinetics, which may be due to relatively low expression levels of MOR. Opioid-activated potassium channels do not show heterologous desensitization, indicating that MORs and DORs signal independently. In a direct test for heteromeric functional interactions, the DOR antagonist TIPP-Psi does not alter the kinetics or potency of either the potassium channel or synaptic responses to photorelease of the MOR agonist [d-Ala2, NMe-Phe4, Gly-ol5]enkephalin (DAMGO). Thus, aside from largely redundant and convergent signaling, MORs and DORs do not functionally interact in PV-BCs in a way that impacts somato-dendritic potassium currents or synaptic transmission. These findings imply that cross-talk between MORs and DORs, either in the form of physical interactions or synergistic intracellular signaling, is not a preordained outcome of co-expression in neurons.

Editor's evaluation

This study uses novel photoactivatable opioid ligands and neurophysiological recordings in brain slices to investigate the functional interactions between the delta and mu opioid receptors in parvalbumin-expressing hippocampal interneurons. The authors demonstrate that delta and mu opioid receptors modulate potassium channels without causing heterologous desensitization, indicating that these two opioid receptor types signal independently. These findings extend previous studies by establishing the mechanisms of function of mu and delta opioid receptors in forebrain inhibitory interneurons co-expressing these receptors.

https://doi.org/10.7554/eLife.69746.sa0

Introduction

G protein-coupled receptors (GPCRs) regulate cellular physiology through a diverse but limited number of intracellular signaling pathways. In neurons, signaling through multiple GPCRs expressed in the same cell can converge on the same molecular effectors (e.g. ion channels) to regulate neurophysiological properties such as cellular excitability and neurotransmitter release. Although GPCRs that engage the same family of G proteins (Gαs, Gαi/o, or Gαq) are poised to functionally interact through convergent biochemical signaling, it is not clear a priori whether such interactions would actually occur. Examples of interactions include functional synergy, when activation of one receptor subtype enhances activity at the other, or reciprocal occlusion, when the receptor subtypes compete for the same pool of effector molecules. Alternatively, GPCRs have been proposed to functionally interact through the formation of receptor heteromers, such that conformational changes due to ligand binding at one receptor shape agonist-driven signaling at the other.

Mu and delta opioid receptors (MORs and DORs) are both Gαi/o-coupled GPCRs that are activated by endogenous opioid neuropeptides such as enkephalin to suppress neuronal excitability and synaptic output. MORs are the primary target of widely used opiate analgesics (e.g. morphine, fentanyl) that are plagued by tolerance, high potential for addiction, and a propensity to cause respiratory depression. MORs and DORs have been proposed to functionally interact such that DOR-targeting drugs could reduce the clinical liabilities of MOR-targeting analgesics. For example, either pharmacological suppression or genetic removal of DOR attenuates morphine tolerance (Abdelhamid et al., 1991; Sánchez-Blázquez et al., 1997; Zhu et al., 1999). Furthermore, co-administration of MOR and DOR agonists produces spinal, supraspinal, and peripheral analgesic synergy (Porreca et al., 1987; Schuster et al., 2015; Bruce et al., 2019). In contrast, antagonism of one receptor has been reported to enhance agonist-driven activity at the other receptor in assays using heterologous receptor expression. These observations have been interpreted to support the existence of MOR/DOR heteromers that interact through direct allosteric coupling (Fujita et al., 2015; Cahill and Ong, 2018). MOR/DOR heteromers have been specifically implicated as potential therapeutic targets for the treatment of pain, as intrathecal co-administration of the DOR-selective antagonist TIPP-Psi with morphine produces stronger analgesia than morphine alone (Gomes et al., 2004). Due to the clinical potential of therapeutic approaches that simultaneously engage MORs and DORs, understanding the mechanisms that underlie their potential for functional interactions is of great importance.

Relatively few studies have investigated functional interactions between endogenous MORs and DORs using sensitive measurements of cellular physiology with the single-cell resolution required to implicate cell-autonomous interactions, as opposed to circuit-level effects. In recordings from neurons in the nucleus raphe magnus after upregulation of DORs in response to chronic morphine treatment, MORs and DORs were found to synergistically suppress inhibitory synaptic transmission through a PKA-dependent pathway, but evidence of heteromers was not observed (Zhang and Pan, 2010). Also supporting functionally independent signaling, using both electrophysiological and receptor trafficking experiments, a more recent study of spinal dorsal horn neurons that co-express MOR and DOR did not find evidence for co-internalization or co-degradation after intrathecal administration of either the DOR-selective agonist SNC80 or the MOR-selective agonist [d-Ala2, NMe-Phe4, Gly-ol5]enkephalin (DAMGO) (Wang et al., 2018). In contrast, recordings from ventral tegmental area neurons suggested MOR/DOR interactions consistent with heteromer formation (Margolis et al., 2017). In that study, TIPP-Psi enhanced DAMGO-evoked membrane potential hyperpolarization, and the MOR antagonist CTOP enhanced hyperpolarization evoked by the DOR agonists DPDPE and deltorphin II. However, at least some of the recordings were from dopamine neurons, which have been shown not to express Oprm1 mRNA (Galaj et al., 2020). Thus, in naïve mice, unequivocal evidence for functional interactions between endogenous MORs and DORs in the same neurons, and in particular, for the existence of MOR/DOR heteromers that impact neuronal physiology, is lacking.

In some brain regions, including the hippocampus, MORs and DORs are established to be co-expressed in the same neurons, such that the receptors and their downstream intracellular signaling pathways are poised to interact (Chieng et al., 2006; Erbs et al., 2015). In the hippocampus, activation of MORs in GABA neurons contributes to stress-induced memory deficits (Shi et al., 2020), whereas DORs may contribute to spatial contextual cue-related memory retrieval (Le Merrer et al., 2011; Le Merrer et al., 2012; Le Merrer et al., 2013). Recently, we reported that MORs and DORs both contribute to opioid-mediated suppression of perisomatic inhibition in the CA1 region of hippocampus, consistent with previous studies of MOR and DOR modulation of synaptic transmission (Glickfeld et al., 2008; Piskorowski and Chevaleyre, 2013; Banghart et al., 2018). In fact, MORs and DORs are well established to regulate inhibitory synaptic transmission in CA1 (Zieglgänsberger et al., 1979; Nicoll et al., 1980; Lupica and Dunwiddie, 1991; Lupica et al., 1992; Lupica, 1995; Svoboda and Lupica, 1998; Svoboda et al., 1999; Rezaï et al., 2012). Although a substantial body of work indicates co-expression of MOR and DOR in CA1 parvalbumin basket cells (PV-BCs), which are a primary source of perisomatic inhibition (Stumm et al., 2004; Erbs et al., 2012; Faget et al., 2012; Yao et al., 2021), a direct comparison of their neurophysiological actions has not been conducted.

In this study, we explored potential interactions between MORs and DORs in CA1 PV-BCs using recordings from hippocampal slices. In order to obtain precise and sensitive measures of receptor function, we optically probed native MORs and DORs using photoactivatable (caged) opioid neuropeptides (Banghart and Sabatini, 2012; Banghart et al., 2018). Using this approach, we found that MORs and DORs activate partially overlapping pools of somato-dendritic potassium channels in PV-BCs, and suppress synaptic output from PV-BCs in a mutually occlusive manner. Despite their co-expression and functional redundancy, we did not find evidence of synergy or for heteromers, indicating that MOR and DOR signal in a parallel, functionally independent manner in PV-BCs.

Results

Occlusive suppression of hippocampal perisomatic inhibition by MORs and DORs

We first confirmed that both MORs and DORs are co-expressed in PV-BCs using fluorescence in situ hybridization, which revealed that 78% (171/218) of Pvalb mRNA-containing neurons with cell bodies in and around stratum pyramidale contain both Oprm1 and Oprd1 mRNA (Figure 1—figure supplement 1A, B). To determine if both MORs and DORs are functional in PV-BCs, we virally expressed the light-gated cation channel Chronos in a Cre recombinase-dependent manner in the CA1 region of PvalbCre mice and measured the effects of the selective MOR and DOR agonists DAMGO and SNC162, respectively, on light-evoked synaptic transmission using electrophysiological recordings from pyramidal cells (PCs) in acute hippocampal slices (Klapoetke et al., 2014). We chose SNC162 due to its exceptional selectivity for DOR over MOR (Knapp et al., 1996). To maximize the relative contribution of perisomatic inhibition from PV basket cells, as opposed to dendrite-targeting PV bistratified cells, we restricted the area of illumination to a small region of stratum pyramidale around the recorded PC (Figure 1A). Bath perfusion of either DAMGO (1 μM) or SNC162 (1 μM) strongly reduced the optically evoked IPSC (oIPSC) to a similar degree (Figure 1B–D). Sequential drug application only slightly increased the degree of suppression compared to either drug alone (DAMGO: 0.69 ± 0.05, n = 9 cells; SNC162: 0.70 ± 0.05, n = 9 cells; both: 0.76 ± 0.03, n = 18 cells; no significant differences, ordinary one-way ANOVA) (Figure 1D, Figure 1—figure supplement 1F). In both cases, application of pairs of optical stimuli (50 ms apart) revealed small increases in the paired-pulse ratio (PPR) in the presence of the opioid agonist, consistent with a presynaptic mechanism of action for the opioid receptor (BL: 0.47 ± 0.08; DAMGO: 0.68 ± 0.14; n = 9 pairs; p = 0.0078, Wilcoxon matched-pairs signed rank test; BL: 0.42 ± 0.05; SNC162: 0.56 ± 0.07; n = 8 pairs; p = 0.016, Wilcoxon matched-pairs signed rank test) (Figure 1E). With sustained application, both the effects of DAMGO and SNC162 appeared to desensitize slightly, with DAMGO showing greater desensitization (Figure 1—figure supplement 1H, I) (DAMGOearly: 0.69 ± 0.05; DAMGOlate: 0.44 ± 0.07; n = 9 pairs; p = 0.0038, paired t-test; SNC162early: 0.70 ± 0.05; SNC162late: 0.61 ± 0.06; n = 9 pairs; p = 0.048, paired t-test). These results reveal that both MORs and DORs suppress the output of PV-BCs in a mutually occlusive manner.

Figure 1 with 1 supplement see all
Electrophysiological recordings of opioid-sensitive synaptic output from hippocampal parvalbumin basket cells.

(A) Schematic of the experimental configuration for recording optogenetically evoked inhibitory synaptic transmission in PV-Cre mice. (B) Representative optically evoked IPSC (oIPSC) pairs (50 ms interval) recorded from a pyramidal cell. Black traces are the average of six baseline sweeps, and colored traces are the average of six sweeps after addition of either [d-Ala2, NMe-Phe4, Gly-ol5]enkephalin (DAMGO) (1 µM, blue) or SNC162 (1 µM, red). Scale bars: x = 40 ms, y = 100 pA. (C) Baseline-normalized, average oIPSC amplitude over time during bath application of DAMGO (n = 9 cells from six mice) or SNC162 (n = 9 cells from seven mice). (D) Summary data of double flow-in experiments, comparing oIPSC suppression by DAMGO or SNC162 alone, followed by the other drug. (E) oIPSC paired-pulse ratios (Peak 2/Peak 1), before (baseline, BL) and after drug addition. (F) Schematic of the experimental configuration for recording electrically evoked inhibitory synaptic transmission in wild-type mice. (G) Representative electrically evoked IPSC (eIPSC) pairs (50 ms interval) recorded from a pyramidal cell (as in B). Scale bars: x = 40 ms, y = 200 pA. (H) Baseline-normalized, average eIPSC amplitude over time during bath application of DAMGO (n = 15 cells from 13 mice) or SNC162 (n = 9 cells from five mice). (I) Summary data of double flow-in experiments with electrical stimulation (as in D). (J) eIPSC paired-pulse ratios (Peak 2/Peak 1), before and after drug addition.

Figure 1—source data 1

IPSC suppression, paired pulse ratios, and time courses for DAMGO and SNC162.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig1-data1-v3.xlsx

To avoid complications due to optical cross-talk between optogenetic tools and photoactivatable peptides in subsequent experiments, we established an electrical stimulation protocol for preferential activation of PV-BC terminals by placing a small bipolar stimulating electrode in stratum pyramidale immediately adjacent to the recorded PC (Figure 1F). Recordings were made from PCs near stratum oriens, as these have been shown to receive BC input that is biased toward PV-BCs, as opposed to CCK-BCs (Lee et al., 2014). Whereas fast-spiking, presumably PV-BCs have been shown to be opioid, but not cannabinoid sensitive, output from regular-spiking CCK-BCs is suppressed by CB1R, but not MOR activation (Glickfeld et al., 2008). Consistent with only a minor contribution to the electrically evoked IPSC (eIPSC) from CB1R-expressing CCK-BCs, bath application of the CB1R agonist WIN55,212 (1 μM) resulted in only modest eIPSC suppression (0.25 ± 0.07, n = 8 cells), and application of WIN55,212 in the presence of DAMGO produced only slightly more suppression than DAMGO alone, although this effect was not significant, suggesting some occlusion (DAMGO: 0.67 ± 0.02, n = 12 cells; WIN55,212 + DAMGO: 0.79 ± 0.03, n = 8 cells; p = 0.14, ordinary one-way ANOVA with Tukey’s multiple comparison test) (Figure 1—figure supplement 1C-E). Under these electrical stimulation conditions, DAMGO and SNC162 again suppressed the eIPSC to a similar degree, with DAMGO, but not SNC162, producing slight desensitization (Figure 1—figure supplement 1H) (DAMGOearly: 0.70 ± 0.03; DAMGOlate: 0.41 ± 0.05; n = 13 pairs; p < 0.0001, paired t-test; SNC162early: 0.63 ± 0.06; SNC162late: 0.57 ± 0.05; n = 9 pairs; p = 0.10, paired t-test). For both eIPSCs and oIPSCs, DAMGO resulted in more desensitization than SNC162 (Figure 1—figure supplement 1I) (eIPSC DAMGO: 0.28 ± 0.04; oIPSC DAMGO: 0.25 ± 0.06; eIPSC SNC162: 0.07 ± 0.04; oIPSC SNC162: 0.09 ± 0.04; Skillings-Mack non-parametric test for grouped data (Mack and Skillings, 1980), p < 0.0001 for column effects (DAMGO vs. SNC162), p = 0.13 for row effects (eIPSC vs. oIPSC)). As with optogenetic stimulation, DAMGO and SNC162 exhibited strong mutual occlusion of the eIPSC (DAMGO: 0.69 ± 0.02, n = 14 cells; SNC162: 0.63 ± 0.06, n = 9 cells; both: 0.75 ± 0.04, n = 14 cells; no significant differences, ordinary one-way ANOVA), and a small increase in PPR was produced by DAMGO but not SNC162 (BL: 0.67 ± 0.03; DAMGO: 0.80 ± 0.04; n = 11 pairs; p = 0.019, Wilcoxon matched-pairs signed rank test; BL: 0.65 ± 0.02; SNC162: 0.77 ± 0.04; n = 9 pairs; p = 0.055, Wilcoxon matched-pairs signed rank test) (Figure 1F–J, Figure 1—figure supplement 1F). Although it is possible that an opioid-sensitive population of non-PV interneurons contributes to the opioid-sensitive component of the eIPSC, the effects of DAMGO and SNC162 on the eIPSC and oIPSC were indistinct (no significant difference, two-way ANOVA) (Figure 1—figure supplement 1G).

MOR and DOR are thought to exhibit similar affinity for enkephalin, but how this translates to ligand efficacy at native receptors in neurons is not clear. In addition, receptor signaling kinetics could prove to be a sensitive means of detecting functional interactions. To compare the ligand sensitivity and receptor signaling kinetics of MORs and DORs, we turned to photoactivatable derivatives of the MOR and DOR agonist [Leu5]-enkephalin (LE) (Figure 2A, top) (Banghart and Sabatini, 2012). For quantitative pharmacology, we chose to use N-MNVOC-LE, which is highly inactive at both DOR and MOR (Banghart et al., 2018). In the presence of N-MNVOC-LE (6 µM), which is optimized for simultaneous activation of MORs and DORs, application of a strong 5 ms UV light flash 2 s prior to an eIPSC produced a rapid, transient suppression of the eIPSC that recovered within 1–2 min (Figure 2A and B). Varying UV light intensity in a graded fashion allowed us to rapidly obtain power-response curves within a single recording. To assess the potency of LE at MORs and DORs, and the relative contributions of the receptors to the eIPSC suppression by LE, we recorded power-response curves in the absence and presence of the MOR- and DOR-selective antagonists CTOP (1 μM) and TIPP-Psi (1 μM), respectively (Figure 2C). We chose CTOP over its analog CTAP due to its higher selectivity for MORs. Whereas LE uncaging at the highest light power (84 mW) in the absence of opioid antagonists suppressed synaptic transmission by 63% ± 4%, activation of MORs or DORs alone, which were isolated by antagonizing with TIPP-Psi or CTOP, respectively, suppressed synaptic output by ~40% each. Although the extent of suppression achieved with caged LE was somewhat less than with bath application (Figure 1I), the relative contributions of MORs and DORs were similar in both experiments and consistent with mutual occlusion. The power-response curve revealed that LE exhibits approximately threefold greater potency for DORs than MORs in regulating perisomatic inhibition (EC50 values in the absence [black, 3.28 ± 0.47 mW] and presence of either CTOP [red, 2.29 ± 0.61 mW] or TIPP-Psi [blue, 9.30 ± 1.40 mW]). Moreover, DOR activation largely accounts for the actions of LE in the absence of antagonists. This could reflect greater affinity for DORs, or more efficacious signaling by DORs than MORs (Figure 2D).

Characterization of the potency and kinetics of synaptic modulation by [Leu5]-enkephalin (LE) at mu (MOR) and delta opioid receptors (DOR) using caged peptides.

(A) Left: Schematic of the experimental configuration for photo-uncaging of opioid neuropeptides while recording electrically evoked inhibitory synaptic transmission in wild-type mice. Right: Schematic of photoreleasing LE (cyan) from N-MNVOC-LE or CYLE (cyan with purple caging group) in the presence of selective antagonists to isolate its action on either MOR (blue, in TIPP-Psi) or DOR (red, in CTOP). (B) Example recording showing graded suppression of inhibitory synaptic transmission by uncaging N-MNVOC-LE at various light intensities. Inset: Example electrically evoked IPSC (eIPSCs) before (black) and after LE uncaging at each light intensity. Scale bars: x = 20 ms, y = 100 pA. (C) Linear optical power-response curves of eIPSC suppression as a function of light intensity, in the absence (black, n = 6–12 cells per laser intensity) and presence of either CTOP (red, n = 5–8 cells) or TIPP-Psi (blue, n = 4–10 cells). (D) Logarithmic optical power-response curves of the data in (C) normalized to the maximal eIPSC suppression observed in each condition. (E) Representative recording from a pyramidal cell demonstrating rapid suppression of eIPSC amplitude in response to photoactivation of CYLE during 10 Hz trains of electrical stimuli. Purple arrow represents CYLE uncaging at 2 s into the 10 Hz train. Outward stimulus artifacts are removed for clarity. Scale bars: x = 1 s, y = 100 pA. (F) Average, baseline subtracted and baseline-normalized eIPSC amplitude showing the kinetics of synaptic suppression with electrical stimulation at 10 Hz in the absence (artificial cerebrospinal fluid [ACSF], n = 9 cells from six mice) and presence of either CTOP (n = 12 cells from seven mice) or TIPP-Psi (n = 8 cells from six mice). (G) Time constants of synaptic suppression in response to CYLE photoactivation with an 84 mW light flash at the indicated frequencies of synaptic stimulation. At 20 Hz, the time constant in TIPP-Psi was significantly greater than the time constant without any antagonists. (H) Plot of eIPSC suppression as a function of synaptic stimulation frequency.

Figure 2—source data 1

Power-response curves and onset kinetics at presynaptic MOR and DOR.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig2-data1-v3.xlsx

We evaluated receptor signaling kinetics using the photoactivatable LE derivative CYLE, which photolyzes within tens of microseconds, such that receptor activation is rate-limiting (Banghart and Sabatini, 2012; Banghart et al., 2018). In order to sample synaptic transmission at frequencies sufficient to resolve receptor signaling kinetics, we drove eIPSCs in 5 s bouts at 10, 20, and 50 Hz, and photolyzed CYLE (6 µM) after synaptic depression had stabilized to a steady state (Figure 2E). To obtain the time constants of synaptic suppression for each receptor, we repeated this experiment in the presence of the selective antagonists and fit the post-flash eIPSC amplitudes with a single exponential function (Figure 2F). The time constants we obtained for each pharmacological condition were similar for all three stimulus frequencies (Figure 2G). At 20 Hz, DOR (CTOP at 20 Hz, tau = 419 ± 105 ms, n = 11 cells) exhibited kinetics indistinct from the drug-free condition (artificial cerebrospinal fluid [ACSF] at 20 Hz, tau = 259 ± 30 ms, n = 8 cells), but the time constant of MOR-mediated suppression was surprisingly slow (TIPP-Psi at 20 Hz, tau = 683 ± 36 ms, n = 6 cells; p = 0.0046, Kruskal-Wallis test with Dunn’s multiple comparisons). At other frequencies, although the MOR kinetics trended toward slower time constants, statistical significance was not observed. We also observed that the extent of eIPSC suppression correlated inversely with the frequency of synaptic stimulation, and that this was most pronounced in the absence of antagonists (Figure 2H).

Together, these results suggest that MOR and DOR suppress output from overlapping populations of PV-BC presynaptic terminals, and that this suppression is dominated by DOR, both in terms of sensitivity to LE and response kinetics.

MORs and DORs suppress GABA release by inhibiting voltage-sensitive Ca2+ channels

At least two mechanisms of presynaptic inhibition by Gαi/o-coupled GPCRs have been established, but the pathways engaged by opioid receptors in PV-BCs are not known. One potential mechanism involves the inhibition of voltage-sensitive calcium channels (VSCCs) by Gβγ proteins (Bean, 1989), whereas the other involves direct suppression of SNARE proteins by Gβγ binding to the C-terminus of SNAP25 (Blackmer et al., 2001; Gerachshenko et al., 2005; Zurawski, 2019; Hamm and Alford, 2019). The observed frequency-dependent synaptic suppression is consistent with both mechanisms, as Gβγ binding to VSCCs is reversed by strong depolarization, and elevated Ca2+ facilitates displacement of Gβγ from the SNARE complex by Ca2+-bound synaptotagmin (Park and Dunlap, 1998; Brody and Yue, 2000; Yoon et al., 2007).

To ask if MOR and DOR inhibit presynaptic VSCCs in PV-BCs, we imaged action potential (AP)-induced Ca2+ transients in presynaptic boutons of PV-BCs using two-photon laser scanning microscopy. PV-BCs were targeted for whole-cell current clamp recordings in PvalbCre/Rosa26-lsl-tdTomato (Ai14) mice with the small molecule Ca2+ indicator Fluo5F included in the recording pipette (Figure 3A). Line scans across putative boutons were obtained while triggering either one or five APs, before and after bath application of DAMGO, SNC162, or both drugs together (Figure 3B).

Axonal calcium imaging reveals that both mu and delta opioid receptors suppress presynaptic voltage-sensitive calcium channels.

(A) Two-photon image of a tdTomato-expressing basket cell filled with 30 µM Alexa 594 and 300 µM Fluo-5F in a brain slice taken from a PV-Cre; tdTom mouse. Scale bar: 50 μm. Inset shows the two axonal boutons where the line scan was carried out, with the orientation of the line scan indicated by the arrow. Scale bar: 5 μm. (B) Example of either a single action potential (AP) (left) or five APs (right) triggered in the cell body (top), and the resulting averaged, presynaptic Ca2+ transients, before and after application of DAMGO (top, blue, n = 8 cells, 16 boutons), SNC162 (red bottom, n = 7 cells, 14 boutons), and both drugs (top and bottom, purple). The transients are measured as the change in green signal (ΔG) , divided by G in saturating Ca2+ conditions (Gsat). Scale bars: top, 50 mV; bottom, x = 100 ms, y = 0.01 (left) or 0.02 (right) (ΔG/Gsat. (C) Summary of peak Ca2+ transients for DAMGO application in response to one AP (left) or five APs (right). One AP: BL 0.014 ± 0.001; DAMGO 0.011 ± 0.001; DAMGO+ SNC162 0.010 ± 0.001 (p = 0.042 and p = 0.0001, n = 10 pairs, Friedman test with Dunn’s multiple comparisons) five AP: BL 0.032 ± 0.004; DAMGO 0.025 ± 0.002, DAMGO+ SNC162 0.022 ± 0.003 (p = 0.076 and p = 0.0004, n = 10 pairs). (D) Summary of peak Ca2+ transients for SNC162 application in response to one AP (left) or five APs (right). One AP: BL 0.014 ± 0.002; SNC162 0.010 ± 0.002; SNC162+ DAMGO 0.008 ± 0.001 (p = 0.014 and p < 0.0001, n = 14 pairs, Friedman test with Dunn’s multiple comparisons). Five AP: BL 0.039 ± 0.004; SNC162 0.029 ± 0.003; SNC162+ DAMGO 0.023 ± 0.002 (p = 0.014 and p < 0.0001, n = 14 pairs).

Figure 3—source data 1

Ca2+ transient peaks with and without DAMGO and SNC162.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig3-data1-v3.xlsx

Individually, DAMGO and SNC162 both caused an ~30% reduction in the peak ΔG/Gsat evoked by either stimulation protocol (DAMGO 27.27% for one AP, 17.73% for five APs, SNC162 31.18% for one AP, 26.55% for five APs). When DAMGO and SNC162 were applied together, these presynaptic Ca2+ transients were suppressed by ~40%, on average (DAMGO then SNC162 40.95% for one AP, 38.92% for five APs, SNC162 then DAMGO 46.08% for one AP, 40.85% for five APs) (Figure 3C and D). Under the conditions employed, peak ΔG/Gsat is linearly correlated with Ca2+ concentration (Higley and Sabatini, 2008). Given the nonlinear Ca2+ dependence of vesicular fusion, a 30% reduction in presynaptic Ca2+ is consistent with the strong suppression of PV-BC IPSCs by MORs and DORs (Wu and Saggau, 1997). These results indicate that the inhibition of VSCCs by both MORs and DORs is the most likely mechanism accounting for their effects on inhibitory transmission. Furthermore, the marginal effect of adding a second drug suggests convergence on the same pool of VSCCs.

Enkephalin generates large outward somato-dendritic currents in PV-BCs primarily through DORs rather than MORs

i/o-coupled GPCRs, including both MORs and DORs, often hyperpolarize neurons by activating G protein-coupled inward rectifier K+ (GIRK) channels, as well as voltage-gated K+ channels, or by suppressing hyperpolarization-gated cyclic nucleotide (HCN) channels (Williams et al., 1982; North et al., 1987; Wimpey and Chavkin, 1991; Svoboda and Lupica, 1998). Although MORs were previously reported to activate outward currents in the somato-dendritic compartment of fast-spiking CA1 BCs, the role of DORs has not been explored (Glickfeld et al., 2008). To address this, we performed voltage clamp recordings of opioid-evoked currents in tdTom-labeled cells in PvalbCre/Rosa26-lsl-tdTomato mice (Figure 4A). At a holding potential of –55 mV, N-MNVOC-LE photoactivation using strong (84 mW) light flashes applied to the soma and proximal dendrites of the recorded neuron evoked rapidly rising outward currents that decayed over ~1 min, similar to previous observations in locus coeruleus (Figure 4B and C; Banghart and Sabatini, 2012). Surprisingly, blocking MORs with CTOP had no measurable effect on the light-evoked current (ACSF: 81.7 ± 9.6 pA, n = 9 cells; CTOP: 82.5 ± 12.8 pA, n = 10 cells; not significant). In contrast, blocking DOR with TIPP-Psi greatly reduced the current amplitude (TIPP-Psi: 26.4 ± 4.8 pA, n = 11 cells; p = 0.016), and addition of both drugs completely abolished it (CTOP + TIPP-Psi: 7.1 ± 0.09 pA, n = 5 cells; p = 0.0009; Kruskal-Wallis test with Dunn’s multiple comparisons). Power-response curves in the presence of each antagonist revealed a larger DOR-mediated than MOR-mediated current (Figure 4D). Similar to our observations with presynaptic receptors, LE exhibited greater potency at DORs than MORs in generating outward currents (EC50 values of ACSF: 17.55 ± 2.98 mW, CTOP: 7.59 ± 1.26 mW, TIPP-Psi: 28.03 ± 7.14 mW) (Figure 4E). Assessment of current activation kinetics with CYLE (6 µM) revealed that, whereas DOR-mediated currents activated with kinetics similar to the MOR currents previously observed in LC neurons, somato-dendritic MOR currents in CA1 PV-BCs activated threefold more slowly, similar to the rate observed for presynaptic MOR in these neurons (ACSF: 275.9 ± 35.7 ms, n = 11 cells; CTOP: 395.3 ± 109.6 ms, n = 6 cells; TIPP-Psi: 844.1 ± 105.2 ms, n = 9 cells; p = 0.019, Kruskal-Wallis test with Dunn’s multiple comparisons) (Figure 4F and G; Ingram et al., 1997; Banghart and Sabatini, 2012). The small MOR-mediated currents, coupled with similarly slow signaling kinetics in both the presynaptic and somato-dendritic compartments, suggest that MOR signaling is relatively inefficient in CA1 PV-BCs.

Figure 4 with 1 supplement see all
Enkephalin evokes outward currents in CA1 parvalbumin (PV) interneurons through both mu and delta opioid receptors.

(A) Schematic of whole-cell voltage clamp recording configuration from PV interneurons with peptide uncaging. (B) Average outward currents evoked by photoactivation of N-MNVOC-LE (6 μM) with an 84 mW light flash in the absence (black, artificial cerebrospinal fluid [ACSF], n = 9 cells from five mice) and presence of mu and delta opioid receptor antagonists (red, CTOP, n = 10 cells from six mice; blue, TIPP-Psi, n = 11 cells from six mice; purple, CTOP+ TIPP-Psi, n = 5 cells from three mice). Scale bar: x = 5 s, y = 20 pA. (C) Summary of peak current amplitudes shown in B. (D) Linear optical power-response curve of peak current as a function of light intensity, in the absence (ACSF, black, n = 9 cells per laser intensity) and presence of either CTOP (red, n = 10 cells) or TIPP-Psi (blue, n = 11 cells). (E) Logarithmic optical power-response curves of the data in D normalized to the maximal peak current observed in each condition. (F) Rising phase of the average peak-normalized outward currents evoked by photoactivation of CYLE (6 μM) with an 84 mW light flash in the absence (black, ACSF, n = 11 cells from four mice) and presence of mu and delta opioid receptor antagonists (red, CTOP, n = 10 cells from four mice; blue, TIPP-Psi, n = 12 cells from four mice). (G) Time constants of current activation in response to photoactivation of CYLE from F. (H) Schematic of viral Cre-dependent mu opioid receptor over-expression in CA1 of PV-Cre mice. (I) Average outward currents evoked by photoactivation of CYLE by an 84 mW light flash in the presence of TIPP-Psi in either PV-Cre; tdTom mice (blue, data from B) or PV-Cre mice overexpressing the mu opioid receptor (purple, n = 8 cells from three mice). Scale bar: x = 10 s, y = 20 pA. (J) Summary of current amplitudes shown in I. (K) Time constants of current activation in response to photoactivation of CYLE.

Figure 4—source data 1

Power-response curves and onset kinetics at somato-dendritic MOR and DOR and MOR currents after overexpression.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig4-data1-v3.xlsx

To identify the ion channels underlying the MOR- and DOR-mediated outward currents, we applied the GIRK channel blocker Ba2+ (1 mM) while delivering strong light flashes to uncage N-MNVOC-LE, in the absence and presence of CTOP or TIPP-Psi. Consistent with a primary role of GIRK channels, Ba2+ blocked the majority, but notably not all, of the current mediated by both MOR and DOR to the same extent (Figure 4—figure supplement 1A, B) (Ba2+ in ACSF: 67.9% ± 4.9%, n = 8 cells; Ba2+ in CTOP: 59.6% ± 9.7%, n = 10 cells; Ba2+ in TIPP-Psi: 67.7% ± 9.1%, n = 11 cells; no significant differences, ordinary one-way ANOVA). At DORs, inclusion of the HCN channel blocker ZD7288 (1 µM) did not further block the current, suggesting the involvement of additional ion channels (Ba2+, ZD7288 in CTOP: 74.0% ± 5.6%, n = 9 cells; no significant difference, unpaired t-test). Due to the small size of the Ba2+-insensitive MOR-mediated current, we did not examine the effect of ZD7288 at MOR.

One possible explanation for the slow kinetics and low efficacy of MOR-mediated GIRK activation, as well as slow kinetics of synaptic suppression, is relatively low cell surface expression of MORs in comparison to DORs. In LC, reducing available surface MORs with a covalent antagonist leads to a reduction not only in the amplitude of MOR-mediated currents, but also a slowing of activation kinetics (Williams, 2014). To test this hypothesis, we virally overexpressed human MOR (hMOR) with an mCherry tag in PvalbCre mice and probed the resulting enhanced MOR signaling with CYLE in TIPP-Psi (Liu et al., 2021; Figure 4H1). As predicted, hMOR overexpression enhanced both the magnitude (57.5 ± 7.8 pA, n = 8 cells, p < 0.0001, unpaired t-test) and the kinetics (421.8 ± 68.7 ms, n = 8 cells, p = 0.0052, unpaired t-test) of the MOR-mediated current evoked with a strong light flash in comparison to those recorded from PvalbCre/Rosa26-lsl-tdTomato mice (Figure 4I–K). Both parameters correlated strongly with mCherry fluorescence as an indicator of expression level (peak: r = 0.8314, tau on: r = –0.8538, Pearson’s correlation coefficient) (Figure 4—figure supplement 1C, D). These results indicate that low MOR expression levels can account for the surprisingly modest effects of MOR activation in the somato-dendritic compartment of PV-BCs.

MORs and DORs do not functionally interact in CA1 PV-BCs

The apparent co-expression of MORs and DORs in the somato-dendritic compartment is a minimal requirement for functional interactions between receptors. We therefore asked if MORs and DORs undergo heterologous desensitization such that desensitization of one receptor perturbs the function of the other. We first confirmed that prolonged exposure to DAMGO (1 µM) caused desensitization of the resulting outward current (Figure 5A). After incubating slices in DAMGO for at least 10 min to maximally desensitize MOR, power-response curves were obtained in the presence of DAMGO, such that subsequent photorelease of LE would only activate DORs (Figure 5B). We compared these responses to those evoked in naïve slices bathed in the MOR antagonist CTOP. Indicative of a lack of heterologous desensitization, neither the efficacy nor potency of LE at DORs was affected by MOR desensitization (EC50 value of LE in the presence of DAMGO: 5.12 ± 0.38 mW, n = 9 cells; CTOP: 6.00 ± 0.42 mW, n = 7 cells) (Figure 5C and D). Similarly, prolonged exposure to deltorphin II (1 µM) caused desensitization of the outward current (Figure 5E). Desensitization of DORs using deltorphin II did not affect the ability of LE to elicit somato-dendritic outward currents compared to naïve slices bathed in the DOR antagonist TIPP-Psi (EC50 value of LE in the presence of Delt II: 13.47 ± 1.10 mW, n = 7 cells; TIPP-Psi: 13.47 ± 1.10 mW, n = 11 cells). These results reveal that MORs and DORs do not undergo heterologous desensitization in CA1 PV-BCs.

Somato-dendritic mu and delta opioid receptors do not exhibit heterologous desensitization.

(A) Average outward current evoked by sustained bath application of DAMGO (n = 9 cells from six mice). (B) Average outward currents evoked by photoactivation of N-MNVOC-LE either in the presence of CTOP (red, data from 4B) or in the presence of DAMGO, after desensitization (brick red, n = 9 cells from four mice). Scale bars: x = 10 s, y = 25 pA. (C) Linear optical power-response curve of peak current as a function of light intensity, in the presence of either CTOP (red, n = 10 cells, data from 4C) or DAMGO (brick red, n = 9 cells). (D) Logarithmic optical power-response curves of the data in (C) normalized to the maximal peak current observed in each condition. (E) Average outward current evoked by sustained bath application of deltorphin II (n = 12 cells from six mice). (F) Average outward currents evoked by photoactivation of N-MNVOC-LE either in the presence of TIPP-Psi (blue, data from 4B) or in the presence of deltorphin II, after desensitization (purple, n = 8 cells from four mice). Scale bars: x = 10 s, y = 10 pA. (G) Linear optical power-response curve of peak current as a function of light intensity, in the presence of either TIPP-Psi (blue, n = 11 cells, data from 4C) or deltorphin II (purple, n = 8 cells). (H) Logarithmic optical power-response curves of the data in F normalized to the maximal peak current observed in each condition.

Figure 5—source data 1

Somato-dendritic currents from DAMGO and Deltorphin II and power-response curves of uncaging-evoked currents.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig5-data1-v3.xlsx

MORs and DORs have been proposed to functionally interact through the formation of heteromeric receptors such that a selective antagonist for one receptor enhances signaling at the other (Gomes et al., 2004). To directly probe for functional interactions of this type, we developed a new photoactivatable analogue of the MOR-selective agonist DAMGO, CNV-Y-DAMGO (Ma et al., 2021). We hypothesized that if these interactions are present, inclusion of TIPP-Psi in the bath would lead to a leftward shift in the optical power-response curves of CNV-Y-DAMGO, and possibly an increase in the response kinetics. We tested this by uncaging CNV-Y-DAMGO (1 µM) while measuring somato-dendritic currents in PV-BCs (Figure 6A–E) and eIPSCs in pyramidal neurons (Figure 6F–J). In both cases, TIPP-Psi did not alter either the kinetics of the response to DAMGO photorelease (GIRK tau on CNV-Y-DAMGO: 917.6 ± 75.7 ms, n = 11 cells; CNV-Y-DAMGO+ TIPP-Psi: 808.8 ± 46.5 ms, n = 7 cells; no significant difference, Mann-Whitney test; eIPSC tau on CNV-Y-DAMGO: 476.4 ± 36.9 ms, n = 8 cells; CNV-Y-DAMGO+ TIPP-Psi: 441.6 ± 28.1 ms, n = 7 cells; no significant difference, Mann-Whitney test) (Figure 6C and H), its maximal effect (Figure 6D and I), or its power dependence (EC50 values for GIRKs in CNV-Y-DAMGO: 6.86 ± 0.68 mW, n = 8 cells; CNV-Y-DAMGO+ TIPP-Psi: 8.53 ± 0.64 mW, n = 7 cells; EC50 values for eIPSCs in CNV-Y-DAMGO: 2.79 ± 0.44 mW, n = 9 cells; CNV-Y-DAMGO+ TIPP-Psi: 3.06 ± 0.38 mW, n = 9 cells) (Figure 6E and J). These results indicate that MORs and DORs do not interact in PV-BCs in a manner consistent with MOR/DOR heteromers. To confirm the lack of TIPP-Psi effect on DAMGO-mediated suppression of PV-BC output in a cell-specific manner, we optogenetically stimulated PV-BCs with Chronos, as in Figure 1, and asked if TIPP-Psi enhanced the effect of a sub-maximal concentration of DAMGO (300 nM, Figure 6—figure supplement 1). Consistent with the uncaging data obtained using electrical stimulation, TIPP-Psi was again without effect (300 nM DAMGO: 0.33 ± 0.05; 300 nM DAMGO in TIPP-Psi: 0.30 ± 0.08; no significant difference, unpaired t-test).

Figure 6 with 1 supplement see all
Mu and delta opioid receptors do not signal as heteromers in CA1 parvalbumin (PV) neurons.

(A) Schematic of whole-cell voltage clamp recording configuration from PV interneurons with peptide uncaging. (B) Average outward currents evoked by photoactivation of CNV-Y-DAMGO with an 84 mW light flash either in the absence (sky blue, n = 8 from five mice) or presence (green, n = 7 cells from four mice) of TIPP-Psi. Scale bar: x = 10 s, y = 20 pA. (C) Time constants of current activation in response to photoactivation of CNV-Y-DAMGO in the absence or presence of TIPP-Psi. (D) Linear optical power-response curve of peak current as a function of light intensity, in the absence (sky blue) or presence (green) of TIPP-Psi. (E) Logarithmic optical power-response curves of the data in (D) normalized to the maximal peak current observed in each condition. (F) Schematic of the experimental configuration for photo-uncaging of opioid neuropeptides while recording electrically evoked inhibitory synaptic transmission in wild-type mice. (G) Average, baseline subtracted and baseline-normalized electrically evoked IPSC (eIPSC) amplitude showing the kinetics of synaptic suppression with electrical stimulation at 10 Hz in the absence (sky blue, n = 8 cells from four mice) or presence of TIPP-Psi (green, n = 8 cells from four mice). (H) Time constants of synaptic suppression at 10 Hz stimulation in response to photoactivation of CNV-Y-DAMGO in the absence or presence of TIPP-Psi. (I) Linear optical power-response curve of eIPSC suppression as a function of light intensity, in the absence (sky blue) or presence (green) of TIPP-Psi. (J) Logarithmic optical power-response curves of the data in I normalized to the maximal eIPSC suppression observed in each condition.

Figure 6—source data 1

Power-response curves and onset kinetics of CNV-Y-DAMGO uncaging with and without TIPP-Psi.

https://cdn.elifesciences.org/articles/69746/elife-69746-fig6-data1-v3.xlsx

Discussion

Identification of the delta opioid receptor as the primary target of enkephalin in CA1 PV-BCs

Prior models of neuromodulator actions on hippocampal interneurons have emphasized MOR expression as a primary distinctive feature of PV-BCs, as opposed to CCK-BCs (Freund and Katona, 2007). This results from an electrophysiological study in CA1 BCs that used the MOR agonist DAMGO to elicit outward somato-dendritic currents and suppress synaptic output (Glickfeld et al., 2008). Although multiple studies have demonstrated the expression of DORs, in addition to MORs, in CA1 PV neurons, the relative contributions of the two receptors to opioid modulation of CA1 PV-BCs has not been established (Stumm et al., 2004; Erbs et al., 2012; Faget et al., 2012). Our findings, using caged leucine-enkephalin to activate both MORs and DORs, indicate that DORs dominate cellular and synaptic responses to enkephalin, in particular at low concentrations that may be most physiologically relevant. Notably, MOR-mediated currents of >2 pA were evoked in 22/25 cells using caged LE in TIPP-Psi, which suggests that the presence of a subpopulation of cells lacking MOR entirely do not account for the small effect. Reinforcing the dominant role of DOR, the somato-dendritic currents obtained with maximal photorelease of caged DAMGO, a full agonist of MOR G protein signaling (Williams et al., 2013), were also smaller than those produced by LE uncaging in CTOP (currents were apparent in 19/19 cells). Power-response curves with caged enkephalin revealed that LE activates DORs with approximately threefold greater potency than MORs in both the somato-dendritic and presynaptic compartments. Strikingly, the power-response relationships observed in the absence of antagonist closely match those obtained with MORs blocked, which underscores the dominant role of DORs in the integrated response to enkephalin. While this may reflect a greater binding affinity of LE for DORs (Toll et al., 1998), because somato-dendritic DOR-mediated currents are much larger than MOR-mediated currents when both receptors are saturated, this preferential recruitment of DOR signaling is also likely to result in much stronger inhibition of cellular excitability. In presynaptic terminals of PV-BCs, the strong reciprocal occlusion of synaptic suppression by saturating doses of selective MOR and DOR agonists suggests that because DOR activation by LE occurs at lower concentrations, it will occlude subsequent actions of MOR at higher doses. Given that local sources of the MOR-selective neuropeptide β-endorphin are apparently lacking in CA1 (Bjorklund and Hokfelt, 1986), this raises the question as to why PV-BCs express MORs at all. One possible explanation is that diurnal variation in the levels of brain-wide β-endorphin in the cerebrospinal fluid contribute to the resting excitability and tune the strength of synaptic output via PV-BC MORs, while dynamic, local release of enkephalin in CA1 produces stronger, temporally precise inhibition of cellular output through activation of DORs (Dent et al., 1981; Barreca et al., 1986).

A recent study in CA2 implicated enkephalin release from vasoactive-intestinal peptide interneurons in social memory (Leroy et al., 2021). This effect was attributed to DOR-mediated LTD at PV-BC synapses onto PCs (Piskorowski and Chevaleyre, 2013). It is currently not clear if CA2 PV-BCs also express MOR, and if their activation also drives LTD. In contrast to CA2, enkephalin-mediated presynaptic suppression of PV-BCs is reversible in CA1. Given that hippocampal DORs contribute to memory formation, and possibly, cue-related retrieval as well (Le Merrer et al., 2011; Le Merrer et al., 2012; Le Merrer et al., 2013; ), and that hippocampal MORs are implicated in stress-induced memory deficits, one possibility is that MOR activation in response to stress-induced β-endorphin release (Millan et al., 1981) occludes enkephalin actions at DOR to perturb DOR-dependent memory formation and/or retrieval. Understanding the behavioral significance of the interplay between DOR and MOR signaling will require the identification of behavior contexts that result in endogenous enkephalin release in CA1.

Enkephalin suppresses synaptic transmission with sub-second kinetics

Although GPCRs are well established to engage effector pathways within 100 ms of exposure to agonists, data describing the kinetics of synaptic suppression by Gαi/o-coupled GPCRs are sparse. A study in rat cerebellum reported rapid and transient GABAB-mediated suppression of an excitatory synapse that peaked 300 ms after application of a high-frequency stimulus to drive GABA release, with detectable reduction in presynaptic Ca2+ 100 ms after the stimulus (Dittman and Regehr, 1997). A similarly structured study in rat striatum observed a maximal suppression of corticostriatal transmission 500 ms after stimulating striatal neurons to release endogenous opioid neuropeptides (Blomeley and Bracci, 2011). Both of these studies involved relatively small quantities of neuromodulator such that rapid clearance likely obscured the intrinsic kinetics of the presynaptic signaling pathway. Here, we found that photorelease of enkephalin during high-frequency stimulation of synaptic transmission produced suppression that peaked between 1–2 s after the light flash. The high sample frequency we employed facilitated rate determination, yielding an average time constant of ~300 ms at 10 Hz. A potential caveat to our approach is that our measurements were taken from synapses that were already in a partially depressed state. Nonetheless, we observed a striking difference in the kinetics of synaptic suppression by DORs and MORs that closely matched the time constants determined for the activation of outward current in the somato-dendritic compartment. In both cases, MORs exhibited much slower kinetics (tau ~800 ms) than DORs. This was not ligand-dependent, as the same time constants were obtained using caged DAMGO (Figure 6C and H). This stands in contrast to prior measurements of the kinetics of GIRK activation by MORs in other cell types that found faster time constants, similar to our measurements of DOR-mediated responses here (Ingram et al., 1997; Banghart and Sabatini, 2012; Williams, 2014). Interestingly, in the somato-dendritic compartment, we found that increasing MOR expression increased the MOR-evoked current activation rate. Thus, differences in MOR kinetics observed for other brain regions or cell types are likely to reflect differences in relative levels of MOR expression.

It is also notable that relatively strong activity-dependent synaptic depression due to high-frequency stimulation did not dramatically occlude synaptic suppression, indicating that release of a relatively depleted readily releasable pool of vesicles is still prone to attenuation by Gαi/o-coupled GPCRs that inhibit presynaptic Ca2+ channels. We observed a modest but significant negative correlation between the extent of synaptic suppression and the frequency of stimulation, which is consistent with voltage-dependent unbinding of Gβγ from VSCCs (Bean, 1989; Brody et al., 1997).

Lack of cross-talk between MORs and DORs in CA1 PV-BCs

MORs and DORs have been suggested to physically interact via the formation of heterodimers when expressed in the same cell. Although most of the mechanistic work on MOR/DOR heteromers has been performed in cultured cells with overexpressed receptors, multiple studies have also found evidence for their occurrence in naïve brain tissue (Gomes et al., 2004; Gupta et al., 2010; Kabli et al., 2014; Erbs et al., 2015). The pharmacological framework for detecting MOR/DOR functional interactions emerges from studies in cultured cells showing that ligands for one receptor can increase the binding (in terms of Bmax but not Kd) and signaling efficacy of agonists for the other (Gomes et al., 2000). Specifically, both the DOR-selective agonist deltorphin II and the selective antagonist TIPP-Psi were observed to enhance binding of DAMGO, which was accompanied by a decrease in DAMGO’s EC50 in a functional assay of MOR activation. Conversely, DAMGO, as well as the MOR antagonist CTOP, enhanced binding and reduced the EC50 of deltorphin II. Similar enhancements of MOR activation in the presence of DOR antagonist have been observed in brain tissue using multiple functional assays of MOR signaling, including antinociceptive behavior (Gomes et al., 2004).

Additional evidence supporting the existence of endogenous MOR/DOR heteromers has emerged from the observation that the efficacy of bivalent MOR-DOR ligands is highly dependent on the length of the linker connecting them, which is consistent with action at a receptor complex (Daniels et al., 2005). Numerous studies of receptor trafficking in cultured cells indicate substantial co-localization of MORs and DORs, as well as co-internalization upon exposure to certain agonists for one of the two receptors (e.g. He et al., 2011; Derouiche et al., 2020). In addition, biochemical studies have reported co-immunoprecipitation from naïve brain tissue using an antibody for either MORs or DORs (Gomes et al., 2000), or an antibody that specifically recognizes MOR/DOR heteromers (Gupta et al., 2010).

In contrast to these prior studies that focus on heteromers, we found no evidence for functional interactions between MORs and DORs in CA1 PV-BCs. Rather than synergistic, supralinear signaling, we observed largely parallel signaling and occlusion. If LE elicited synergistic signaling between MORs and DORs, we would predict that the power-response curve for LE with both receptors intact (control conditions) would sit to the left of the curves obtained for either receptor in isolation using selective antagonists. This was not the case. Instead, in both subcellular compartments, DOR activation accounted for the low end of the power-response curves, with MORs contributing only at higher concentrations. Strong occlusion at presynaptic terminals was observed, as simultaneous application of small molecule agonists for both receptors only slightly increased the extent of synaptic modulation in comparison to either drug alone (from 70% to ~75% suppression). Similar occlusion was also observed while monitoring presynaptic Ca2+ transients. Interestingly, only unidirectional occlusion was observed in the somato-dendritic compartment, where MOR block had no effect on outward currents driven by high doses of LE, while DOR block dramatically reduced them. This observed sub-linear signaling suggests that DORs have access to a larger pool of GIRKs than MORs, and that GIRKs activated by MORs are completely shared between both receptor types. A model based on these results is presented in Figure 7.

Models of mu opioid receptor (MOR) and delta opioid receptor (DOR) signaling in the soma and the pre-synaptic terminal.

(A) In the soma, both MORs (blue) and DORs (red) signal through G protein-coupled inward rectifier K+ (GIRK) channels. MORs are expressed at lower levels than DORs, as the somato-dendritic currents evoked by activation of MORs alone are small and are increased by increasing MOR expression. The unidirectional occlusion observed suggests that MORs only have access to a subset of GIRKs, whereas DORs have access to a larger pool that encompasses the MOR-pool. (B) In the pre-synaptic terminal, MORs and DORs both act on voltage-sensitive calcium channels (VSCCs) to suppress Ca2+ influx and inhibit vesicle release. Unlike somatic MORs and DORs, pre-synaptic MORs and DORs are bidirectionally occlusive, so that both MORs and DORs have access to the majority of VSCCs.

In addition, we did not observe heterologous desensitization between MORs and DORs in the somato-dendritic compartment. In general, presynaptic inhibitory GPCRs do not desensitize (Pennock et al., 2012). Due to the relatively small amount of presynaptic desensitization observed (~20% with DAMGO), we did not attempt to study heterologous desensitization at presynaptic terminals. Given the strong occlusion we observed between MOR and DOR in presynaptic terminals, it remains possible that some heterologous desensitization may occur in this compartment. In opioid-naïve animals, desensitization appears to occur at the level of the receptor, likely due to C-terminus phosphorylation, rather than through the effectors (Llorente et al., 2012; Leff et al., 2020). Nonetheless, because desensitization can lead to endocytosis, and possibly conformational changes, if the receptors were physically interacting, desensitization of one receptor may be expected to impact signaling at the other.

Similarly, our findings argue against the presence of native MOR/DOR heteromers that influence cellular physiology in either the somato-dendritic or presynaptic compartments of CA1 PV-BCs, since TIPP-Psi had no effect on DAMGO potency or signaling kinetics, both of which serve as sensitive measures of receptor function. This lack of interaction between MORs and DORs is consistent with our previous observation in striatal indirect pathway neurons, wherein their actions were strictly additive, and genetic removal of either receptor neither enhanced nor suppressed the efficacy of the other (Banghart et al., 2015). A possible explanation is that MOR/DOR heteromers present in PV-BCs are retained in the Golgi apparatus due to a lack of Rtp4 expression (Allen Institute for Brain Science, 2015; Décaillot et al., 2008; Saunders et al., 2018). As this may involve sequestering MORs, it may also contribute to the surprisingly small somato-dendritic MOR-mediated GIRK currents we observed. While MOR/DOR functional interactions may be more prominent in other brain regions, our findings indicate that co-expression and co-localization in subcellular compartments do not guarantee receptor cross-talk at the cell surface.

In conclusion, DORs in CA1 PV-BCs, rather than MORs, are the primary target of the opioid neuropeptide enkephalin. Although signaling at both receptors converges on largely overlapping populations of effectors within the same subcellular compartments, MORs and DORs appear to signal predominantly in a parallel, functionally independent manner. These results imply that functional redundancy between multiple GPCRs expressed in the same neuron may be a common feature in the nervous system. Additional research is necessary to further delineate mechanisms that determine whether or not heteromers form when heterophilic receptors are present in close proximity within cells.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Mus musculus, male and female)C57Bl/6The Jackson LaboratoryCat # 000664RRID:IMSR_JAX:000664
Strain, strain background (Mus musculus, male and female)PvalbCreThe Jackson LaboratoryCat # 012358RRID:IMSR_JAX:012358
Strain, strain background (Mus musculus, male and female)Rosa26-lsl-tdTomato (Ai14)The Jackson LaboratoryCat # 007914RRID:IMSR_JAX:007914
Recombinant DNA reagentAAV1-Syn-FLEX-Chronos-GFPAddgeneCat # 62722RRID:Addgene_62722
Recombinant DNA reagentAAVDJ-hSyn1-FLEX-mCh-T2A-FLAG-hMOR-WPREBanghart LabAddgene Plasmid #166970
Commercial assay or kitRNAscope Fluorescent Multiplex KitACD bio/Bio-TechneCat # 320850
Commercial assay or kitPvalb FISH probeACD bio/Bio-TechneCat # 421931-C3
Commercial assay or kitOprd1 FISH probeACD bio/Bio-TechneCat # 427371-C2
Commercial assay or kitOprm1 FISH probeACD bio/Bio-TechneCat # 315841
Chemical compound, drugN-MNVOC-LEBanghart et al., 2018
Chemical compound, drugCYLEBanghart Lab and NIDA Drug Supply Program Banghart and Sabatini, 2012MPSP-117 (NDSP)
Chemical compound, drugCNV-Y-DAMGOMa et al., 2021
Chemical compound, drugNBQXHelloBioCat # HB0443
Chemical compound, drug(R)-CPPHelloBioCat # HB0021
Chemical compound, drugTIPP-PsiNIDA Drug Supply ProgramMPSP-056
Chemical compound, drugCTOPTocrisCat # 1578
Chemical compound, drugDAMGOTocrisCat # 1171
Chemical compound, drugSNC162TocrisCat # 1529
Chemical compound, drugAlexaFluor 547Thermo FisherCat # 10438
Chemical compound, drugFluo5FThermo FisherCat # F14221
Chemical compound, drugPicrotoxinSigmaCat # P1675
Chemical compound, drugTTXHelloBioCat # HB1035
Chemical compound, drugWIN55,212TocrisCat # 1038
Chemical compound, drugDeltorphin IINIDA Drug Supply ProgramMPSP-036
Chemical compound, drugZD7288TocrisCat # 1000
Software, algorithmMATLABMathworks IncRRID:SCR_001622
Software, algorithmScanImagePologruto et al., 2003RRID:SCR_014307
Software, algorithmIgor ProWaveMetricsRRID:SCR_000325
Software, algorithmImageJNIHRRID:SCR_003070
Software, algorithmIllustrator CCAdobe Systems IncRRID:SCR_010279
Software, algorithmPrism 7GraphPad IncRRID:SCR_002798
Software, algorithmExcelMicrosoftRRID:SCR_016137

Brain slice preparation

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Animal handling protocols were approved by the UC San Diego Institutional Animal Care and Use Committee. Most experiments were conducted using postnatal day 15–32 mice of both males and females on a C57Bl/6 background. For experiments that required viral expression (Figures 1A–E4H–K, and Figure 6—figure supplement 1), older mice of postnatal day 25–41 (both males and females) were used. Mice were anesthetized with isoflurane and decapitated, and the brain was removed, blocked, and mounted in a VT1000S vibratome (Leica Instruments). Horizontal slices (300 μm) were prepared in ice-cold choline-ACSF containing (in mM): 25 NaHCO3, 1.25 NaH2PO4, 2.5 KCl, 7 MgCl2, 25 glucose, 0.5 CaCl2, 110 choline chloride, 11.6 ascorbic acid, and 3.1 pyruvic acid, equilibrated with 95% O2/5% CO2. Slices were transferred to a holding chamber containing oxygenated ACSF containing (in mM): 127 NaCl, 2.5 KCl, 25 NaHCO3, 1.25 NaH2PO4, 2 CaCl2, 1 MgCl2, and 10 glucose, osmolarity 290. Slices were incubated at 32°C for 30 min and then left at room temperature until recordings were performed.

Electrophysiology

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All recordings were performed within 5 hours of slice cutting in a submerged slice chamber perfused with ACSF warmed to 32°C and equilibrated with 95% O2/5% CO2. Whole-cell voltage clamp recordings were made with an Axopatch 700B amplifier (Axon Instruments). Data were filtered at 3 kHz, sampled at 10 kHz, and acquired using National Instruments acquisition boards and a custom version of ScanImage written in MATLAB (Mathworks). Cells were rejected if holding currents exceeded −200 pA or if the series resistance (<25 MΩ) changed during the experiment by more than 20%. For recordings measuring K+ currents in PV cells (Figure 1), patch pipettes (open pipette resistance 2.0–3.0 MΩ) were filled with an internal solution containing (in mM): 135 KMeSO4, 5 KCl, 5 HEPES, 1.1 EGTA, 4 MgATP, 0.3 Na2GTP, and 10 Na2phosphocreatine (pH 7.25, 286 mOsm/kg). Cells were held at −55 mV, and synaptic transmission was blocked with the addition to the ACSF of 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo(f)quinoxaline (NBQX; 10 μM), R,S-3-(2-carboxypiperazin-4-yl)propyl-1-phosphonic acid (CPP; 10 μM), picrotoxin (10 μM), and TTX (1 μM). TdTomato-expressing neurons were visualized through a Cy3 filter cube (Semrock Cy3-4040C) upon illumination with an CoolLED pE-300. For recordings measuring inhibitory synaptic transmission in mouse hippocampus, patch pipettes (2.5–3.5 MΩ) were filled with an internal solution containing (in mM): 135 CsMeSO3, 10 HEPES, 1 EGTA, 3.3 QX-314 (Cl salt), 4 Mg-ATP, 0.3 Na-GTP, and 8 Na2phosphocreatine (pH 7.3, 295 mOsm/kg). Cells were held at 0 mV to produce outward currents. Excitatory transmission was blocked by the addition to the ACSF of NBQX (10 μM) and CPP (10 μM). To electrically evoke IPSCs, stimulating electrodes pulled from theta glass with ∼5 μm tip diameters were placed at the border between stratum pyramidale and stratum oriens nearby the recorded cell (∼50–150 μm) and two brief pulses (0.5 ms, 50–300 μA, 50 ms interval) were delivered every 20 s. The experimenters were not blinded to the pharmacological conditions employed.

UV photolysis

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Uncaging was carried out using 5 ms flashes of collimated full-field illumination with a 355 nm laser, as previously described. Light powers in the text correspond to measurements of a 10 mm diameter collimated beam at the back aperture of the objective. Beam size coming out of the objective onto the sample was 3900 μm2.

Optogenetics

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AAV encoding Chronos-GFP was injected into the hippocampus of PvalbCre pups P0-3. The virus was allowed to express for 4 weeks and then acute hippocampal slices were made as described above. For optogenetic stimulation of PV basket cell terminals, two 2 ms pulses from a blue LED (CoolLED pE-300, filtered through a 472/30 nm bandpass, Semrock [FF02-472/30-25]) were applied over the cell body of the recorded PC. The field stop of the LED was narrowed to 6600 μm2 in order to limit the excitation to only the immediate axons surrounding the cell body, such that the power reaching the sample was 5–20 mW/mm2.

Two-photon calcium imaging

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Two-photon imaging of axonal boutons was performed using a custom-built two-photon laser scanning microscope (Carter and Sabatini, 2004; Bloodgood and Sabatini, 2007). First, PV neurons in the CA1 region of the hippocampus were visualized using epifluorescence in a PvalbCre/Rosa26-lsl-tdTomato line and targeted recordings were made under infrared differential interference contrast (IR-DIC) on an Olympus BX51 microscope. Whole-cell current clamp recordings were made with a potassium (K)-methanesulfonate internal consisting of (in mM): 135 KMeSO4, 5 KCl, 5 HEPES, 4 MgATP, 0.3 Na2GTP, and 10 Na2phosphocreatine. The internal also contained the Ca2+-sensitive green fluorophore Fluo-5F (300 μM) and Ca2+-insensitive red fluorophore Alexa Fluor-594 (30 μM). After a patch was made, the cell was allowed at least 15 min for the dye and indicator to fill the axons. Then an 800 nm laser was used to locate axonal boutons based on morphology. Once identified, line scans were made across 1–2 boutons while evoking one or five APs by injecting voltage into the cell body. Calcium transients were averaged across 30 trials, before and after drug addition. Stimulus-evoked changes in fluorescence (and the Ca2+ signal) were reported as ∆G/Gsat, reflecting measurements of ∆G/R normalized to G/R in saturating Ca2+ as described previously (Bloodgood and Sabatini, 2007).

Data analysis

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Electrophysiology data were analyzed in Igor Pro (Wavemetrics). Peak current amplitudes were calculated by averaging over a 200 ms (GIRK) or 2 ms (synaptic transmission) window around the peak. Activation time constants for GIRKs were calculated by fitting the rising phases of light-evoked currents to an exponential function. To determine magnitude of modulation by enkephalin uncaging (%IPSC suppression), the IPSC peak amplitude immediately after a flash was divided by the average peak amplitude of the three IPSCs preceding the light flash. Kinetics of synaptic modulation (Figure 3) were determined by averaging three stimulus trains before uncaging (at 10, 20, and 50 Hz) and fitting a bi-exponential curve to describe the synaptic depression. The curve was then divided from the stimulus train with uncaging to get the traces seen in Figure 3B. The time constant was then extracted from a mono-exponential fit to the suppression from the time of uncaging. The effects of drugs on IPSC suppression were calculated as the average %IPSC suppression 1–3 min after drug addition. PPR was determined by dividing Peak 2/Peak 1, where Peak 2 was calculated by subtracting the residual Peak 1 current (1 ms before second stimulus) from the absolute peak amplitude of Peak 2. Summary values are reported as mean ± SEM. Data were tested for normality using the D’Agostino and Pearson test, and the appropriate statistical tests (parametric or non-parametric) were carried out based on those results. All statistical tests were performed in GraphPad Prism except for the Skilling-Mack test, which was performed in MATLAB using code developed by Thomas Pingel [https://github.com/thomaspingel/mackskill-matlab; copy archived at swh:1:rev:8e91d5dfb95435b880ed1320727d956d2d44dd15 (Pingel, 2016)] . Specific statistical tests and corrections are described for each figure in the text and figure legends.

Fluorescence in situ hybridization

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Mice were deeply anesthetized with isoflurane and decapitated, and their brains were quickly removed and frozen in tissue freezing medium on dry ice. Brains were cut on a cryostat (Leica CM 1950) into 8 μm sections, adhered to SuperFrost Plus slides (VWR), and stored at –80°C. Samples were fixed with 4% paraformaldehyde, processed according to ACD RNAscope Fluorescent Multiplex Assay manual, and coverslipped with ProLong antifade reagent (Molecular Probes). Sections were imaged on a Keyence BZ-X710 Microscope at 60× magnification. The images were acquired and manually scored for the presence of fluorescent puncta and co-localization using ImageJ.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

References

    1. Abdelhamid EE
    2. Sultana M
    3. Portoghese PS
    4. Takemori AE
    (1991)
    Selective blockage of delta opioid receptors prevents the development of morphine tolerance and dependence in mice
    The Journal of Pharmacology and Experimental Therapeutics 258:299–303.
  1. Book
    1. Bjorklund A
    2. Hokfelt T
    (1986)
    Gaba and Neuropeptides in the Cns, Part I
    In: Greengard P, editors. Handbook of Chemical Neuroanatomy. Elsevier Science Ltd. pp. 1–423.
  2. Book
    1. Cahill CM
    2. Ong E
    (2018) Evidence and function relevance of native DOR–MOR heteromers
    In: Barrett JE, editors. Handbook of Experimental Pharmacology. New York: Springer. pp. 115–127.
    https://doi.org/10.1007/164_2018_112
    1. Hamm HE
    2. Alford ST
    (2019) Physiological roles for neuromodulation via Gi/o GPCRs working through Gβγ–SNARE interaction
    Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology 45:221.
    https://doi.org/10.1038/s41386-019-0497-2
    1. Knapp RJ
    2. Santoro G
    3. De Leon IA
    4. Lee KB
    5. Edsall SA
    6. Waite S
    7. Malatynska E
    8. Varga E
    9. Calderon SN
    10. Rice KC
    11. Rothman RB
    12. Porreca F
    13. Roeske WR
    14. Yamamura HI
    (1996)
    Structure-activity relationships for SNC80 and related compounds at cloned human delta and mu opioid receptors
    The Journal of Pharmacology and Experimental Therapeutics 277:1284–1291.
    1. Porreca F
    2. Heyman JS
    3. Mosberg HI
    4. Omnaas JR
    5. Vaught JL
    (1987)
    Role of mu and delta receptors in the supraspinal and spinal analgesic effects of [D-Pen2, D-Pen5]enkephalin in the mouse
    The Journal of Pharmacology and Experimental Therapeutics 241:393–400.
    1. Sánchez-Blázquez P
    2. García-Espãna A
    3. Garzón J
    (1997)
    Antisense oligodeoxynucleotides to opioid mu and delta receptors reduced morphine dependence in mice: role of delta-2 opioid receptors
    The Journal of Pharmacology and Experimental Therapeutics 280:1423–1431.
    1. Toll L
    2. Berzetei-Gurske IP
    3. Polgar WE
    4. Brandt SR
    5. Adapa ID
    6. Rodriguez L
    7. Schwartz RW
    8. Haggart D
    9. O’Brien A
    10. White A
    11. Kennedy JM
    12. Craymer K
    13. Farrington L
    14. Auh JS
    (1998)
    Standard binding and functional assays related to medications development division testing for potential cocaine and opiate narcotic treatment medications
    NIDA Research Monograph 178:440–466.

Decision letter

  1. Gregory Scherrer
    Reviewing Editor; UNC School of Medicine, United States
  2. Lu Chen
    Senior Editor; Stanford University, United States
  3. Gregory Scherrer
    Reviewer; UNC School of Medicine, United States
  4. Brady K Atwood
    Reviewer; Indiana University School of Medicine, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for submitting your work entitled "Convergent, functionally independent signaling by mu and delta opioid receptors in hippocampal parvalbumin interneurons" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Lu Chen as the Senior Editor.

Essential revisions:

Requiring experiments:

1. Regarding the experiments examining MOR-DOR functional interactions at the synaptic terminals of PV+ cells, the authors used electrical stimulation to excite PV+ cells. Electrical stimulation most likely recruits other inhibitory inputs in addition to PV+ cells, and it is clear from the literature that other types of inhibitory interneurons express MOR and/or DOR. With this electrical stimulation protocol, the authors might be recording agonist effects on convergent inputs from different MOR+ and/or DOR+ inhibitory neurons, instead of interrogating MOR-DOR cellular interactions in PV+ cells. To sustain the claim that they interrogated MOR-DOR cellular interactions specifically in PV+ inputs, the authors would need to confirm they obtain consistent findings and reach the same conclusions when stimulating specifically PV+ cells using optogenetics.

2. While the literature supports the idea that DOR is expressed by virtually all PV+ neurons, MOR expression in PV+ cells is more variable, with some PV+ cells lacking MOR expression. The authors claim that MOR has limited function in somatic excitability control, however, this limited function of MOR in soma could result, in part, from the inclusion in the analysis of recordings from MOR-negative PV+ cells. To sustain this claim, the authors would need to a. confirm MOR expression in recorded PV+ neurons, and b. test additional MOR agonists.

Without additional experiments:

3. The statistical analysis needs to be comprehensively revised, please see specific recommendations from the Reviewers.

4. The wording used by the authors to describe their experiments and findings needs to be more precise and careful; the experiments performed probe cellular functional interactions between the two receptors, not dimerization.

5. The methods need to be described more thoroughly, with the inclusion of additional details including the sex and age of the animals, blinding of experimenters, PPR experiments, new CNV-Y-DAMGO ligand, and SNC162 selectivity. Please see the specific recommendations from the Reviewers.

Reviewer #1:

This manuscript by Banghart et al. uses slice electrophysiology to examine the functional interactions between the delta and mu opioid receptors (DOR and MOR, respectively) in a class of neurons proposed to co-express both receptors, PV+ hippocampal interneurons. Whether these two receptors are co-expressed in neurons in intact circuits and can influence each other's functions, including through direct physical interactions and heterodimerization, is a long-standing and important question in the fields of opioid neurobiology, pain, and addiction. The studies are logically organized and generally well designed to answer this question. The experiments employ complementary and sophisticated receptor stimulation and recording paradigms, and the data presented convincingly support the authors' claim that DOR and MOR signal independently in PV+ hippocampal interneurons.

– One of the most interesting findings reported here is that MOR signaling is relatively inefficient in PV+ neurons. Supporting Figure S1 shows that not all PV+ neurons express DOR and MOR, consistent with published RNA-seq data. How was MOR expression tracked in individual PV+ recorded neurons and taken into account when interpreting the data? For example, in Figure 4C, while the authors state that "blocking MORs with CTOP had no measurable effect", it seems that there is considerable variability in the CTOP effect, with some cells showing a clear reduction in current amplitude compared to ACSF. Could it be that the cells in which no CTOP effect was observed in fact did not express MOR? This would be consistent with findings in cortical PV+ neurons, which consistently express DOR but where MOR expression is more variable (Birdsong et al. 2019 eLife, Smith et al. 2018 eLife). This clarification is important for the interpretation of many experiments. To confirm that MOR signaling is relatively inefficient in CA1 PV+ neurons, it would be helpful to test the effects of additional MOR-selective agonists on membrane potential or holding current.

– Figure 4D. Are the ACSF and CTOP peak currents statistically different? The authors indicate that "opioid-dose response curves in the presence of each antagonist revealed a larger DOR-mediated than MOR-mediated" current; however, it is unclear that this experiment revealed any MOR-mediated current at all.

– Figure 4H. What is the expression level and subcellular distribution of the hMORs, and is it comparable to that of the native MORs in cells where MOR-mediated responses are recorded? A histological analysis would be useful, if only as a control to confirm hMOR expression in PV+ cells.

– The authors indicate that they "chose SNC162 for its exceptional selectivity for DOR over MOR". It is unclear that SNC162 selectivity is superior to that of SNC80 or deltorphin II, the agonists typically used to interrogate DOR function. To justify their statement, can the authors provide published KD (or KI) data for each receptor and selectivity ratios for these three ligands?

– Can the authors provide additional information on CNV-Y-DAMGO such as its KD for MOR, selectivity for MOR vs DOR, and whether CNV-Y-DAMGO effects are lost in Oprm1 KO mice or in the presence of CTOP? At present, the utility of CNV-Y-DAMGO versus the well characterized agonist DAMGO for Figure 6 experiments is not obvious.

– The interrogation of DOR-MOR functional interactions in PV+ hippocampal neurons is unidimensional and restricted to neurophysiological effects. Ideally, one would want to clarify, or at least discuss, the function of DOR or MOR and their potential interactions in PV+ hippocampal neurons at other levels of opioid receptor biology, such as at the behavioral levels, on learning and memory.

– In the Introduction, the study by Wang et al. 2018 is described as a trafficking study. However, this study did not only use imaging of receptor trafficking to examine DOR-MOR interactions in neurons that co-express both receptors, but also electrophysiological recordings and desensitization protocols. These electrophysiological studies showed that the pharmacological elimination of DOR from the plasma membrane did not affect the ability of MOR to signal and activate GIRK channels. Additionally, Wang et al. verified MOR and DOR co-expression in recorded cells and included other levels of analysis, including behavioral studies. Since the aims of the Wang et al. 2018 study are conceptually very similar to those of the present study, and both studies conclude that MOR and DOR signal independently, it is important that these earlier findings are presented accurately to the reader in the Introduction and Discussion.

– It would also be useful to the reader to discuss the literature claiming that DOR is a dormant receptor, without function in the absence of priming stimulus, and clarify that the results presented here refute this idea.

– Please check the list of References. For example the Bean 1989 paper is cited in the Results but absent from the References section.

Reviewer #2:

The authors then make use of photopharmacology and calcium imaging to demonstrate that both MOR and DOR suppress presynaptic voltage gated calcium channels on PV interneurons. They demonstrate that DOR signaling is the primary driver of somato-dendritic inhibition through coupling to GIRK channels. Given that MOR and DOR were expressed on overlapping populations of neurons, they examine whether these receptors signaling as "functional heterodimers." However, they found no evidence of heterologous desensitization or functional heterodimerization, suggesting these receptors to not dimerize in hippocampal PV interneurons using the techniques they use here. It still remains rather unclear what we all mean when we say "dimers" for Class A receptors anyways. Maybe they quickly kiss one another during anterograde transport, or maybe it is packaging for internalized and degraded receptors. The authors still leave those questions very unanswered, but the study remains important in other ways and adds to our understanding of GPCR interactions. I would suggest at the outset that the authors are more careful with the term dimers throughout and clarify what they mean by the term.

Strengths:

This is a highly rigorous set of experiments, using complementary approaches to understand the functional interaction between MOR and DOR receptors in hippocampal PV interneurons. The techniques are well suited to address these questions, and the authors make use of novel photo-uncageable opioid ligands in combination with traditional pharmacological approaches to probe these interactions. Decades of research in heterologous expression systems have demonstrated that MOR and DOR can functionally dimerize, yet few studies have examined this in native systems. This study provides strong evidence for the lack of functional dimerization in PV interneurons.

Weaknesses: the central limitations of this study relation to the terminology used, the use of electrical stimulation in some cases, and the cell type selectivity.

Comments for the authors:

1) There is methodological concern with the surprising switch from optogenetic to electrical stimulation of putative PV input to pyramidal neurons. The authors mention that this is to "improve experimental throughput." However, this explanation is not sufficient given the caveats of this approach. First, the authors attempt to demonstrate that inhibitory input from CCK interneurons is not recruited by this stimulation paradigm by examining cannabinoid agonist induced depression, which they mentioned was minimal. However, 25% depression should not be dismissed, as only a subset of inhibitory interneurons in the hippocampus express CB1 (mainly CCK interneurons). This suggests that the electrical stimulation paradigm is likely also recruiting CCK input as well. While this may not in and of itself be an issue given the low expression of opioid receptors on this population, other hippocampal interneurons, such as somatostatin positive interneurons, do express opioid receptors at a high level. Therefore, the authors cannot conclude with certainty that they are only recording from PV input. There are also noticeable differences between the optical and electrical stimulation paradigms, as MOR agonist application with optical stimulation induces an increase in the PPR while there is no significant change with electrical stimulation. Lastly, the paper they site as justification for this electrical stimulation paradigm does not use bipolar electrical stimulation at any point; thus using this paper as justification is incorrect. Therefore, they should do one of three things: 1). Demonstrate these effects to do not hold for other populations of hippocampal interneurons, 2). Replicate more of their PV projection findings using optogenetic approaches, 3). Remove mention of PV and say inhibitory input instead.

2) Dimerization is a term that is frankly used for GPCRs in strange ways (think about how pentameric ion channels are described for example to reevaluate the meaning here), and so "functional heteromers" seems less accurate even. The authors need to really clarify more in the intro and discussion these distinctions and make it more clear what they mean by their terms. They've certainly provided nice data with respect to functional "interactions" between receptors, but the TIRF experiments are missing, as are critical biochemical experiments, or FRET studies to definitively rule out all interactions. There readouts limit this, as does their language about it need some refining.

Reviewer #3:

The question of whether different types of opioid receptors expressed in the same cell operate independently or as obligatory functional units (heterodimers) has been of great interest to the field for some time. This study tested the hypothesis that mu and delta opioid receptors (MORs and DORs respectively) that are co-expressed in hippocampal basket cells are both able to independently modulate neuronal excitability and regulate synaptic transmission. This is a potentially very exciting study as the authors conclude that these two receptors couple to similar effector systems in these cells, but do so independently. The investigators explored their hypothesis with a variety of complementary methods to assess the interactions in multiple ways. While the data largely support their conclusion, there are some concerns regarding how the data were analyzed and in some elements of the experimental design (especially related to animal age), thus suggesting caution in how to interpret their data at this point. Nonetheless, the impact of this study, if proven correct, will be great as it helps elucidate signaling interactions between different opioid receptors that respond to the same endogenous ligands and couple to similar signaling pathways.

Strengths:

1. Comparing the interaction of MORs and DORs in both the synaptic terminals and the somatodendritic compartments allows for an understanding how the cellular environment can influence interactions. The investigators used a variety of electrophysiological measures and pharmacological and genetic tools to provide a nice composite view of receptor signaling differences.

2. The use of caged opioid ligands allows for detailed assessments of the kinetics of responses.

3. The investigators explored convergent signaling, heterologous desensitization and dimerization, all important aspects of studying the different ways the receptors could interact.

Weaknesses:

1. There are concerns regarding the statistical tests performed and how the data are interpreted based upon these analyses. The methods states that all data were treated as parametric, but a justification for this is not provided, and it is not clear that this is accurate because the text reports the use of non-parametric analyses. It is apparent that the authors are interested in comparing cellular responses mediated by MORs and DORs, yet in most multiple comparison statistical tests, comparisons are only made between receptor antagonists and control and not to each other. Statistical assessment of the role of specific ion channels in the effects of MOR and DOR activation were not appropriately performed. In many places, statistical significance is ignored and results are treated as significantly different when the analyses do not support these conclusions. Therefore, some of the results should be interpreted with caution. Order effects of antagonists are considered in Figure 3, but not other figures. It was not indicated if investigator blinding to treatment was used.

2. The sex of the animals used was not reported. The age of the animals also spanned a large range (postnatal days 15-35). This is a major concern as there is considerable brain development that occurs over this age range that could produce physiological changes in the hippocampus. It is important to take age and sex into account in the interpretation of the data.

3. Heterologous desensitization was tested for somatodendritically-localized receptors, but not for synaptic receptors, given that they stated that presynaptic MORs desensitize (it was not specifically tested if DORs do). Given that there was mutual occlusion at the terminals, it is important to note whether these receptors undergo such heterologous desensitization, even if they don't heterodimerize.

4. The authors propose that DORs in the basket cells play a larger role in modulating basket cell function than MORs, and based on their data, this may be true under conditions where enkephalin predominates. Overall, the authors' conclusions are likely accurate, however it is conceivable that the results are the outcomes of testing a limited set of ligands. The authors rightly suggest that as far as physiological conditions are the focus, circulating β-endorphin could produce a different outcome. However, exogenous opioids (e.g. prescription painkillers, illicit opioids) could also differentially engage MORs and DORs and produce different outcomes due to differences in affinity or even functional selectivity.

5. Indicate the sex and ages of the animals used for each experiment.

6. Resolve discrepancy between actual statistical tests used and the statement in the methods that all data were treated as parametric. Were data tested for normality? Were outliers identified (there are a number of places where there appeared to be outliers)?

7. Dunnett's multiple comparison post hoc test is not the appropriate test for the assessment of their findings, especially as they are often making statements of comparisons between the roles of MOR and DOR. Tukey's multiple comparisons test is the more appropriate post hoc analysis. They used this test in Figure 4, but not in other figures.

8. Resolve why order effects were tested in Figure 3, but not other figures?

9. Statistical significance was treated very lightly throughout the manuscript. For example, components of Figures 1J, S1E, 2G, S2B were discussed as if they were significant (or selectively interpreted if one component was significant and another was not). For example, I am not convinced that DAMGO doesn't occlude the effect of WIN55,212-2 in S1E.

10. Figure S2B was indicated to show the role of GIRKs and HCNs in the effects of receptor activation. A one-way ANOVA was not the appropriate statistical test in this case as all this did was show that Ba2+ had no difference in its effect regardless of the drug treatment, but does not specifically test the involvement of different ion channels.

11. It was stated that DAMGO produced desensitization in Figure 1C,H. Was this statistically determined?

12. The methods do not describe the performance/analysis of PPR. How was amplitude of the second peak determined as the decay from the first hadn't completely returned to baseline?

13. The authors cite a publication in preparation as evidence of validation of their caged DAMGO peptide. This is worrisome for the interpretation of their findings without any provided validation here.

14. The authors looked at heterologous desensitization in somatodendritic signaling, but not at synaptic terminals. This is especially important as the two receptors are mutually occlusive at the terminals. Even if they are not dimers, they could produce heterologous desensitization. At the very least, the authors need to justify why they didn't explore this at synaptic terminals or present this as a limitation of their study.

15. Why do the authors think that they had less suppression as a result of uncaging than they did with bath application (Figure 1I)?

16. Some line colors in a number of figure panels are difficult to resolve due to their similarities. For example, Figure 5F-H, Figure 6.

17. Include a statement of investigator blinding.

https://doi.org/10.7554/eLife.69746.sa1

Author response

Essential revisions:

Requiring experiments:

1. Regarding the experiments examining MOR-DOR functional interactions at the synaptic terminals of PV+ cells, the authors used electrical stimulation to excite PV+ cells. Electrical stimulation most likely recruits other inhibitory inputs in addition to PV+ cells, and it is clear from the literature that other types of inhibitory interneurons express MOR and/or DOR. With this electrical stimulation protocol, the authors might be recording agonist effects on convergent inputs from different MOR+ and/or DOR+ inhibitory neurons, instead of interrogating MOR-DOR cellular interactions in PV+ cells. To sustain the claim that they interrogated MOR-DOR cellular interactions specifically in PV+ inputs, the authors would need to confirm they obtain consistent findings and reach the same conclusions when stimulating specifically PV+ cells using optogenetics.

We agree with this statement, which pertains to ~20% of the experiments presented (Figure 2 and Figure 6G-J). Indeed, in Supporting Figure 1D-E, we show that ~25% of the eIPSC is sensitive to CB1 agonist, which suggests that our stimulation may also recruit a minor population of CB1R-expressing, presumably CCK+ axons. It is also likely that a small population of the recruited synapses are suppressed by both receptors, which is consistent with the occlusion observed in Figure S1E. Although we used a small bipolar stimulating electrode constructed from theta glass in order to restrict the volume of tissue stimulated to that immediately adjacent to the recorded pyramidal cell, thus enriching the eIPSC for basket-cell terminals, it is possible that we excite processes of other non-PV+ interneurons passing through the stimulated volume. We have added a statement to the Results section for Figure 1 reflecting this consideration, which is most pertinent to the potency and kinetic data presented subsequently in Figure 2.

A major reason electrical stimulation was employed was to allow the use of peptide uncaging with UV light, as the UV light also activates opsins such as Chronos. This greatly complicates analysis of uncaging responses, as one must control for the effect of a large UV light flash on subsequent oIPSCs in the absence of caged peptide – this consideration was bundled into the term “throughput” without elaboration. Because we have observed strong opsin responses to UV light flashes in the past, and subsequent alterations in blue light-evoked release, we did not attempt to combine the two optical methods in this study (the power-response experiments would be particularly impractical). We have also observed apparent opsin bleaching in response to strong UV light flashes, in particular when opsin expression is modest. We regret not stating this rationale in the manuscript. Because we introduced electrical stimulation before we introduce peptide uncaging, it felt awkward to present this justification in Figure 1, which does not involve peptide uncaging. Nonetheless we have now included it there as it is an important technical rationale that impacts the interpretation of the subsequent results.

Technical constraints aside, we have attempted to address the major finding made using electrical stimulation, namely that MOR and DOR do not functionally interact according to a receptor-heteromer model, using optogenetic stimulation of PV+ axons with Chronos in PV-Cre mice, as in Figure 1. For this experiment, we identified and applied a sub-saturating concentration of DAMGO (300 nM) in the absence and presence of the DOR antagonist TIPP-Psi (1 uM). This is very similar to the experiment shown in Figure 6I/J, but only involves a single DAMGO concentration. Because 300 nM DAMGO only produced partial suppression, if DOR antagonism enhanced MOR signaling at PV+ terminals as suggested by the MOR/DOR heteromer model, we would expect to observe greater suppression in TIPP-Psi. Consistent with our results using electrical stimulation and power-response curves with caged DAMGO, no difference was observed. This experiment is now presented in Supporting Figure S3 and has been added to the text. We think that this result strengthens our primary finding that is based solely on electrical stimulation of synaptic transmission and thank the reviewers for the suggestion.

2. While the literature supports the idea that DOR is expressed by virtually all PV+ neurons, MOR expression in PV+ cells is more variable, with some PV+ cells lacking MOR expression. The authors claim that MOR has limited function in somatic excitability control, however, this limited function of MOR in soma could result, in part, from the inclusion in the analysis of recordings from MOR-negative PV+ cells. To sustain this claim, the authors would need to a. confirm MOR expression in recorded PV+ neurons, and b. test additional MOR agonists.

a. We think that the absence of MOR in some PV neurons further supports our claim that MOR plays a limited role in somatic excitability control when considering the PV-BC cell population as a whole. When considering individual cells, our electrophysiological recordings from PV neurons do not appear to include many neurons that lack MOR responses, such that non-responders (presumably MOR-negative neurons) could account for the statistically determined difference between the average MOR and DOR-mediated somato-dendritic outward currents. A sentence was added to the discussion to address this point: “Notably, MOR-mediated currents were evoked in 22/25 cells using caged LE in TIPP-Psi, which suggests that the presence of a subpopulation of cells lacking MOR entirely do not account for the small effect.”

1. As shown Figure 4C, which reports MOR-mediated outward currents evoked by uncaging nMNV-LE, 10/11 cells had a response in the presence of TIPP-Psi. Only 1 cell was unresponsive, using a threshold of 2 pA to indicate a response.

2. As shown figure 4J, which reports the currents evoked by uncaging CYLE (PV-Cre;TdTom condition), 12/14 cells responded.

3. In Figure 6B-D, which reports the currents evoked by uncaging CNV-Y-DAMGO, although the amplitude distributions are not shown, 19/19 PV+ cells responded.

4. Considering all of these experiments, 41/44 recorded PV-BCs yielded MOR-mediated currents, suggesting that non-responders that lack MOR entirely are unlikely to account for the observation that the average LE-evoked MOR-mediated current is smaller than the average DOR-mediated current.

b. We tested two MOR agonists in this study: LE and DAMGO. DAMGO is thought to maximally engage G protein signaling and, by extension, GIRK activation. As shown in Figure 6D, currents produced by maximal uncaging of CNV-Y-DAMGO (1 uM) were ~60 pA in amplitude, which is smaller than the nMNV-LE (3 uM)-evoked currents at DOR in CTOP (Figure 4C), which averaged ~100 pA. The nMNV-LE (3 uM)-evoked currents at MOR in Tipp-Psi were ~ 25 pA in amplitude. The greater efficacy of DAMGO uncaging could be attributed to its resistance toward protease activity, in both the caged and uncaged form, which may enhance the concentration of photoreleased agonist that is able to reach the receptor and its spread compared to LE, such that DAMGO activates MORs over a larger area of dendrites than LE due to diffusion. That proteases limit peptide agonist potency and diffusion in brain slices is well established (Williams, Christie, North and Roques, J. Pharmacol Exp Ther, 1987, 243(1), 397-401; Banghart and Sabatini, Neuron, 2012, 73(2), 249-59). This may also simply reflect a greater efficacy of DAMGO than LE at MOR, although this is not well documented. Regardless, using these two different caged agonists, we observe that DOR produces larger somatodendritic currents than MOR. We added a statement to the discussion pointing out that caged-DAMGO-evoked currents at MOR were smaller than those obtained with caged LE in CTOP: “Reinforcing the dominant role of DOR, the somato-dendritic currents obtained with maximal photorelease of caged DAMGO, a full agonist of MOR G protein signaling (Williams et al., 2013), were also smaller than those produced by LE uncaging in CTOP (currents were apparent 19/19 cells).”

In other work that is not included in this publication, we have measured outward currents evoked by uncaging the small molecule MOR agonist oxymorphone under ~identical conditions, and also found the responses to be quite small (~10 pA). We do not wish to include such data in this manuscript, as a separate manuscript describing that molecule in other applications is currently in preparation.

As covered in the discussion, we would also like to emphasize here that DOR exhibited much faster kinetics than MOR, both when activating somato-dendritic GIRKs, but also, clearly at least at one frequency of stimulation when suppressing synaptic transmission. MOR, instead, was profoundly slower in both assays (tau ~800 ms), when activated with either caged LE or caged DAMGO (they yielded similar time constants). Yet increasing the expression level of MOR increased both the rate of GIRK activation and peak current amplitude. Together these results strongly support our hypothesis that MOR signaling in PV-BCs is less efficient than DOR due to a lower abundance of functional receptors.

To leave room for the possibility that other MOR agonists might be more efficacious in PV-BCs than LE and DAMGO, we restricted our wording to state that DOR dominates the response to enkephalin.

Without additional experiments:

3. The statistical analysis needs to be comprehensively revised, please see specific recommendations from the Reviewers.

Thank you for these constructive critiques. This feedback has improved the rigor of our study by correcting aspects of our statistical analysis. Because most, but not all, of our datasets were normally distributed, we inappropriately used primarily parametric statistics throughout, in order to run ANOVAs when assessing multiple variables. We have overhauled the statistical analysis to include the determination of normality for each dataset, and employed the appropriate parametric and non-parametric tests, with attention to the reviewers’ suggestions. A table is provided in response to Reviewer 3’s comments that summarizes the changes. The new analyses did not change the conclusions of our study or the interpretation of any single experiment. As suggested and described in detail below, we were more precise in our interpretation of several experiments (e.g. the rate determinations in Figure 2G) to more accurately reflect the statistical outcomes.

4. The wording used by the authors to describe their experiments and findings needs to be more precise and careful; the experiments performed probe cellular functional interactions between the two receptors, not dimerization.

We strongly agree with this sentiment and were very careful to not use the word “dimer” in our manuscript. In fact, we use “functional interactions” throughout with this point in mind exactly. In the introduction, beginning with the first paragraph, we very carefully described the various forms of possible functional interactions between the two receptors, which includes potential heteromerization as only one of several possibilities. A text search of the submitted manuscript did identify one mistaken use of the word “heterodimer” in a figure legend and that has been removed, as well as another intentional use in the discussion concerning models posed by other labs. When specifically discussing the heteromer hypothesis, which other groups have proposed to involve “heterodimers,” we prefer to use the word “heteromer,” as to not imply strictly dimeric interactions. In contrast, the companion manuscript by Arttamangkul et al., uses the term “heterodimer” broadly in reference to the functional interactions investigated in their study.

As described in the introduction and discussion in detail, we assessed our data in the context of multiple potential forms of functional interactions: cross-sensitization (by agonizing both receptors), cross-desensitization (heterologous desensitization), and heteromers (specifically allosteric sensitization, as evidenced with an antagonist for one receptor), all of which would manifest differently. As stated in the abstract and discussion, we concluded that our data reveal a great deal of occlusion and no evidence for cross-desensitization or sensitization, either by co-activation of both receptors, or via allosteric interactions between heteromers.

Admittedly, we did not perform biochemical or molecular imaging experiments to probe for physical interactions between MOR and DOR. Instead we used functional measures of receptor signaling-dependent cellular physiology to evaluate the proposed model for MOR/DOR heteromer signaling (among the other forms of possible functional interactions discussed). This is arguably THE most relevant measure in the context of a neuron embedded in its natural neural circuit. We added to the abstract “Thus, despite largely redundant and convergent signaling, MORs and DORs do not functionally interact in PV-BCs in a way that impacts somato-dendritic potassium currents or synaptic transmission.” to underscore this point. Also, in the introduction, we added “Thus, in naïve mice, unequivocal evidence for functional interactions between endogenous MORs and DORs in the same neurons, and in particular, for the existence of MOR/DOR heteromers that impact neuronal physiology, is lacking.

Given that we described several possibilities and assessed them specifically in the introduction, text, and discussion, and have added several statements clarifying that we are probing for heteromers that impact cellular physiology specifically, we hope that the language used in our manuscript is now precise and careful enough to accurately describe how our data reflect the various forms of functional interactions that may occur in neurons to impact their function.

5. The methods need to be described more thoroughly, with the inclusion of additional details including the sex and age of the animals, blinding of experimenters, PPR experiments, new CNV-Y-DAMGO ligand, and SNC162 selectivity. Please see the specific recommendations from the Reviewers.

We regret these omissions. We have added the sex and ages of animals used to the methods and indicated that experimenters were not blind to the pharmacological conditions employed. We also recalculated PPR as requested below describe the PPR calculation in more detail.

The new CNV-Y-DAMGO ligand is reported in a short pre-print that has been uploaded to BioRXiv prior to resubmission of this manuscript. A draft of this pre-print describing CNV-Y-DAMGO was, in fact, supplied to the editors with the initial submission, according to eLife guidelines. Perhaps it was not provided to the reviewers or simply overlooked during the initial review process – there is no mention of it in any review. Nonetheless, because preprints may be cited by eLife papers, assuming the reviewers accept this as sufficient validation of CNV-Y-DAMGO, this concern should be alleviated.

https://www.biorxiv.org/content/10.1101/2021.09.13.460181v1

A reference indicating the superior selectivity of SNC162 (Knapp et al.) has been added to the bibliography. https://jpet.aspetjournals.org/content/277/3/1284.long.

Reviewer #1:

[…] – One of the most interesting findings reported here is that MOR signaling is relatively inefficient in PV+ neurons. Supporting Figure S1 shows that not all PV+ neurons express DOR and MOR, consistent with published RNA-seq data. How was MOR expression tracked in individual PV+ recorded neurons and taken into account when interpreting the data? For example, in Figure 4C, while the authors state that "blocking MORs with CTOP had no measurable effect", it seems that there is considerable variability in the CTOP effect, with some cells showing a clear reduction in current amplitude compared to ACSF. Could it be that the cells in which no CTOP effect was observed in fact did not express MOR? This would be consistent with findings in cortical PV+ neurons, which consistently express DOR but where MOR expression is more variable (Birdsong et al. 2019 eLife, Smith et al. 2018 eLife). This clarification is important for the interpretation of many experiments. To confirm that MOR signaling is relatively inefficient in CA1 PV+ neurons, it would be helpful to test the effects of additional MOR-selective agonists on membrane potential or holding current.

Thank you for your interest in this surprising finding. The data in Figure 4C under each pharmacological condition were obtained from different cells. We did not obtain currents before and after CTOP addition, as such antagonist flow-in experiments consume huge quantities of caged peptide. Instead we compared populations of cells recorded under each condition. We discuss the issue of MOR expression above in more depth. Frankly, we were quite surprised by the finding that CTOP did not reduce the current at all compared to control. Our interpretation, as depicted in Figure 7, is that DORs can access the same pool of GIRKs that are recruited by MORs, but not vice-versa. This might be explained, at least in part, by a relatively low abundance of MOR compared to DOR. As discussed, we also tested caged DAMGO, a full, agonist of MOR G protein signaling, and found that the maximal current evoked was still smaller than the DOR-isolating condition with LE.

– Figure 4D. Are the ACSF and CTOP peak currents statistically different? The authors indicate that "opioid-dose response curves in the presence of each antagonist revealed a larger DOR-mediated than MOR-mediated" current; however, it is unclear that this experiment revealed any MOR-mediated current at all.

The ACSF and CTOP peak currents are not statistically different. We isolated the MOR-mediated current using TIPP-Psi (plotted in blue). It peaks at about 25 pA (84 mW). The DOR-mediated current is plotted in red (CTOP). The ACSF and CTOP-mediated currents were statistically different at intermediate light powers, but we did not include this analysis in the manuscript and do not make claims about it, as we are unable easily explain it, and the effect sizes are small. Based on our interpretation that DOR can activate the same GIRKs as MOR (Figure 7 model), but not vice-versa, there may indeed be no MOR-mediated current in ACSF, as it is occluded by DOR. Yet it is revealed in TIPP-Psi.

– Figure 4H. What is the expression level and subcellular distribution of the hMORs, and is it comparable to that of the native MORs in cells where MOR-mediated responses are recorded? A histological analysis would be useful, if only as a control to confirm hMOR expression in PV+ cells.

In this experiment the goal was to overexpress MOR. It is difficult to judge the relative expression level and distribution compared to native MOR. We are highly confident of hMOR expression however, as the construct includes mCherry separated from MOR with a T2A self-cleaving peptide, such that mCherry fluorescence should scale stoichiometrically with MOR expression. As shown in Figure S2C, the peak amplitude and rise time of the caged LE-evoked current correlates well with mCherry fluorescence, which strongly suggests expression of functional receptor.

– The authors indicate that they "chose SNC162 for its exceptional selectivity for DOR over MOR". It is unclear that SNC162 selectivity is superior to that of SNC80 or deltorphin II, the agonists typically used to interrogate DOR function. To justify their statement, can the authors provide published KD (or KI) data for each receptor and selectivity ratios for these three ligands?

We cited the paper demonstrating this (Knapp et al). From their abstract:

“The most selective delta receptor ligand (SNC162) differed from SNC80 by the absence of the 3-methoxy substitution of the benzyl ring. The Ki for SNC162 at the delta receptor (0.625 nM) was over 8700-fold lower than that at the mu receptor (5500 nM), making this the most selective delta receptor ligand available.”

– Can the authors provide additional information on CNV-Y-DAMGO such as its KD for MOR, selectivity for MOR vs DOR, and whether CNV-Y-DAMGO effects are lost in Oprm1 KO mice or in the presence of CTOP? At present, the utility of CNV-Y-DAMGO versus the well characterized agonist DAMGO for Figure 6 experiments is not obvious.

A “supporting manuscript” containing many of these experiments was provided to eLife with our initial submission. Regretfully, it was apparently not provided to and/or read by the reviewers. We hope that this manuscript, which is now available as a pre-print, will satisfy any concerns about the validity of CNV-Y-DAMGO.

– The interrogation of DOR-MOR functional interactions in PV+ hippocampal neurons is unidimensional and restricted to neurophysiological effects. Ideally, one would want to clarify, or at least discuss, the function of DOR or MOR and their potential interactions in PV+ hippocampal neurons at other levels of opioid receptor biology, such as at the behavioral levels, on learning and memory.

Thank you for the suggestion. We have elaborated on our discussion of β-endorphin vs enkephalin signaling in hippocampus to suggest that stress-induced β-endorphin might act on MOR to occlude enkephalin actions at DOR that mediate memory formation or retrieval. While under review, a manuscript from the Siegelbaum Lab was published implicating DOR-mediated LTD of PV-BC synapses in CA2 in social memory. We have included this manuscript in the discussion as well.

– In the Introduction, the study by Wang et al. 2018 is described as a trafficking study. However, this study did not only use imaging of receptor trafficking to examine DOR-MOR interactions in neurons that co-express both receptors, but also electrophysiological recordings and desensitization protocols. These electrophysiological studies showed that the pharmacological elimination of DOR from the plasma membrane did not affect the ability of MOR to signal and activate GIRK channels. Additionally, Wang et al. verified MOR and DOR co-expression in recorded cells and included other levels of analysis, including behavioral studies. Since the aims of the Wang et al. 2018 study are conceptually very similar to those of the present study, and both studies conclude that MOR and DOR signal independently, it is important that these earlier findings are presented accurately to the reader in the Introduction and Discussion.

Thank you for pointing this out. We regret this omission and did not intend to imply that it was only a trafficking study, only that we wanted to highlight that aspect of their findings, in particular. We agree that the electrophysiology experiments employed are highly relevant and have updated the introduction to include this aspect of the study as well.

– It would also be useful to the reader to discuss the literature claiming that DOR is a dormant receptor, without function in the absence of priming stimulus, and clarify that the results presented here refute this idea.

We appreciate this point. We had considered discussing this topic but decided that it was beyond of the scope of our study. Our GIRK data strongly refute this idea in the somatodendritic compartment. However, in our synaptic transmission studies, the stimuli used to establish a baseline IPSC could, in principle, function as this priming stimulus.

– Please check the list of References. For example the Bean 1989 paper is cited in the Results but absent from the References section.

Thank you for pointing this out. We have ensured its inclusion.

Reviewer #2:

The authors then make use of photopharmacology and calcium imaging to demonstrate that both MOR and DOR suppress presynaptic voltage gated calcium channels on PV interneurons. They demonstrate that DOR signaling is the primary driver of somato-dendritic inhibition through coupling to GIRK channels. Given that MOR and DOR were expressed on overlapping populations of neurons, they examine whether these receptors signaling as "functional heterodimers." However, they found no evidence of heterologous desensitization or functional heterodimerization, suggesting these receptors to not dimerize in hippocampal PV interneurons using the techniques they use here. It still remains rather unclear what we all mean when we say "dimers" for Class A receptors anyways. Maybe they quickly kiss one another during anterograde transport, or maybe it is packaging for internalized and degraded receptors. The authors still leave those questions very unanswered, but the study remains important in other ways and adds to our understanding of GPCR interactions. I would suggest at the outset that the authors are more careful with the term dimers throughout and clarify what they mean by the term.

We appreciate the overall positive assessment of our work. As discussed above and below, we did not use the term “functional heterodimers” or “dimers” in our manuscript. In a subset of experiments, we specifically intended to test a model put forth by Gomez et al. in 2004 in which DOR antagonists enhance MOR signaling (and vice versa), presumably through allosteric interactions between heteromeric receptors. Uniquely, our study examines this model using multiple measurements of cellular physiology. We did not intend to address whether or not heterodimers can exist between MOR and DOR in any form, but rather whether the synergistic model that has gained so much traction is physiologically relevant in one of the relatively rare classes of neurons in the brain that co-express both receptors.

Strengths:

This is a highly rigorous set of experiments, using complementary approaches to understand the functional interaction between MOR and DOR receptors in hippocampal PV interneurons. The techniques are well suited to address these questions, and the authors make use of novel photo-uncageable opioid ligands in combination with traditional pharmacological approaches to probe these interactions. Decades of research in heterologous expression systems have demonstrated that MOR and DOR can functionally dimerize, yet few studies have examined this in native systems. This study provides strong evidence for the lack of functional dimerization in PV interneurons.

Weaknesses: the central limitations of this study relation to the terminology used, the use of electrical stimulation in some cases, and the cell type selectivity.

We have done our best to clarify the terminology used and to address the limitations of using electrical stimulation, which is less cell-type selective than optogenetic stimulation.

Comments for the authors:

1) There is methodological concern with the surprising switch from optogenetic to electrical stimulation of putative PV input to pyramidal neurons. The authors mention that this is to "improve experimental throughput." However, this explanation is not sufficient given the caveats of this approach. First, the authors attempt to demonstrate that inhibitory input from CCK interneurons is not recruited by this stimulation paradigm by examining cannabinoid agonist induced depression, which they mentioned was minimal. However, 25% depression should not be dismissed, as only a subset of inhibitory interneurons in the hippocampus express CB1 (mainly CCK interneurons). This suggests that the electrical stimulation paradigm is likely also recruiting CCK input as well. While this may not in and of itself be an issue given the low expression of opioid receptors on this population, other hippocampal interneurons, such as somatostatin positive interneurons, do express opioid receptors at a high level. Therefore, the authors cannot conclude with certainty that they are only recording from PV input. There are also noticeable differences between the optical and electrical stimulation paradigms, as MOR agonist application with optical stimulation induces an increase in the PPR while there is no significant change with electrical stimulation. Lastly, the paper they site as justification for this electrical stimulation paradigm does not use bipolar electrical stimulation at any point; thus using this paper as justification is incorrect. Therefore, they should do one of three things: 1). Demonstrate these effects to do not hold for other populations of hippocampal interneurons, 2). Replicate more of their PV projection findings using optogenetic approaches, 3). Remove mention of PV and say inhibitory input instead.

As described above, we agree with this general concern about the selectivity of electrical stimulation for recruiting PV terminals and have modified the text to include concerns about optical cross-talk to justify the transition to electrical stimulation. We have also chosen option 2 and replicated the lack of effect of Tipp-Psi on DAMGO-mediated synaptic suppression using optogenetic stimulation of PV-Cre axons.

The manuscript cited (Glickfeld et. al) does not refer to the electrical stimulation paradigm but the functional segregation of CB1R-sensitive regular-spiking (presumably CCK) basket cells and MOR-sensitive fast-spiking (presumably PV) basket cells. Thank you for noting this. Our writing was not clear. An additional sentence clarifying this point has been added.

2) Dimerization is a term that is frankly used for GPCRs in strange ways (think about how pentameric ion channels are described for example to reevaluate the meaning here), and so "functional heteromers" seems less accurate even. The authors need to really clarify more in the intro and discussion these distinctions and make it more clear what they mean by their terms. They've certainly provided nice data with respect to functional "interactions" between receptors, but the TIRF experiments are missing, as are critical biochemical experiments, or FRET studies to definitively rule out all interactions. There readouts limit this, as does their language about it need some refining.

A text search of our manuscript did not reveal the term “functional heteromer” or “functional heterodimer,” although to us this term might refer to a heteromer that is functionally relevant to cellular physiology. We are left to wonder if this comment was mistakenly directed at our manuscript instead of the companion paper by Attarmangkul et al.. As described above, we intentionally avoided the term “dimer” and it was only found in a single figure legend, mistakenly, in our manuscript.

Yet we would like to take this opportunity to reiterate that we think that our use of neuronal physiology as a readout is largely what distinguishes our study from others and makes our work important. As described in the manuscript, most studies into MOR/DOR heteromers involve assays with heterologous expression in order to incorporate imaging labels, or in cultured cells, or using biochemical methods that cannot reveal neurophysiological function. Thus the physiological relevance of such work has remained questionable. Our experiments assess only physiologically relevant interactions that impact somato-dendritic GIRK currents (which in turn impact cellular excitability) and synaptic transmission. While there are of course additional neuronal functions that could be studied (dendritic integration, synaptic plasticity, nuclear signaling, gene expression changes etc.), our study is one of the first to rigorously explore any aspect of neurophysiological function in the context of MOR/DOR functional interactions.

Reviewer #3:

[…] 1. There are concerns regarding the statistical tests performed and how the data are interpreted based upon these analyses. The methods states that all data were treated as parametric, but a justification for this is not provided, and it is not clear that this is accurate because the text reports the use of non-parametric analyses. It is apparent that the authors are interested in comparing cellular responses mediated by MORs and DORs, yet in most multiple comparison statistical tests, comparisons are only made between receptor antagonists and control and not to each other. Statistical assessment of the role of specific ion channels in the effects of MOR and DOR activation were not appropriately performed. In many places, statistical significance is ignored and results are treated as significantly different when the analyses do not support these conclusions. Therefore, some of the results should be interpreted with caution. Order effects of antagonists are considered in Figure 3, but not other figures. It was not indicated if investigator blinding to treatment was used.

We regret not doing a better job with this important component of our study. Initially, we indeed used a mix of parametric and non-parametric statistics, but not all parametric tests were justified by tests for normality first. So our statement regarding all data being treated as parametric was incorrect. Detailed responses are provided below under Recommendations.

2. The sex of the animals used was not reported. The age of the animals also spanned a large range (postnatal days 15-35). This is a major concern as there is considerable brain development that occurs over this age range that could produce physiological changes in the hippocampus. It is important to take age and sex into account in the interpretation of the data.

We apologize for the omission. Both sexes were used equally in all experiments. We also indicated age for each experiment in the methods. Only a few experiments requiring gene expression were conducted in ~P28-P41 animals. Because PV promotor activity does not become strong until ~P18-22, older animals were required for optogenetic experiments in order to achieve adequate opsin or mCh-2A-hMOR expression. Notably, the MOR and DOR sensitivity observed in our recordings from P15-P32 animals using electrical stimulation (with caveats of course) are not obviously different from those observed using optogenetic stimulation in the older mice.

3. Heterologous desensitization was tested for somatodendritically-localized receptors, but not for synaptic receptors, given that they stated that presynaptic MORs desensitize (it was not specifically tested if DORs do). Given that there was mutual occlusion at the terminals, it is important to note whether these receptors undergo such heterologous desensitization, even if they don't heterodimerize.

Although we were interested in this point as well, we reasoned that the relatively small amount of desensitization observed would make this a very difficult experiment to interpret, as statistically detecting changes in DOR, for example, after only ~20% desensitization of MOR, could be very challenging.

4. The authors propose that DORs in the basket cells play a larger role in modulating basket cell function than MORs, and based on their data, this may be true under conditions where enkephalin predominates. Overall, the authors' conclusions are likely accurate, however it is conceivable that the results are the outcomes of testing a limited set of ligands. The authors rightly suggest that as far as physiological conditions are the focus, circulating β-endorphin could produce a different outcome. However, exogenous opioids (e.g. prescription painkillers, illicit opioids) could also differentially engage MORs and DORs and produce different outcomes due to differences in affinity or even functional selectivity.

We generally agree with this statement and note that DAMGO is considered to be a full, agonist of G protein signaling at MOR and that the DAMGO-evoked MOR-mediated currents were still smaller than the DOR-mediated currents obtained with caged LE in TIPP-Psi. Despite this, we have carefully chosen our wording to emphasize that DOR dominates the response to enkephalin, as to leave room for the possibility that other mu agonists might be more efficacious in PV-BCs than LE and DAMGO.

5. Indicate the sex and ages of the animals used for each experiment.

This information has been added to the methods.

6. Resolve discrepancy between actual statistical tests used and the statement in the methods that all data were treated as parametric. Were data tested for normality? Were outliers identified (there are a number of places where there appeared to be outliers)?

Author response table 1
FigureNormal?Results changed?
1DYesOne way ANOVANo
1E newNo for BL(DAM)Wilcoxon test, both significantNo
1IYesOne way ANOVANo
1J newNo for BL(DAM)Wilcoxon test, DAMGO p = 0.0186, SNC p = 0.058DAMGO significant, SNC no longer significant
S1EYesOne way ANOVA w/ Tukey (changed from Dunnett’s)No
S1GYesTwo way ANOVANo
S1HYesPaired t-testNew data
S1INoSkillings-Mack non-parametric test for grouped dataNew data
2GNoKruskal-Wallis (non-parametric): only significant difference is for 20hz, between ACSF and TIPP-PsiNo
3CNoFriedman test with Dunn’s multiple comparisonsNo
3DNoFriedman test with Dunn’s multiple comparisonsNo
4CNoKruskal-Wallis (non-parametric) with Dunn’s multiple comparisonsNo
4GNoKruskal-Wallis (non-parametric) with Dunn’s multiple comparisonsNo
4JYesUnpaired t-testNo
4KYesUnpaired t-testNo
S2BYesOne way ANOVA, and t-test for CTOP condition onlyNo
6CNoMann-Whitney test, p = 0.4252No
6HNoMann-Whitney test, p = 0.2824No
S3BYesUnpaired t-test, p = 0.7518No

7. Dunnett's multiple comparison post hoc test is not the appropriate test for the assessment of their findings, especially as they are often making statements of comparisons between the roles of MOR and DOR. Tukey's multiple comparisons test is the more appropriate post hoc analysis. They used this test in Figure 4, but not in other figures.

All the Dunnett’s multiple comparisons post hoc tests have been replaced with either Tukey’s multiple comparisons (for parametric data) or with Kruskal-Wallis tests with Dunn’s multiple comparisons (for non-parametric data).

8. Resolve why order effects were tested in Figure 3, but not other figures?

We did not intend to imply that we were testing order effects. We did not include a specific statistical test to address the effect of the order of drug addiction. We simply tested the MOR and DOR agonists independently, and then to determine the effect of both drugs together, added the 2nd drug. Rather than pooling the DAMGO/SNC162 data, we analyzed them separately. In principle, we could have done the same thing in Figure 1D and I but these experiments were not conducted as systematically to obtain the “both” condition so those data are pooled.

9. Statistical significance was treated very lightly throughout the manuscript. For example, components of Figures 1J, S1E, 2G, S2B were discussed as if they were significant (or selectively interpreted if one component was significant and another was not). For example, I am not convinced that DAMGO doesn't occlude the effect of WIN55,212-2 in S1E.

We have adjusted the text to accurately reflect the significance of the datasets.

For Figure S1E, we now state that “WIN55 in the presence of DAMGO produced only slightly more suppression than DAMGO alone, but this effect was not significant, suggesting some occlusion.”

For Figure 2G, we added a statement clarifying that the only difference found was between 20 Hz ACSF and 20 Hz TIPP-Psi and included the term “trend” to discuss the results at 10 and 50 Hz.

Figure S2B is discussed below.

10. Figure S2B was indicated to show the role of GIRKs and HCNs in the effects of receptor activation. A one-way ANOVA was not the appropriate statistical test in this case as all this did was show that Ba2+ had no difference in its effect regardless of the drug treatment, but does not specifically test the involvement of different ion channels.

Because we only have data for Ba2+ with ZD7288 in one condition (CTOP), we were unable to run a two-way ANOVA to test for the interactions between the ion channels. We decided to carry out a one-way ANOVA for the Ba2+ only conditions across ACSF, CTOP, and TIPP-Psi, and found no differences. We then carried out a t-test between the Ba2+ only and the Ba2+ with ZD7288 conditions in CTOP and also found no difference.

11. It was stated that DAMGO produced desensitization in Figure 1C,H. Was this statistically determined?

We have added Figure S1H that quantifies the degree of desensitization produced by DAMGO and SNC162 in both experiments. DAMGO produced desensitization 8-10 minutes after bath application for both optogenetic stimulation and electrical stimulation (Figure S1H) (opto: p = 0.0038, estim: p = 0.0001, paired t-test). SNC162 produced desensitization only with optogenetic stimulation, but not electrical stimulation (opto: p = 0.048, estim: p = 0.010, paired t-test). We compared these effects and found that DAMGO produces more desensitization than SNC162 using both stimulation protocols.

12. The methods do not describe the performance/analysis of PPR. How was amplitude of the second peak determined as the decay from the first hadn't completely returned to baseline?

In the initial analysis, it was simply calculated as the absolute peak amplitude. We have re-calculated the PPR after subtracting the residual Peak 1 current from Peak 2 and described this calculation in the methods.

13. The authors cite a publication in preparation as evidence of validation of their caged DAMGO peptide. This is worrisome for the interpretation of their findings without any provided validation here.

As described above, a draft of this manuscript was provided with the initial submission to eLife, and has now been uploaded to BioRxiv as a preprint.

14. The authors looked at heterologous desensitization in somatodendritic signaling, but not at synaptic terminals. This is especially important as the two receptors are mutually occlusive at the terminals. Even if they are not dimers, they could produce heterologous desensitization. At the very least, the authors need to justify why they didn't explore this at synaptic terminals or present this as a limitation of their study.

Presynaptic Gi/o-coupled GPCRs typically do not desensitize (Pennock, Dicken and Hentges, J. Neurosci. 2012, 32(30), 10192-200). The amount of desensitization in presynaptic receptors was relatively small (20-25%) and was most obvious only with DAMGO, so we didn’t think that we would be able to resolve changes in opioid efficacy after such partial desensitization in synaptic terminals. We have added a statement to the discussion to point out this limitation.

15. Why do the authors think that they had less suppression as a result of uncaging than they did with bath application (Figure 1I)?

We likely observed less suppression with uncaging because the photoreleased peptide is somewhat spatially restricted and does not access the entire dendritic tree, in contrast to bath application. Thus fewer receptors are activated on each cell when uncaging through a 60x objective.

16. Some line colors in a number of figure panels are difficult to resolve due to their similarities. For example, Figure 5F-H, Figure 6.

Thank you we have adjusted the colors.

17. Include a statement of investigator blinding.

The lack of blinding has been added to the methods.

https://doi.org/10.7554/eLife.69746.sa2

Article and author information

Author details

  1. Xinyi Jenny He

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3884-0596
  2. Janki Patel

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  3. Connor E Weiss

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  4. Xiang Ma

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Methodology, Resources
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9164-8608
  5. Brenda L Bloodgood

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Methodology, Resources, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4797-9119
  6. Matthew R Banghart

    Division of Biological Sciences, Neurobiology Section, University of California, San Diego, La Jolla, United States
    Contribution
    Conceptualization, Funding acquisition, Project administration, Resources, Writing – original draft, Writing – review and editing
    For correspondence
    mbanghart@ucsd.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7248-2932

Funding

National Institute on Drug Abuse (R00DA034648)

  • Matthew Ryan Banghart

National Institute of General Medical Sciences (R35GM133802)

  • Matthew Ryan Banghart

National Institute of Neurological Disorders and Stroke (U01NS113295)

  • Matthew Ryan Banghart

National Institute of Mental Health (U01NS113295)

  • Matthew Ryan Banghart

Brain and Behavior Research Foundation (NARSAD Young Investigators Award)

  • Matthew Ryan Banghart

Esther A. and Joseph Klingenstein Fund (Klingenstein-Simons Fellowship in Neuroscience)

  • Matthew Ryan Banghart

National Institute of General Medical Sciences (T32GM007240)

  • Xinyi Jenny He

National Institute of Neurological Disorders and Stroke (R01NS111162)

  • Brenda L Bloodgood

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank the National Institute on Drug Abuse Drug Supply Program (NDSP) for generously providing pharmacological reagents; L Sancho and E Campbell for training and assistance with two-photon microscopy; BK Lim for reagents for adenoassociated virus production; E Berg for genotyping, animal husbandry, adenoassociated virus production and administrative assistance; J Isaacson, W Birdsong, J Williams, M Lovett-Barron, and members of the Banghart Lab for helpful discussions.

Ethics

All procedures were performed in accordance with protocols approved by the University of California San Diego Institutional Animal Care and Use Committee (IACUC) following guidelines described in the the US National Institutes of Health Guide for Care and Use of Laboratory Animals (UCSD IACUC protocol S16171). All surgery was performed under isoflurane anesthesia.

Senior Editor

  1. Lu Chen, Stanford University, United States

Reviewing Editor

  1. Gregory Scherrer, UNC School of Medicine, United States

Reviewers

  1. Gregory Scherrer, UNC School of Medicine, United States
  2. Brady K Atwood, Indiana University School of Medicine, United States

Publication history

  1. Preprint posted: April 24, 2021 (view preprint)
  2. Received: May 20, 2021
  3. Accepted: November 16, 2021
  4. Accepted Manuscript published: November 17, 2021 (version 1)
  5. Accepted Manuscript updated: November 17, 2021 (version 2)
  6. Version of Record published: December 29, 2021 (version 3)

Copyright

© 2021, He et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Xinyi Jenny He
  2. Janki Patel
  3. Connor E Weiss
  4. Xiang Ma
  5. Brenda L Bloodgood
  6. Matthew R Banghart
(2021)
Convergent, functionally independent signaling by mu and delta opioid receptors in hippocampal parvalbumin interneurons
eLife 10:e69746.
https://doi.org/10.7554/eLife.69746

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