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Compartment-specific opioid receptor signaling is selectively modulated by different dynorphin peptides

  1. Jennifer M Kunselman
  2. Achla Gupta
  3. Ivone Gomes
  4. Lakshmi A Devi
  5. Manojkumar A Puthenveedu  Is a corresponding author
  1. Cellular and Molecular Biology Training Program, University of Michigan Medical School, United States
  2. Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, United States
  3. Department of Pharmacology, University of Michigan Medical School, United States
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Cite this article as: eLife 2021;10:e60270 doi: 10.7554/eLife.60270

Abstract

Many signal transduction systems have an apparent redundancy built into them, where multiple physiological agonists activate the same receptors. Whether this is true redundancy, or whether this provides an as-yet unrecognized specificity in downstream signaling, is not well understood. We address this question using the kappa opioid receptor (KOR), a physiologically relevant G protein-coupled receptor (GPCR) that is activated by multiple members of the Dynorphin family of opioid peptides. We show that two related peptides, Dynorphin A and Dynorphin B, bind and activate KOR to similar extents in mammalian neuroendocrine cells and rat striatal neurons, but localize KOR to distinct intracellular compartments and drive different post-endocytic fates of the receptor. Strikingly, localization of KOR to the degradative pathway by Dynorphin A induces sustained KOR signaling from these compartments. Our results suggest that seemingly redundant endogenous peptides can fine-tune signaling by regulating the spatiotemporal profile of KOR signaling.

Introduction

The endogenous opioid system provides an excellent and physiologically relevant example to study redundancy in signaling systems in our body. Over 20 endogenous opioids have been identified, all of which preferentially activate one of three opioid receptors – delta, kappa, and mu opioid receptors – which are all members of the G protein-coupled receptor (GPCR) family of proteins (Gendron et al., 2016; Chavkin, 2013; Williams et al., 2013). All these opioid peptides activate their cognate GPCRs broadly at similar levels in most of the readouts that have been used to measure activation (Sternini et al., 2013). Whether all these opioid peptides are truly redundant or whether they contribute to signaling diversity beyond the initial signaling has been a long-standing question in the field.

Signaling from intracellular compartments, after the initial signaling from the surface, is emerging as a key determinant of the downstream consequences of receptor activation (Irannejad et al., 2013; Yarwood et al., 2017; Eichel and von Zastrow, 2018). While this is still an emerging field, a growing body of evidence suggests that GPCRs are active in endosomes and other intracellular compartments, and that receptors in endosomes can cause distinct signaling outcomes compared to receptors on the cell surface (Vilardaga et al., 2014; Bowman et al., 2016; Stoeber et al., 2018). Receptors rapidly and dynamically move between intracellular compartments and the surface by trafficking. Trafficking could therefore act as a master regulator of GPCR signaling by selectively amplifying signals from specific locations (Weinberg et al., 2019; Hanyaloglu, 2018). Whether physiological systems take advantage of trafficking to localize receptors to different compartments and dictate location-biased signaling, however, is still unanswered.

Here we bridge both questions by asking whether different endogenous opioid peptides can sort receptors to distinct intracellular compartments and drive different location-biased signaling outcomes. Using the kappa opioid receptor (KOR) as a model GPCR, we show that although related Dynorphin peptides can activate KOR on the surface to a similar extent, they induce different trafficking fates and endosomal localization of the receptor. Dyn B predominantly localized KOR to Rab11 recycling endosomes and caused KOR recycling, while Dyn A predominantly localized KOR to late endosomes and caused KOR degradation. Strikingly, Dyn A-activated KOR, but not Dyn B-activated KOR, was in an active conformation in lysosomes and induced cAMP signaling from intracellular compartments. The differences are likely a result of differences in how the peptides activate KOR, as opposed to peptide stability. Our results show that seemingly redundant opioid peptides, which activate receptors on the surface to similar levels, can drive spatially and temporally different signaling outcomes by differentially sorting receptors to distinct endosomal compartments after internalization.

Results

To examine activation and internalization of KOR by Dynorphin peptides we first focused on four physiologically relevant endogenous peptides – Dynorphin A17 (Dyn A), Dynorphin A8 (Dyn A8), Dynorphin B (Dyn B), and ɑ-neoendorphin (ɑ-neo). These peptides differ mainly in their length and C-terminal peptide sequence (Figure 1A). We carried out our studies using neuroendocrine PC-12 cells stably expressing KOR tagged with a pH-sensitive GFP (SpH-KOR) (Sankaranarayanan et al., 2000) that facilitates visualization of agonist-mediated KOR trafficking, and CHO cells stably expressing Flag epitope tagged KOR (CHO-KOR). Consistent with previous findings, we find that in these cells Dyn A, Dyn A8, Dyn B, and ɑ-neo bind KOR at relatively comparable affinities (Table 1).

Figure 1 with 1 supplement see all
Initial activation and internalization of KOR by Dynorphins are comparable.

(A) Schematic of the regions of Pro-dynorphin from which Dynorphin A8 (Dyn A8), Dynorphin A (Dyn A), Dynorphin B (Dyn B), and α-neoendorphin (α-neo) peptides are generated, showing that Dyn A and Dyn B are processed from adjacent regions. (B) Dyn A8, Dyn A, Dyn B, and α-neo (1 μM) inhibit intracellular cAMP levels to a similar extent in PC12 cells stably expressing SpH-KOR. Values were normalized to basal cAMP measurements in the absence of peptide, which were set as 100% (mean ± SEM shown). (C) Representative TIR-FM images of PC12 cells stably expressing SpH-KOR treated with Dyn A8, Dyn A, Dyn B, and α-neo (1 μM) show roughly similar agonist-mediated receptor clustering at the cell surface following 1 min treatment. Scale bar = 2 µm. (D) Quantitation of the loss of surface SpH-KOR fluorescence, as an index of internalization, after 5 min of treatment with each peptide (1 μM), normalized to surface fluorescence before agonist treatment, show similar levels of internalization for all four peptides (mean ± SEM shown, Dyn A: n = 10 cells; Dyn B: n = 10 cells; Dyn A8: n = 10 cells; ɑ-neo: n = 11 cells).

Table 1
Displacement binding parameters for Dynorphin peptides at PC12 SPH-KOR and CHO-KOR cells.
PC12 SpH-KOR cellsCHO-KOR cells
LigandLow Ki (nM)High Ki (nM)% Bmax at 10 μMnHLow Ki (nM)High Ki (nM)% Bmax at 10 μMnH
Dyn A856.9 ± 0.30.020 ± 1.9018.30 ± 1.4836.9%563 ± 0.10.41 ± 0.1521.51 ± 1.5441.6%
Dyn A17
(Dyn A)
52.4 ± 0.30.016 ± 0.4715.22 ± 1.5639.1%119 ± 0.20.26 ± 0.5418.72 ± 1.0929.4%
Dyn B13
(Dyn B)
37.8 ± 0.20.010 ± 0.3111.13 ± 1.0733.4%355 ± 0.10.38 ± 0.1117.16 ± 0.8242.2%
a-neo-endorphin39.1 ± 0.10.011 ± 0.2013.32 ± 1.8438.7%591 ± 0.10.18 ± 0.3420.55 ± 1.5721.4%

Next, we measured the inhibition of cAMP levels and KOR endocytosis induced by these peptides. Dose–response curves with Dyn A and Dyn B in SpH-KOR cells showed maximal inhibition ~1 µM (Figure 1—figure supplement 1A). At this concentration, Dyn A8 and ɑ-neo inhibited whole-cell cAMP to levels comparable to that of Dyn A and Dyn B (Figure 1B). Measurement of cell surface levels of KOR by ELISA show that Dyn A and Dyn B endocytose the receptor to a similar extent in SpH-KOR cells and in CHO-KOR cells (Figure 1—figure supplement 1B and CGupta et al., 2016), with maximal endocytosis at ~1 µM. Examination of surface SpH-KOR fluorescence by live cell imaging using Total Internal Reflection Microscopy (TIR-FM) shows similar extent of agonist-mediated KOR clustering into endocytic domains and receptor endocytosis by the four Dynorphin peptides (1 µM) (Figure 1C and D). Together these results indicate that different Dynorphin peptides activate KOR and induce KOR internalization to similar levels.

We next examined if different Dynorphins selectively regulate the fate of KOR after initial activation and internalization, by adapting a discrete-event imaging method to quantitate the rate of individual KOR recycling events over unit time. SpH-KOR fluorescence is quenched in acidic endosomal compartments and is rapidly dequenched when receptors recycle back to the cell surface and are exposed to the extracellular media. This dequenching can be visualized as single events using Total Internal Reflection Fluorescence microscopy (TIR-FM), where the recycling events appear as distinctive sudden spikes in fluorescence followed by an exponential decay as the receptors diffuse on the cell membrane (Figure 2A–C). This method allows us to quantitate individual recycling events in the same cells over time without the confounding effects of continuing endocytosis (Kunselman et al., 2019). When the number of SpH-KOR recycling events were quantitated and normalized to time and cell area, a significantly higher number of recycling events was seen 5 min after Dyn B-induced KOR internalization , compared to Dyn A, Dyn A8, or ɑ-neo (Figure 2D).

Figure 2 with 1 supplement see all
The post-endocytic fate of KOR is determined by the specific Dynorphin that activates it.

(A) Frames from a time lapse movie of a representative region of a PC12 cell stably expressing SpH-KOR (SpH-KOR cells) shown in (B), treated for 5 min with Dyn B (1 μM) and imaged in TIR-FM, showing two examples of exocytic events (white arrows in A) associated with KOR recycling. (C) Fluorescence traces of the two exocytic events, arbitrary units, showing a characteristic abrupt increase in maximum fluorescence intensity followed by exponential decay. (D) Quantitation of the number of exocytic events/µm2/min showing a significant increase for Dyn B compared to the other peptides (mean ± SEM, **p<0.01, ****p<0.0001 in multiple comparisons after ANOVA, n = 14, 39, 52, and 33 cells for α-neo, Dyn A, Dyn B, and Dyn A8, respectively). (E) Ensemble SpH-KOR surface fluorescence measured over time using confocal microscopy shows a decrease in fluorescence upon agonist addition because of quenching of internalized SpH-KOR, and an increase upon peptide washout as receptors recycle to the surface and SpH-KOR is dequenched. (F) Quantification of change in ensemble surface fluorescence over 30 min following treatment with Dyn A or Dyn B (1 μM), normalized to fluorescence before agonist addition, showing the loss during endocytosis and increase during recycling. (G) Quantitation of the amount of SpH-KOR recycled, normalized to the amount endocytosed after Dyn A or Dyn B treatment B (1 μM), shows that a higher amount of receptor is recycled after Dyn B washout (mean ± SEM, ****p<0.0001 by Mann–Whitney; n = 33 and 30 fields for Dyn A and Dyn B, respectively). (H) Recycling of SpH-KOR to the cell surface after treatment with 100 nM Dyn A or Dyn B measured by ELISA shows a much higher rate and extent of recycling after Dyn B washout. (I) Representative immunoblot of total receptor levels in SpH-KOR cells treated with cycloheximide (3 µg/ml) for 2 hr prior to Dyn A or Dyn B treatment (1 μM) for the indicated times show receptor loss after 120 min of Dyn A but not Dyn B treatment. GAPDH is used as a control. (J) Quantification of total receptor levels normalized to untreated control cells under each condition (**p<0.01 by post hoc comparison after two-way ANOVA; n = 5).

To test whether this increase in the rate of discrete recycling events corresponded to an increase in receptor levels at the cell surface, we measured ensemble changes in surface KOR levels by two different methods – whole-cell fluorescence and ELISA-based methods. We focused on Dyn A and Dyn B as a highly relevant and interesting pair, as both are processed from adjacent regions of pro-dynorphin and are often co-expressed in physiologically relevant brain regions (Nikoshkov et al., 2005; Corder et al., 2018). When SpH-KOR fluorescence was followed by live confocal imaging, surface fluorescence decreased after Dynorphin addition, as was expected with receptor internalization. The fluorescence decrease reached a plateau at 10 min, suggesting an equilibrium between endocytosis and recycling at this time point (Figure 2E). When agonist was removed by washing out the media and replacing with fresh media containing antagonist (naltrexone; 10 µm), to specifically measure recycling without the contribution of endocytosis, the fluorescence recovery rate was higher with Dyn B than with Dyn A at the 30 min time point (Figure 2F and G).

A potential reason for the differences we observe could be differences in the rate of proteolytic degradation of the peptides (Mzhavia et al., 2003; Fricker et al., 2020). Therefore, we directly tested whether inhibiting proteolysis abolishes the difference between Dyn A and Dyn B. We first used a protease inhibitor cocktail in the media to inhibit general proteolysis. When discrete recycling events were quantitated as in Figure 2D, Dyn B showed a higher number of KOR recycling events even in the presence of protease inhibitors (Figure 2—figure supplement 1A). When the recovery of surface KOR levels after agonist washout were measured by an independent ELISA-based method, Dyn B-treated cells showed a higher rate of recovery compared to Dyn A, even in the presence of protease inhibitors (Figure 2H). These experiments indicate that differences in general proteolysis of the peptides did not contribute to the increased KOR recycling we observe with Dyn B. Because Dyn B, but not Dyn A, can be cleaved by Endothelin Converting Enzyme 2 (ECE2) in vitro, we next tested whether this differential proteolysis by ECE2 could contributes to the differences between Dyn A and Dyn B-induced KOR recycling. We used S136492, which inhibits ECE2 relatively selectively in vitro in purified systems (Mzhavia et al., 2003), to test whether ECE2 activity was required for Dyn B to drive increased recycling. S136492 significantly reduced recycling for both Dyn A and Dyn B, indicating that the differences in trafficking between Dyn B and Dyn A cannot be explained solely by ECE2 sensitivity (Figure 2—figure supplement 1B). Together, these results suggest that intrinsic differences between Dyn A and Dyn B contribute to differences in KOR recycling when activated by these peptides.

Because KOR did not recycle efficiently when activated by Dyn A, we next asked whether Dyn A-activated KOR was sorted into the degradative pathway. To test this, PC12 cells expressing SpH-KOR were pretreated with cycloheximide (3 µg/ml) 2 hr before agonist addition to inhibit any new protein synthesis and to measure agonist-mediated turnover of KOR. Total KOR levels were determined through immunoblotting, after Dyn A or Dyn B treatment for 30 min or 2 hr (Figure 2I). When total receptor levels were quantified, 2 hr treatment with Dyn A caused a loss of 50% of KOR, while Dyn B treatment caused no loss (Figure 2J). These results suggest that, after endocytosis, Dyn A preferentially sorts KOR into the degradative pathway, while Dyn B sorts KOR into the recycling pathway.

Considering the emerging importance of spatial encoding in diversifying the outcomes of GPCR signaling (Eichel and von Zastrow, 2018; Weinberg et al., 2019; Hanyaloglu, 2018), we next asked whether Dyn A or Dyn B generated distinctive intracellular localization patterns of KOR at steady state. Because Dyn A drove KOR degradation, we first tested whether Dyn A-activated KOR was differentially localized to the late endosomal pathway. When PC12 cells expressing FLAG-KOR and Rab7-GFP, to mark the late endocytic pathway, were treated with 1 µM Dyn A for 20 min and imaged live, KOR colocalized predominantly with Rab7 (example in Figure 3A). To quantitate the distribution of KOR in the endosomal pathway more comprehensively, we treated cells expressing SpH-KOR with 1 µM Dyn A or Dyn B for 20 min, and fixed and stained for APPL1 (very early endosomes), EEA1 and Rab5 (early endosomes), Rab11 (recycling endosomes), Rab7 (late endosomes), and Lamp1 (lysosomes), as markers for the biochemically distinct compartments along the early, recycling, and late endosomal pathway. Using automated object-picking, we then quantitated the fraction of KOR that colocalized with each endosomal marker under these conditions. KOR localized mainly to compartments marked by Rab7 and Lamp1 when activated by Dyn A, but to compartments marked by EEA1, Rab5, and Rab11 when activated by Dyn B (Figure 3B and C). These results show that KOR is concentrated in different endosomal compartments based on the Dynorphin that activates it.

Figure 3 with 1 supplement see all
Dyn A selectively drives KOR signaling from late endosomal compartments.

(A) Representative image of a PC12 cell expressing FLAG-KOR and Rab7-GFP, treated with 1 µM Dyn A for 20 min. Yellow arrows denote KOR endosomes that colocalize with Rab7. (B) SpH-KOR cells treated with 1 μM Dyn A for 20 min were fixed and processed for immunofluorescence with the noted markers. Quantitation, across multiple cells, of the percentage of KOR containing endosomes that colocalize with each of the endosomal markers is noted. KOR primarily localizes in Rab7 and Lamp1 positive late endosomes after Dyn A (n = 8, 10, 9, 11, 20, and 17 cells for APPL1, EEA1, Rab5, Rab11, Rab7, and Lamp1, respectively). (C) A similar quantitation of immunofluorescence images after Dyn B treatment (1 μM for 20 min) shows that KOR localizes less with late endosomes, and more with markers of early/recycling endosomes (n = 18, 16, 15, 18, 23, and 29 cells for APPL1, EEA1, Rab5, Rab11, Rab7, and Lamp1, respectively). (D) Representative images of PC12 cells expressing FLAG-KOR and Nb39, imaged live after treatment with 1 µM Dyn A or Dyn B for 20 min. Yellow arrows in Dyn A show KOR endosomes that recruited Nb39, while cyan arrows in Dyn B show KOR endosomes that do not show obvious recruitment of Nb39. (E) Linear profile plots of fluorescence of KOR and Nb39, measured along lines drawn across regions of the cell with KOR endosomes after treatment with 1 μM Dyn A or Dyn B for 20 min, show that Nb39 fluorescence increases along with KOR in Dyn A, but less noticeably with Dyn B. (F) Ratios of integrated fluorescence of Nb39:KOR in endosomes identified by 3D object analysis show higher amounts of Nb39 relative to KOR in Dyn A-treated cells (****p<0.0001 by Mann–Whitney, n = 766 and 800 endosomes for Dyn A and Dyn B, respectively). (G) Quantitation of the percentage of KOR endosomes per cell with a noticeable increase in Nb39 fluorescence above background shows a higher fraction of KOR endosomes recruited Nb39 in 1 µM Dyn A-treated cells (***p<0.001 by Mann–Whitney, n = 11 and 14 cells for Dyn A and Dyn B, respectively). (H) Representative images of PC12 cells expressing FLAG-KOR and Nb39 and labeled with LysoTracker imaged live after treatment with 1 μM Dyn A or Dyn B for 20 min. Yellow arrows in Dyn A show KOR endosomes that recruited Nb39 that were also labeled with Lysotracker, while cyan arrows in Dyn B show KOR endosomes that do not show obvious labeling with Nb39 and Lysotracker. (I) The average composition of total KOR endosomes that are positive for ±Nb39 and ±Lysotracker after 20 min treatment with Dyn A (1 μM). n = 10 cells. −Lyso/−Nb39 = 23.4 ± 8.1%; −Lyso/+Nb39 = 38.4% ± 17.4%; +Lyso/−Nb39 = 23.7 ± 11.4%; +Lyso/+Nb39 = 14.6 ± 5.1%. (J) cAMP levels after initial Dynorphin treatment (1 μM) for 5 min, washout for 25 min, or a Dynorphin rechallenge (1 μM) at end of the washout, show comparable initial cAMP inhibition by both Dyn A and Dyn B, but persistent signaling by Dyn A after agonist washout.

The agonist-selective localization of KOR to specific endosomes raised the exciting possibility that different Dynorphins could generate distinct subcellular spatial patterns of KOR signaling. To test this possibility, we combined conformation-selective biosensors and high-resolution imaging of FLAG-KOR to ask whether KOR was active in endosomes. A nanobody (Nb39) that specifically recognizes the active conformation of KOR (Che et al., 2018), when co-expressed with FLAG-KOR in PC12 cells, localized efficiently to endosomes that also contained Dyn A-activated KOR. In contrast, Nb39 localized less to endosomes containing Dyn B-activated KOR (Figure 3D and E). When the fraction of total number of KOR endosomes/cell that colocalized with Nb39 was quantitated by analyzing 3D stacks, endosomes containing Dyn A-activated KOR recruited Nb39 at a significantly higher level (Figure 3F and G), suggesting that KOR was in an active conformation in the endosomes specifically after activation by Dyn A. Nb39 recruitment to endosomes required KOR endocytosis, as recruitment was abolished when cells were treated with agonist in the presence of 40 µM Dyngo4A, an endocytosis inhibitor (Figure 3—figure supplement 1A and B). To directly examine whether Dyn A-activated KOR in lysosomes was in an active conformation, we used three-color live cell imaging of FLAG-KOR, Nb39, and LysoTracker. In cells treated with 1 µM Dyn A, a subset of KOR endosomes colocalized with both Nb39 and Lysotracker. In cells treated with 1 µM Dyn B, however, virtually no KOR endosomes colocalized with both Nb39 and Lysotracker (Figure 3H). When the colocalization was quantitated in Dyn A-treated cells, ~15% of all KOR endosomes colocalized with both markers, suggesting that a subset of Dyn A-activated KOR in the lysosome was in the active conformation (Figure 3I). In contrast, in cells treated with 1 µM Dyn B, virtually no KOR endosomes colocalized with both Nb39 and Lysotracker (Figure 3H).

To test whether the subset of Dyn A-activated KOR in the active conformation in late endosomes and lysosomes was capable of signaling, we measured cAMP inhibition under conditions where the agonist was washed out to avoid continued signaling from the surface. Twenty-five minutes after agonist washout, Dyn A-activated KOR was still localized predominantly to Rab7-labeled late endosomal compartments, while Dyn B-activated KOR was localized predominantly to Rab11-labeled recycling endosomes (Figure 3—figure supplement 1C–H). This distribution was comparable to that observed in the continued presence of agonist, and at this time point, there was little to no KOR degradation (Figure 2I and J). Strikingly, Dyn A, but not Dyn B, caused sustained decrease in cAMP levels under conditions where the majority of KOR was in late endosomes and lysosomes (Figure 3J). Together, our results suggest that Dyn A, but not Dyn B, specifically coordinates activation and cAMP inhibition by KOR in late endosomes and lysosomes.

Importantly, this Dynorphin-selective coordination of KOR recycling and endosomal activation was conserved in striatal neurons. To directly measure KOR recycling, E18 rat primary embryonic striatal neurons were transfected with SpH-KOR, and individual recycling events were imaged using TIRFM. The number of individual exocytic events, when quantified per minute and normalized to cell area, was significantly lower in neurons treated for 30 min with 1 µM Dyn A compared to Dyn B (Figure 4A). This suggested that Dyn B, but not Dyn A, preferentially sorted KOR to recycling endosomes in neurons. We directly tested this by detecting the steady-state localization of KOR in endosomes after Dyn A or Dyn B treatment. KOR colocalized predominantly with Rab7 when activated by Dyn A, and with Rab11 when activated by Dyn B (Figure 4B and C). To test whether this differential localization correlated with differential location-based activation of KOR in endosomes, we expressed Nb33, a distinct nanobody that recognizes the active conformation of opioid receptors (Manglik et al., 2017), fused to GFP in neurons. Endosomes containing Dyn A-activated KOR recruited Nb33, while endosomes containing Dyn B-activated KOR recruited Nb33 to a noticeably lesser extent. This recruitment was readily apparent in dendritic projections, where endosomes were distinctly visible (Figure 4D). The percentage of KOR endosomes that recruited Nb33 was significantly higher for Dyn A-activated KOR than for Dyn B (Figure 4E), showing that dynorphin-selective spatial activation of KOR was conserved in neurons.

Figure 4 with 1 supplement see all
Dyn A-specific late endosomal localization and signaling is conserved in striatal neurons.

(A) The number of discrete exocytic events quantitated in rat medium spiny neuron (MSN) expressing SpH-KOR shows increased recycling for 1 μM Dyn B compared to Dyn A (***p<0.001, n = 8 cells). (B) Quantification of the percentage of KOR endosomes colocalized with Rab7 in MSN expressing SpH-KOR treated with 1 μM Dyn A or Dyn B for 30 min (**p<0.01, n = 5 cells for both). (C) Quantification of the percentage of KOR endosomes colocalized with Rab11 in MSN expressing SpH-KOR treated with 1 μM Dyn A or Dyn B for 30 min (**p<0.01, n = 5 and 9 cells for Dyn A and Dyn B, respectively). (D) Colocalization of FLAG-KOR and Nb33-GFP in the soma and in dendrites of MSNs treated with 1 μM Dyn A for 30 min, seen by confocal microscopy. Yellow arrows show KOR endosomes that recruit Nb33. (E) Quantitation of the percentage of KOR endosomes/cell with a noticeable increase in Nb33 fluorescence above background shows that a higher fraction of KOR endosomes recruited Nb33 in Dyn A-treated cells (1 μM for 30 min; ***p=0 < 0.001, n = 10 cells). All p-values were from non-parametric Mann–Whitney tests.

Discussion

Together, our results reveal an unanticipated difference between physiologically important endogenous opioid peptides in encoding the subcellular spatial patterns of KOR signaling. Peptidases localized to endosomes, like endothelin-converting enzymes (ECEs) may provide another level of regulation for agonist-dependent KOR trafficking (Padilla et al., 2007; Roosterman et al., 2007; Gupta et al., 2015). However, our results do not suggest that ECE peptide-sensitivity is the only or primary factor that determines agonist-dependent KOR localization (Figure 2—figure supplement 1). Ubiquitination of KOR may also regulate its ability to traffic to and signal from late endosomal and lysosomal compartments (Li et al., 2008; Henry et al., 2011; Dores and Trejo, 2019).

The exact mechanism by which KOR is localized to different compartments is not clear. Because the post-endocytic sorting of GPCRs is usually mediated by specific interactions of the unstructured cytoplasmic tail of the receptors with trafficking proteins, KOR sorting probably involves interactions with PDZ-interacting protein NHERF1/EBP50 (Liu-Chen, 2004). In this context, different Dynorphin peptides could lock KOR into conformations that selectively allow or inhibit interactions with trafficking and signaling proteins, essentially defining the receptor interactome in an agonist-specific manner. This conformational lock could require the presence of the ligand that is co-internalized with the receptor, although an exciting possibility is that the ligands provide a ‘conformational memory’ to KOR that is sustained through the endocytic trafficking pathway. At present it is not clear what could provide such a conformational memory. It is possible that different Dynorphins could cause agonist-specific post-translational modifications, which is a general emerging theme for opioid receptors (Chiu et al., 2017; Mann et al., 2019). In any case, the differential subcellular localization and trafficking of KOR by two physiologically important ligands that we show here are important to underscore the physiological relevance of receptor sorting, which has been studied largely using receptor mutants or by depleting key components of the trafficking machinery (Bowman et al., 2016; Weinberg et al., 2019; Zhao et al., 2013; Sposini et al., 2017).

One striking aspect of our results is that Dyn A-bound KOR activates Gi in the late endosomal pathway on its way to being degraded. This is surprising because early endosomes are the main compartments that support endosomal signaling for most other canonical GPCRs. For example, other Gi-coupled receptors such as the mu opioid receptor can exist in an active conformation in earlier endosomal compartments (Stoeber et al., 2018). Internalization is required for sustained inhibition of cAMP for many receptors, such as for the class B S1P receptor (Willinger et al., 2014). However, Gi is likely present on late endosomal and lysosomal compartments, as cannabinoid receptors trafficking from the Golgi can activate Gi on lysosomes (Rozenfeld and Devi, 2008). Further, the binding of peptides to opioid receptors does not change dramatically at lower pH (Gupta et al., 2015). Therefore, it is possible that Gi could be activated at multiple endosomal compartments based on the specific opioid receptor and ligand, leading to distinct early and late phases of endosomal signaling.

Post-translational modifications such as phosphorylation or ubiquitination could provide regulatory handles for this late phase of signaling. For example, three lysine residues on the C-terminus of KOR are required for normal levels of degradation of KOR, but not for internalization from the surface (Li et al., 2008). Ubiquitination, however, plays complex roles in receptor trafficking and signaling at the endosome, controlling transport of receptors to lysosomes, entry of receptors into intralumenal vesicles, and recruitment of signaling scaffolds that could initiate non-canonical signaling pathways (Patwardhan et al., 2021). In this context, Dyn A-activated KOR could also activate alternate pathways, such as mTOR signaling, on late endosomes and lysosomes. Interestingly, mTOR signaling is involved in potentially deleterious effects of KOR, leading to efforts to generate agonists bypassing this signaling pathway (Che and Roth, 2018; Liu et al., 2018; Liu et al., 2019). However, under the conditions we tested, we did not see a significant increase in p70S6 phosphorylation, as a readout for mTOR activation, upon activation of KOR with either Dyn A or Dyn B. This could potentially be due to the high baseline of p70S6 phosphorylation in the PC12 cells (Figure 4—figure supplement 1). However, it is possible that KOR could activate mTOR signaling from late endosomes or lysosomes in a subset of neurons yet to be identified, that could mediate aversive effects of KOR.

Physiological systems could leverage receptor sorting to fine-tune both spatial and temporal aspects of GPCR signaling. KOR is activated by many opioid peptides that are generated from multiple precursor peptidesproteins, some of which bias signaling from the cell surface to different outputs (Gomes et al., 2020). Our results suggest that, even for peptides where there are no obvious differences in surface signaling, there are differential effects in endocytic sorting and signaling from endosomes. Receptor sorting in cells is a dynamic and incomplete process. The fractions of receptors we see at steady state likely represent an equilibrium of many rounds of rapid iterative sorting as the endosome matures, where only a small fraction is recycled back to the surface in the case of Dyn A, while a large fraction is recycled in the case of Dyn B. Because Dyn A drives little KOR to recycle and promotes endosomal KOR activation, the net effect would be to cause a sustained cAMP inhibition from endosomes after a single exposure. Because Dyn B drives KOR recycling and induces endosomal signaling only to small amounts, the net effect would be short-lived cAMP inhibition primarily from the surface. On the other hand, the rapid recycling and resensitization caused by Dyn B would sensitize cells to repeated pulses of ligand release, unlike with Dyn A. This difference in steady-state localization, however, is enough to cause a difference in endosomal receptor activation and cAMP signaling, suggesting that small differences in steady-state localization can cause relevant changes in signaling.

Whether these different Dynorphins are always co-released in the nervous system, or whether different brain regions selectively release specific Dynorphins, is still unclear. Dyn A and Dyn B are generated from prodynorphin likely in the late stages of dense core vesicle maturation and could be predominantly co-released, but there could be mechanisms that actively segregate or selectively release individual Dynorphins. In the case of co-released peptides, it is possible that one or more of the peptides could be dominant in dictating the conformational states in which receptors spend most of their time, in which case the signaling and trafficking fates would be determined primarily by these dominant peptides. In any case, our results that highly related opioid peptides regulate spatial encoding of KOR suggest an unanticipated layer of granularity to the anatomical and functional maps of the brain.

Numerical data file

An Excel file reporting the numerical data (means, standard deviations, standard errors, p-values, and n) for the graphs in the figures as noted is provided as Source data 1.

Materials and methods

Reagents, constructs, and cells

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Dynorphin A17 (Dyn A), Dynorphin B13 (Dyn B), Dynorphin A (Dyn A8), and ɑ-neoendorphin (ɑ-neo) were purchased from Tocris Bioscience and/or Phoenix Pharmaceuticals. Naltrexone, protease inhibitor cocktail (Cat. No. P2714), anti-Flag M2 antibody (Cat. No. F3165) were purchased from Sigma Aldrich (St. Louis, MO). Anti-APPL1, -EEA1, -Rab5, -Rab11, -Rab7, -Lamp1 rabbit monoclonal antibodies were purchased from Cell Signaling Technology. Anti-GFP rabbit polyclonal antibodies (Cat. No. A10260) were from Thermo Fisher Scientific. Nb39 and Nb33 constructs were provided by Dr. Bryan Roth (UNC Chapel Hill) and Dr. Mark von Zastrow (UCSF) respectively. Cell lines used were validated, and cells were purchased from ATCC. Cells in the lab are routinely tested for mycoplasma contamination. Stable non-clonal PC12 cells expressing KOR N-terminally tagged with superecliptic phluorin (SpH) (SpH-KOR cells) were selected in puromycin (Gibco) and grown in F12K media supplemented with 10% horse serum and 5% fetal bovine serum (Gibco) in collagen coated flasks. PC12 cells were also transiently transfected with KOR fused to FLAG on its N-terminus using Lipofectamine 2000 as per manufacturer’s protocol (ThermoFisher). Transfected cells were imaged 2–3 days after transfection. CHO cells stably expressing Flag epitope tagged KOR generated as described previously (Gupta et al., 2016) were grown in F12 media supplemented with 10% fetal bovine serum and 1% penicillin–streptomycin. E18 rat striatal neurons were obtained from BraintBits LLC and cultured on poly-d-lysine (Sigma) coated coverslips for 1 week in Neurobasal media (Gibco) supplemented with B27 (Gibco), 1% Glutamax (Gibco), and 1% penicillin–streptomycin (Gibco) before transfection with SpH-KOR or Flag-KOR and Nb33-GFP using Lipofectamine 2000 as per manufacturer’s protocol (ThermoFisher). Antibodies used are listed below.

AntibodySourceIdentifier
Rabbit anti-APPL1Cell Signaling TechnologyD83H4 XP, #3858S, Lot 1
Rabbit anti-EEA1Cell Signaling TechnologyC45B10, #3288, Lot 2
Rabbit anti-Rab5Cell Signaling TechnologyC8B1, #3547, Lot 7
Rabbit anti-Rab11Cell Signaling TechnologyD4F5 XP, #5589, Lot 4
Rabbit anti-Rab7Cell Signaling TechnologyD95F2 XP, #9367, Lot 1
Rabbit anti-Lamp1Cell Signaling TechnologyD2D11 XP, #9091, Lot 6
Goat anti-Rabbit IgG Secondary Antibody, Alexa Fluor 647InvitrogenA21244, Lot 792514
Mouse anti-FLAG M1 (647 conjugate)InvitrogenA20173A, Lot 2136857
Mouse anti-FLAG M2SigmaF3165
Rabbit anti-GAPDHCell Signaling Technology14C10, #2118S, Lot 14
Rabbit p70 S6 KinaseCell Signaling Technology9202S, Lot 20
Rabbit phospho-p70 S6 Kinase (Thr389) (108D2)Cell Signaling Technology9234S, Lot 12
Chicken anti-GFPAbcamAb13970, Lot GR3190550-10
Goat anti-Rabbit IgG (H + L)-HRP conjugateBioRad170–6515, L005679A

Displacement binding assays

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Displacement binding assays were carried out using membranes from PC12 cells stably expressing SpH-KOR (SpH-KOR cells) (100 μg) and CHO-KOR (15 μg) cells. Membranes were prepared as described previously (Gomes et al., 2003). Displacement binding assays were carried out as described previously (Gomes et al., 2004; Gomes et al., 2011) by incubating membranes with [3H] diprenorphine (3 nM) without or with different concentrations (10−12to 10−5 M) of Dyn A8, Dyn A17, Dyn B13, or a-neo-endorphin in 50 mM Tris-Cl buffer pH 7.4 containing 100 mM NaCl, 10 mM MgCl2, 0.2 mM EGTA, and protease inhibitor cocktail (Sigma-Aldrich; cat No. P2714) for 1 hr at 37°C. Non-specific binding was determined in the presence of 10 μM cold diprenorphine. Specific Bound Counts obtained in the absence of peptides was taken as 100%. Data presented are mean ± SE of three independent experiments in triplicate.

Live cell imaging

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Cells were plated onto poly-D-lysine (Sigma) coated 25 mm coverslips. Cells were imaged 2 days later in Leibovitz L15 imaging medium (Gibco) and 1% fetal bovine serum at 37°C in a CO-controlled imaging chamber, using a Nikon Eclipse Ti automated inverted microscope with a 60× or a 100 × 1.49 N.A. TIRF objective or a 20 × 0.75 N.A. objective. Images were acquired with an iXon +897 electron-multiplying charge-coupled device camera with a solid state laser of 488 nm or 647 nm as a light source. Images were analyzed using FIJI (Schindelin et al., 2012).

Quantification of individual recycling events

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PC12 cells stably expressing SpH-KOR (SpH-KOR cells) were treated with KOR agonists: Dyn A17, Dyn B13, Dyn A8, or ɑ-neo endorphin (1 μM) for 5 min to induce receptor clustering and internalization at 37°C. Receptor clustering was visualized using TIRF microscopy. Images were acquired every 3 s for a total of 5 min. Following internalization, a recycling movie was recorded at 10 Hz for 1 min in TIRF. The number of exocytic recycling events were manually scored in FIJI (Fiji Is Just Image J) to determine the recycling rate for each agonist. Recycling events were counted throughout the 1 min movie and the total number of events were normalized by the cell area to determine a recycling rate. Recycling events were also recorded using the same method in primary striatal rat medium spiny neurons transfected with the SpH-KOR plasmid. Recycling movies were taken 30 min after agonist addition in neurons. Statistical significance was determined using a one-way ANOVA.

Ensemble recycling assay

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Receptor surface levels were measured in PC12 cells stably expressing SpH-KOR (SpH-KOR cells) by using confocal microscopy on a 20× objective and 488 nm laser. Images were collected in 30 s intervals across 20 different cell fields. After 2 min of baseline an agonist (1 µM Dyn A17 or Dyn B13) was added to imaging media. Following agonist addition, images were collected for 15 min. After 15 min, agonist was removed, and the imaging media was replaced with fresh media containing antagonist (naltrexone; 10 µm). Images were then collected for another 15 min. Fluorescence intensities were corrected by a background threshold and normalized by the average fluorescence of the baseline frames before agonist treatment. Surface fluorescence analysis was conducted using an ImageJ Macro automated script (National Institutes of Health) (Weinberg et al., 2019). Fluorescence recovery/loss ratios after washout were quantified by normalizing the fluorescence values after washout to the total fluorescence lost before washout. Cell fields that did not respond to Dynorphin treatment were excluded from analysis. Statistical significance was determined by using Student’s paired t-test comparing the endpoints between agonist treatment.

ELISA internalization assays

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CHO cells expressing Flag-epitope tagged KOR (CHO-KOR cells) or PC12 cells stably expressing SpH-KOR (SpH-KOR cells) were seeded in complete growth media into 24-well plates (2 × 105 cells per well). Next day, cells were rinsed with PBS followed by labeling with mouse anti-Flag antibodies for CHO-KOR cells or chicken anti-GFP antibodies for SpH-KOR cells (1:1000 in PBS containing 1% BSA) for 1 hr at 4°C, followed by treatment with 0–10 μM of Dyn A or Dyn B in growth media containing protease inhibitor cocktail (Sigma-Aldrich; Cat. No. P2714) for 60 min at 37°C. Cells were briefly fixed (3 min) with 4% paraformaldehyde followed by three washes (5 min each) with PBS, and incubation with anti-mouse or anti-chicken antibody coupled with horse-radish peroxidase (1:1000 in PBS containing 1% BSA) for 90 min at 37°C. Cells were washed three times with 1% BSA in PBS (5 min each wash), and color was developed by the addition of the substrate o-phenylenediamine (5 mg/10 ml in 0.15 M citrate buffer [pH 5] containing 15 μl of H2O2). Absorbance at 490 nm was measured with a Bio-Rad ELISA reader. Values obtained with secondary antibody in the absence of primary antibody were taken as non-specific and subtracted from all points. The percentage of internalized receptors was calculated by taking total cell surface receptors before agonist treatment for each individual experiment as 100% and subtracting percent surface receptors following agonist treatment. Data presented are mean ± SE of three independent experiments in triplicate.

ELISA recycling assays

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CHO cells expressing Flag-epitope tagged human KOR (CHO-KOR cells) or PC12 cells stably expressing SpH-KOR (SpH-KOR cells) were seeded in complete growth media into 24-well plates (2 × 105 cells per well). Next day, cells were rinsed with PBS followed by labeling with mouse anti-Flag antibodies for CHO-KOR cells or chicken anti-GFP antibodies for SpH-KOR cells (1:1000 in PBS containing 1% BSA) for 1 hr at 4°C, followed by treatment with 100 nM Dyn A, Dyn B, or BAM-22 in growth media containing protease inhibitor cocktail (Sigma-Aldrich; Cat. No. P2714) for 30 min to elicit receptor internalization. The cells were washed to remove the agonist and incubated with medium without or with the ECE2 inhibitor (S136492, 20 μM) for 0–120 min to allow for receptor recycling. At the end of the incubation period, cells were chilled to 4°C and then fixed briefly (3 min) with 4% paraformaldehyde followed by three washes (5 min each) with PBS and incubation with anti-mouse or anti-chicken antibody coupled with horse-radish peroxidase (1:1000 in PBS containing 1% BSA) for 90 min at 37°C. Cells were washed three times with 1% BSA in PBS (5 min each wash), and color was developed by the addition of the substrate o-phenylenediamine (5 mg/10 ml in 0.15 M citrate buffer [pH 5] containing 15 μl of H2O2). Absorbance at 490 nm was measured with a Bio-Rad ELISA reader. Values obtained with secondary antibody in the absence of primary antibody were taken as non-specific and subtracted from all points. % recycled receptors were calculated by subtracting receptors at t = 0 (30 min internalization) from each recycling time point; this represents 0% recycled receptors. Data presented are mean ± SEM of three independent experiments in triplicate.

Immunofluorescence of endosomal markers

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PC12 cells stably expressing SpH-KOR were plated on poly-d-lysine (Sigma Aldrich) coverslips and grown for 24–48 hr at 37°C. Cells were then incubated with different agonists (Dyn A, Dyn B, Dyn A8, or ɑ-neo) for 20 min at 37°C. Cells were then fixed with 4% paraformaldehyde (PFA), pH 7.4, for 20 min. Cells were then rinsed with complete PBS twice and then blocked in PBS containing calcium, magnesium, with 5% FBS, 5% 1M glycine, and 0.75% Triton X-100. SpH-KOR cells were then incubated with an antibody for one of the endosomal markers for 1 hr. Cells were washed three times with PBS containing calcium and magnesium and then labeled with Alexa 647 goat anti-rabbit secondary antibody (1:1000) in a blocking buffer for 1 hr. Confocal imaging of cells was performed using spinning disk confocal microscope (Andor) and 100× objective. Representative images were taken across 10–20 fields for each agonist treatment and endosomal marker. Three biological replicates were performed in each condition.

Endosomal KOR colocalization in live cells with nanobodies and lysotracker

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PC12 cells were transiently transfected with FLAG-KOR and Nb39-YFP or (Nb33-GFP). Cells were labeled with M1-647 for 10 min prior to imaging 3 days after transfection. Images were taken before and after cells were treated with 1 µM Dyn A or Dyn B for 20 min. Confocal imaging of cells was performed using spinning disk confocal microscope (Andor) and 100× objective. Representative images were taken across 10–20 fields for each agonist treatment. In the experiments with Dyngo4A, cells were pretreated with 40 µM Dyngo4a for 30 min prior to imaging. In the Lysotracker experiments, cells were labeled with 25 nM Lysotracker-561 for 5 min prior to imaging.

Endosomal colocalization quantification

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The percent colocalization of the endosomal marker with the total number of receptor positive endosomes was determined using an ImageJ Macro: Object.picker (Weinberg, 2020; doi.10.5281/zenodo.3811031) to identify the total number of endosomes containing receptor in one channel and determine the colocalization with an endosomal marker in another channel. The Image J macro: 3D Object Counter was used as another method of quantification for colocalization. Integrated density values for each object detected in both the receptor and endosome marker channels were used to determine a ratio of endosomal colocalization by dividing the endosomal marker signal by the receptor signal.

Immunoblotting

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PC12 cells stably expressing SpH-KOR were grown in a PDL coated 12-well plate for 2 days at 37°C. Cells were treated with cycloheximide (3 µg/ml) for 2 hr before agonist incubation. Cells were treated with Dyn A17 or Dyn B13 for 30 min or 2 hr. A non-agonist treated well of PC12 cells stably expressing SpH-KOR and a well of PC12 cells not expressing SpH-KOR were used as controls. Following agonist treatments, cells were placed on ice and rinsed twice with PBS containing calcium and magnesium. Cells were directly lysed in the plate using 2× RSB (Bio-Rad, Hercules, CA). Lysates were placed on ice for 30 min and then sonicated in 5 s pulses. Following sonication, lysates were incubated at 37°C for 1 hr. Lysates were run on 10% stain-free gels (BioRad), which were then transferred to nitrocellulose membrane overnight. Membranes were blocked in 5% milk and then probed with anti-GFP Chicken pAB (Abcam) to detect total receptor levels in each condition. Blots were developed using the iBright imager for chemiluminescence signal and quantified using FIJI software. Receptor signal for each condition was normalized to the no treatment control. Five biological replicates were performed. Statistical analysis was performed using two-way ANOVA across time and drug treatment. To test for mTOR activation, PC12 cells stably expressing SpH-KOR were grown in a PDL coated 12-well plate for 2 days at 37°C. Cells were starved overnight in serum-free media and then treated with 1 µM Dyn A or Dyn B for 5 min or 20 min. Cells were placed on ice and rinsed twice with PBS containing calcium and magnesium. Cells were directly lysed in the plate using 2× RSB (Bio-Rad, Hercules, CA). Lysates were placed on ice for 5 min and then placed at 95°C for 5 min. Lysates were run on 10% stain-free gels (BioRad), which were then transferred to nitrocellulose membrane overnight. Membranes were blocked in 5% BSA and then probed with phospho-p70 S6K (CST) to detect phosphorylated S6K levels in each condition. Blots were developed using the iBright imager for chemiluminescence signal and quantified using FIJI software. Membrane was stripped and probed with total p70 S6K (CST) to determine total levels of S6K present in the samples. The phospho-p70 S6K signal was normalized to the total p70 S6K signal for each condition. All samples were then normalized to the no treatment control to determine the fold change over baseline for each condition. Five biological replicates were performed. Statistical analysis was performed using two-way ANOVA across time and drug treatment.

cAMP assays

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PC12 cells stably expressing SpH-KOR (SpH-KOR cells) or CHO cells stably expressing Flag epitope tagged human KOR (CHO-KOR cells) cells (10,000/well) were treated with Dyn A, Dyn B, Dyn A8, or α-neo (1 μM) for 30 min at 37°C in HBSS assay buffer containing 10 mM HEPES, 20 μM forskolin, and protease inhibitor cocktail (Sigma-Aldrich; Cat. No. P2714) and cAMP levels were quantified using the HitHunter cAMP detection kit from DiscoveRx according to the manufacturer’s protocol. In a separate set of experiments dose–response curves were carried out with Dyn A or Dyn B (0–10 μM). In another set of experiments cells were treated Dyn A or Dyn B (1 μM) for 5 min, after which peptides were washed out and cells were incubated in assay buffer for 25 min. Cells were then given a second 5 min treatment with Dyn A or Dyn B (1 μM) and cAMP levels measured. Values obtained in the absence of peptide were taken as 100%. Data presented are mean ± SEM of three independent experiments in triplicate.

Data availability

Data generated and analyzed in this study are included in the manuscript. The study did not generate new sequencing or structural data.

References

    1. Rozenfeld R
    2. Devi LA
    (2008) Regulation of CB1 cannabinoid receptor trafficking by the adaptor protein AP-3
    FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology 22:2311–2322.
    https://doi.org/10.1096/fj.07-102731
  1. Book
    1. Sternini C
    2. Duraffourd C
    3. Anselmi L
    (2013) Opioids
    In: Sternini C, editors. Handbook of Biologically Active Peptides. Elsevier. pp. 1283–1288.
    https://doi.org/10.1016/C2010-0-66490-X

Decision letter

  1. Suzanne R Pfeffer
    Senior and Reviewing Editor; Stanford University School of Medicine, United States
  2. Christopher Evans
    Reviewer; UCLA, United States

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

Acceptance summary:

Why there are over 20 different endogenous opioid peptides but only four receptors, has been a question that has been unanswered for decades. Here the authors show that two highly related endogenous opioids, which initially activate kappa opioid receptor signaling to similar levels, diverge subsequently in trafficking and endosomal signaling. Demonstrating that different endogenous opioids can differentially regulate localization and trafficking of (and signaling by) the same receptor is a key advance in the opioid field.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Compartment-specific opioid receptor signaling is selectively modulated by Dynorphin subtypes" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Christopher Evans (Reviewer #3).

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

This is an interesting and creative paper implicating a differential mechanism of intracellular trafficking and subsequent signaling that is triggered by different dynorphins binding to the kappa opioid receptor. In principle, if the authors could explain the molecular basis for this phenomenon, the story would be of tremendous impact in the fields of opioid receptor signaling and trafficking. Unfortunately, the reviewers noted a number of concerns that would require significant further work and clarification to support the authors' conclusions at this stage. We hope you will find the comments constructive as you plan your next steps.

Reviewer #1

In this manuscript the authors have assessed the different endocytic routes of KOR when activated by DynA or DynB. These are nicely conducted experiments that show interesting results, however the authors completely obviate the connection with their own work that highlights the different degradation mechanisms of these two peptides. As it stands it does not add to the field, and lacks a mechanistic explanation that could be explored given the authors expertise in these systems.

1. The major conclusion of the study is that after endocytosis, DynA preferentially sorts KOR into the degradative pathway, while DynB sorts KOR into the recycling pathway and that this has consequences in the duration of the active state of the receptor and its ability to signal. It is surprising that the authors do not investigate the connection between these results and previously published work that shows differences in the degradation of DynB vs DynA within endosomes. Indeed, the authors have previously shown that: (i) ECE2 hydrolizes DynB and not DynA (Mzhavia et al., JBC 2003), (ii) overexpression of ECE2 increases the rate of mu-opioid receptor recycling upon DynB stimulation (Gupta et al., BJP 2015) and (iii) inhibition of ECE2 decreases mu-opioid receptor recycling (Gupta et al., BJP 2015). Considering this previous work, it is totally expected that the two ligands show distinct post-endocytic trafficking of KOR.

2. Similarly, the differences in ECE2 sensitivity can also explain the Nb39 results, with KOR activated by the ligand that is not hydrolysable (DynA) being able to remain in the active state (and signal) for longer than when activated with the hydrolozable ligand (DynB).

3. A simple experiment to address this obvious connection is to use an ECE2 inhibitor. One would expect that in the presence of this inhibitor DynB-activated KOR is retained intracellularly and remains active for longer. This is an obvious omission of this work and in my opinion the manuscript should not be published without some experiments addressing this.

4. The authors state "this is the first example of different physiological agonists driving spatial localization and trafficking of a GPCR" in light of the above comment, previous work from Bunnett et al., have shown how peptides with different endocytic enzyme sensitivity can indeed, localize GPCRs (e.g somatostatin receptor) in different compartments and elicit distinct signals (Padilla et al., J Cell Biol 2007; Roosterman et al., PNAS 2007; Zhao et al., JBC 2013 to name a few).

5. Support for endosomal signalling falls a bit short. For example, if indeed KOR signals from endosomes, the authors should use an inhibitor of receptor internalization and assess Nb39 recruitment and KOR signalling. Although this reviewer agrees that, since this experiment would still provide indirect evidence, it may not be necessary (though desirable) for publication.

Reviewer #2

This manuscript demonstrates that two highly similar endogenous opioid agonists can give distinct opioid receptor trafficking and signaling fates. There are two key observations that are novel and intriguing: (1) two opioid peptides that are derived from the same precursor can distinctly modulate Kappa Opioid receptor (KOR) trafficking into two distinct pathways; Dynorphin A causes KOR trafficking to the late endosomes/lysosomes pathway whereas Dynorphin B promotes rapid recycling; (2) Dynorphin A activates Gi proteins on the late endosomes/lysosomes which leads to Gi-mediated cAMP inhibition from these compartments.

The idea that GPCRs can activate G proteins at the late endosome/lysosomal compartments is fascinating and novel, however, the data presented here does not fully support their model that Dynorphin A activated Gi proteins on the late endosomes/lysosomes. Without better support for this model, publication in eLife would not be warranted. Here are the main questions that should be addressed before publication:

1. There is a mismatch with the timing of receptor colocalization experiment (Figure 3B and C, 20 min Dynorphin A/B treatment) and the cAMP assay (Figure 3H, 5 min treatment). There needs to be direct evidence that KOR is localized on the late endosomes/lysosomes at 5 minutes post agonist stimulation, i.e. at the time that cAMP levels are measured. It is important to demonstrate that the sustained signaling inhibition by DynA comes from the late endosomes/lysosomes as opposed to early endosomes. A colocalization experiment with 5 min DynA stimulation followed by a 25min washout would be necessary to support their model.

2. What percentage of KORs are proteolytically degraded in the late endosomes/lysosomes at 20 min DynA stimulation?

3. Given that KOR trafficking to the late endosomes and lysosomes is mediate by ubiquitination (as shown here PMID: 18212250), does mutation of these ubiquitination sites (3 lysine residues on KOR C-terminus) block its trafficking and the sustained signaling from the late endosomes/lysosomes?

4. Is there any evidence for Gi protein localization on the late endosome/lysosomes?

5. Additional functional readouts would also be helpful to support their model of Gi-mediated inhibition of cAMP response from late endosomes/lysosomes and not the plasma membrane or early endosomes. Perhaps mTOR activation (as authors have suggested in their discussion) could be used as a read out to show differences between DynA and B-mediated signaling?Reviewer #3

This is an interesting idea and creative paper implicating a differential mechanism of intracellular trafficking and subsequently signaling that is triggered by different dynorphins binding to the kappa opioid receptor. However, there are some questions for the authors:

1. My reading is that some dynorphins are extremely rapidly degraded in serum and with these experiments performed in 15% Horse/FCS there is concern that some of the differential results could be explained by differential degradation. One hypothesis could be a differential frequency of receptor activation over time of a fast recycling receptor population. Can the authors convince me that this difference in trafficking and subsequent signaling is an intrinsic property of the peptide and not an exhaustion of peptide (would be DynB) over the 30min assay?

2. In Figure 2D, 2G and 2J at what time after addition peptides was this data obtained?

3. In Figure 2F the divergence of internalized receptor only occurs from time 20-30 mins which was difficult for me to understand since DynA should be resulting in lost surface receptor number. What confuses me is that in Fig2H the initial recycling induced by DynA17 is fast and slows down so I am wondering if a second hit is needed which feeds into my concern about peptide degradation in the media. Since released peptide would be pulsatile maybe in vivo DynA17 could act like DynB?

4. The assays seem to be done with a single concentration of peptide – 1µM. Do the authors have data to show that at lower (or higher) concentrations than 1µM result in the same trafficking patterns, albeit to a lesser or greater extent. Also, for the cAMP inhibition what concentration gives max inhibition? For a binding affinity of 0.01nM in the cells and with high expression, the 1micromolar concentration seem high.

5. In Figure 2H 100% of receptors appear to be recycled after DynB however 25% of kappa colocalize in Rab7 in 3C so do these Rb 7 co-localized receptors recycle?

6. Could some of the signaling differences be explained by continued activation of receptor as a consequence of peptide processing in the endocytosed vesical as opposed to different vesicles? I guess the continued signaling could also direct subsequent trafficking and this could be tested with a membrane permeable antagonist.

7. The impact statement" Co-released dynorphins, which signal similarly from the cell surface, can differentially localize GPCRs to specific subcellular compartments, and cause divergent receptor fates and distinct spatiotemporal patterns of signaling" could be misconstrued. If one of the pathways is dominant and blocks the other, then co-release may only have one signaling outcome. Have any dynorphin mix experiments been conducted? What might be anticipated?

8. It looks like details for the ELISA measurements in the methods section was missing. Were the ELISA measurements done with untagged KOR or SpH-KOR? One might worry about the effects of the N-terminal SpH tag on KOR trafficking, and it would be nice if the fluorescence SpH-KOR data were supported by ELISA for untagged KOR. (At least some of the data is immunostaining of FLAG-KOR, which probably introduces only minimal perturbation).

9. Dynorphin A17 is a very sticky peptide and difficult to wash out. Since we don't have a dose response it may require only very doses to have full activation for cAMP inhibition. It would be nice to be able to discount this as a potential for prolonged activation after washout.

https://doi.org/10.7554/eLife.60270.sa1

Author response

[Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]

This is an interesting and creative paper implicating a differential mechanism of intracellular trafficking and subsequent signaling that is triggered by different dynorphins binding to the kappa opioid receptor. In principle, if the authors could explain the molecular basis for this phenomenon, the story would be of tremendous impact in the fields of opioid receptor signaling and trafficking. Unfortunately, the reviewers noted a number of concerns that would require significant further work and clarification to support the authors' conclusions at this stage. We hope you will find the comments constructive as you plan your next steps.

We are very happy that you and the reviewers found that the study could be of tremendous impact and describe the paper as “interesting and creative”, “novel and intriguing”, “fascinating and novel”, and feel that the study was “nicely conducted”. We appreciate the comments of the reviewers, and we have addressed the comments as described below.

Reviewer #1

In this manuscript the authors have assessed the different endocytic routes of KOR when activated by DynA or DynB. These are nicely conducted experiments that show interesting results, however the authors completely obviate the connection with their own work that highlights the different degradation mechanisms of these two peptides. As it stands it does not add to the field, and lacks a mechanistic explanation that could be explored given the authors expertise in these systems.

We thank the reviewer for the positive comments. We are happy that the reviewer felt that the experiments are nicely conducted, and that the results are interesting. However, we respectfully but strongly disagree with the comments that our study does not add to the field.

First, considering the extended and severe opioid epidemic, understanding the many ways in which the opioid peptide/receptor system is modulated is of high priority. Endogenous opioid peptides are highly relevant neuromodulators about which we know even less than opioid drugs. Why there are over 20 different endogenous opioid peptides but only four receptors, has been a question that has been unanswered for decades. We show that two highly related endogenous opioids, which initially activate KOR to similar levels, diverge subsequently in trafficking and endosomal signaling. The importance of opioid receptor trafficking to signaling and tolerance is well accepted (although the mechanisms are debated). Demonstrating that different endogenous opioids can differentially regulate localization and trafficking of (and signaling by) the same receptor is a key advance in the opioid field.

Second, the idea that location based-biased signaling can lead to different consequences for the same agonist is a relatively new idea, and clearly a very important area of continuing research. Even for well-studied systems like the adrenergic receptor system, we know almost nothing about the physiological relevance of differential signaling because most of the data are from synthetic compounds. Demonstrating that endogenous ligands take advantage of location bias to generate distinct signaling consequences is a clear indication that such differential trafficking and signaling is physiologically relevant, which is a clear advance in the GPCR field.

1. The major conclusion of the study is that after endocytosis, DynA preferentially sorts KOR into the degradative pathway, while DynB sorts KOR into the recycling pathway and that this has consequences in the duration of the active state of the receptor and its ability to signal. It is surprising that the authors do not investigate the connection between these results and previously published work that shows differences in the degradation of DynB vs DynA within endosomes. Indeed, the authors have previously shown that: (i) ECE2 hydrolizes DynB and not DynA (Mzhavia et al., JBC 2003), (ii) overexpression of ECE2 increases the rate of mu-opioid receptor recycling upon DynB stimulation (Gupta et al., BJP 2015) and (iii) inhibition of ECE2 decreases mu-opioid receptor recycling (Gupta et al., BJP 2015). Considering this previous work, it is totally expected that the two ligands show distinct post-endocytic trafficking of KOR.

2. Similarly, the differences in ECE2 sensitivity can also explain the Nb39 results, with KOR activated by the ligand that is not hydrolysable (DynA) being able to remain in the active state (and signal) for longer than when activated with the hydrolozable ligand (DynB).

3. A simple experiment to address this obvious connection is to use an ECE2 inhibitor. One would expect that in the presence of this inhibitor DynB-activated KOR is retained intracellularly and remains active for longer. This is an obvious omission of this work and in my opinion the manuscript should not be published without some experiments addressing this.

First of all, we respectfully, but strongly, disagree with the implication that only unexpected results are worth publishing. Differentiating and establishing predicted outcomes is critical for advancing biology. Demonstrating a logical conclusion is an essential part of this process. This should be viewed as a strength, and not as a weakness. Acknowledging and supporting this idea is especially important in these times where there is a strong effort and an opportunity, led by eLife, to make academic publishing open and fair.

In this case, however, the key to the reviewer’s three concerns is the assumption that the differences in KOR trafficking are entirely due to differences in ECE2-mediated degradation of Dyn B. In the revised manuscript, we have provided new data and discussion on why peptide degradation cannot fully explain the differences in trafficking between Dyn A and Dyn B.

The reviewer made this assumption based on two arguments. One, that the surface recovery rates of MOR, a different GPCR than the one we study here, is regulated by ECE2, and two, that ECE2 differentially processes Dyn A and Dyn B in the system used here. We feel that these data are not sufficient to make such a strong assumption, for several reasons.

First, relevant to the reviewer’s point about our previous data, we had not previously compared Dyn A and Dyn B-mediated receptor sorting into specific intracellular compartments and their recycling to the cell surface. Our use of advanced high-resolution imaging experiments in this study to carefully study KOR trafficking and signaling provides for a robust signal and allows for the careful comparison between Dyn A and Dyn B in KOR recycling.

Second, it is not accurate to equate the rates of surface recovery to differential location-based signaling. We have known now for over a decade that the rates of GPCR recycling can be regulated by signaling pathways, with functional consequences on signaling, without changing sorting, endosomal localization, or degradation on an ensemble scale (e.g., PMID: 16604070, PMID: 27226565, PMID: 25801029, PMID: 24003153). Therefore, the careful and direct characterization we show here is essential to understand how Dyn A and Dyn B differentially affect KOR localization and signaling.

Third, the correlation of ECE2 sensitivities and receptor trafficking is not established. ECE2 sensitivity for opioid peptides has been estimated using purified peptides and enzymes, and there is no evidence that the selectivity persists in vivo. In fact, most previous studies measured simply the effect of overexpressed ECE2. Further, the correlation is not obvious or direct for related peptide systems either. For example, we have found that BAM peptides, which also activate opioid receptors, drive less recycling of opioid receptors than Dyn B (data presented by Gupta, Gomes and Devi, INRC 2019) even though they are both ECE2 substrates (PMID: 12560336). We have presented data with BAM 22 peptide in Author response image 1. We hope that the reviewer will appreciate that a full and thorough characterization of the comparison of all of the BAM peptides and Dynorphins in the context of the complex roles of ECE2 is a separate study on its own, which is outside the scope of this manuscript that focuses on the physiological differences between two different endogenous opioids in cell lines and in neurons.

Author response image 1
BAM22 drives noticeably less KOR recycling than DynB, even though they are both sensitive to ECE2 inhibition.

(A) Recycling of HA-KOR to the cell surface after 30 min treatment with 100 nM Dyn B or BAM22 and washout for 0-120 min. Cell surface receptors were quantified by ELISA as described in Methods. Levels of cell surface receptors before agonist treatment were taken as 100% for each individual experiment. % recycled receptors were calculated by subtracting surface receptors at t = 0 (30 min internalization) from each recycling time point. (B) Cell surface receptors quantified after peptides were washed out for 120 min in media without or with 20 μm or the ECE2 inhibitor (S136492). The data represent mean ± SEM from three independent experiments carried out in triplicate.

Fourth, it has become increasingly clear that we cannot apply our understanding of one GPCR to the whole family. Many recent studies have highlighted how the mechanisms that regulate GPCRs and their functions diverge considerably between different GPCRs, even though the gross signaling characteristics are nearly identical. Relevant to the reviewer’s assumption, MOR and KOR recycle by distinct mechanisms. KOR uses a PDZ ligand on its C-term to recycle via an EBP-50-mediated mechanism (PMID: 12004055), while MOR uses a leucine-based sequence to recycle via an unknown mechanism (PMID: 12939277). Further, the recycling of MOR is regulated by different signaling pathways (PMID: 31575621) than those that regulate PDZ-mediated recycling of adrenergic receptors (PMID: 24003153). Therefore, it is not a given that the sorting of MOR and KOR will be regulated in the same manner.

Nevertheless, we appreciate that the reviewer’s suggestion to test whether the differences in KOR trafficking are entirely due to differences in ECE2-mediated degradation of Dyn B and not Dyn A. A key prediction of this idea is that inhibiting degradation of the peptides by ECE2 inhibitors would decrease the recycling of Dyn B-activated KOR, but have no effect on Dyn A-activated KOR. We have tested this prediction using ECE2 inhibitors and included the data in the revised manuscript. Contrary to the prediction, however, ECE2 inhibitors decreased KOR recycling after both Dyn A and Dyn B (Figure S2B). General protease inhibitors did not decrease the rates of KOR recycling after Dyn A or Dyn B (Figure S2A). We thank the reviewer for suggesting this experiment. In addition to including this data in the manuscript, we have added a description of the data to address why the differences in trafficking we see are unlikely to be due to differences in peptide processing.

Together, the new data support our conclusion that the differences we observe are not simply because of Dyn B degradation by ECE2, and suggests that the role of ECE2 in regulating sorting of KOR could be complex in vivo. While interesting, we feel that an in-depth characterization of how ECEs regulate peptide degradation in vivo is outside the focus of this study, which focuses on how two related endogenous opioid peptides, derived from the same precursor peptide, can differentially regulate KOR sorting and generate different spatial and temporal profiles of signaling.

4. The authors state "this is the first example of different physiological agonists driving spatial localization and trafficking of a GPCR" in light of the above comment, previous work from Bunnett et al., have shown how peptides with different endocytic enzyme sensitivity can indeed, localize GPCRs (e.g somatostatin receptor) in different compartments and elicit distinct signals (Padilla et al., J Cell Biol 2007; Roosterman et al., PNAS 2007; Zhao et al., JBC 2013 to name a few).

We were quite taken aback by this comment. We take previously published work very seriously, and we try to be as fair as possible when we describe that work.

We carefully searched through the papers the reviewer pointed out for an example where two physiological agonists drive different spatial localization and signaling of the same GPCR. But we could not find one. Padilla et al., 2007, compared different receptors. The manuscript shows that the recycling of CLR, whose ligand is degraded by ECE1, is sensitive to ECE inhibition, but that the recycling of angiotensin receptor or bradykinin receptor, whose ligands are not degraded by ECE, are not. Similarly, Roosterman et al., 2007, focus on how NK1 receptor recycling is sensitive to ECE1 inhibition. To the best of our knowledge, neither paper shows that spatial localization or location-based signaling of a given GPCR is regulated differentially by two different endogenous agonists. The closest experiment we could find was in Figure 2 in Zhao et al., JBC 2013. The main point of this figure is that “Agonists induce endocytosis of SSTR2A in myenteric neurons”. One panel in this figure shows that, when cells exposed to SST14 or the pro-peptide SST28 for 1 hour at 4°C are followed at 37°C and fixed, SSTR labeling at the plasma membrane and cytoplasm is similar at 30 min, but diverges after that. As far as we could decipher, receptor recycling, endosomal identity, or signaling were not tested in this manuscript.

Therefore, we respectfully request that the studies mentioned – of how the recycling of a receptor that binds ECE-sensitive ligands is sensitive to ECE inhibition – should not be conflated with our careful study of whether different endogenous opioids can drive different spatial localization and signaling fates of the same opioid receptor.

We have, however, modified the sentence to state the impact of our work more precisely. We have also cited the relevant paper to discuss the SSTR experiment in the revised manuscript. If the reviewer would point us to specific examples that show that subcellular localization and spatially restricted signaling of a given GPCR are regulated differentially by two different endogenous agonists, we will be more than happy to include a discussion of that work and modify the sentence further to match the current literature.

5. Support for endosomal signalling falls a bit short. For example, if indeed KOR signals from endosomes, the authors should use an inhibitor of receptor internalization and assess Nb39 recruitment and KOR signalling. Although this reviewer agrees that, since this experiment would still provide indirect evidence, it may not be necessary (though desirable) for publication.

We thank the reviewer for suggesting this experiment. As requested, we have included data showing that inhibiting receptor internalization with Dyngo-4a, a dynamin inhibitor, abolishes KOR localization in endosomes as well as Nb39 recruitment (Figure S3A-B).

Reviewer #2

This manuscript demonstrates that two highly similar endogenous opioid agonists can give distinct opioid receptor trafficking and signaling fates. There are two key observations that are novel and intriguing: (1) two opioid peptides that are derived from the same precursor can distinctly modulate Kappa Opioid receptor (KOR) trafficking into two distinct pathways; Dynorphin A causes KOR trafficking to the late endosomes/lysosomes pathway whereas Dynorphin B promotes rapid recycling; (2) Dynorphin A activates Gi proteins on the late endosomes/lysosomes which leads to Gi-mediated cAMP inhibition from these compartments.

The idea that GPCRs can activate G proteins at the late endosome/lysosomal compartments is fascinating and novel, however, the data presented here does not fully support their model that Dynorphin A activated Gi proteins on the late endosomes/lysosomes.

We are very happy that the reviewer found our study fascinating and novel. We thank the reviewer for the comments, and we have addressed them as follows.

1. There is a mismatch with the timing of receptor colocalization experiment (Figure 3B and C, 20 min Dynorphin A/B treatment) and the cAMP assay (Figure 3H, 5 min treatment). There needs to be direct evidence that KOR is localized on the late endosomes/lysosomes at 5 minutes post agonist stimulation, i.e. at the time that cAMP levels are measured. It is important to demonstrate that the sustained signaling inhibition by DynA comes from the late endosomes/lysosomes as opposed to early endosomes. A colocalization experiment with 5 min DynA stimulation followed by a 25min washout would be necessary to support their model.

We thank the reviewer for raising this important point. To clarify, the cAMP inhibition we observe at 5 min of agonist treatment is likely to be a result of signaling from the surface. The prolonged cAMP inhibition is measured after 5 minutes of agonist treatment and a 25 min washout, which is a total of 30 min. At this time, KOR is expected to be present late endosomes/lysosomes after Dyn A treatment. We apologize for not being clear, and we have clarified this in the revised manuscript.

As requested, we tested localization of KOR in Rab7 or Rab 11 endosomes under the same conditions (5 min agonist stimulation followed by a 25 min washout) in which we detected cAMP inhibition. Under these conditions, KOR is preferentially localized in Rab7 endosomes when activated by Dyn A, and in Rab 11 endosomes when activated by Dyn B, suggesting that Dyn A drives KOR to the late endosomal pathway even when agonist is washed out. We have added this new data as Supplemental Figure 3C-H.

In addition, we have also provided three-color live cell imaging data where we simultaneously localized the nanobody that recognizes active KOR with LysoTracker and KOR. As expected, all three markers colocalize in a subset of KOR endosomes, suggesting that at least a subset of the KOR in lysosomes is in the active conformation. We have included this data in the revised manuscript as Figure 3H and I.

2. What percentage of KORs are proteolytically degraded in the late endosomes/lysosomes at 20 min DynA stimulation?

At 20 min, although some of the receptors clearly reach the lysosome (Figure 3B-C, 3H), it is unlikely that there is significant degradation. This idea is supported by our immunoblots that show similar levels of KOR at 30 minutes after Dyn A and Dyn B (Figure 2I-J). This is also roughly consistent with previous studies on the difference in timing between GPCR localization in late endosomes/multivesicular bodies and receptor degradation. We realize this is an important point that we should address, and we have revised the manuscript to clarify these details.

3. Given that KOR trafficking to the late endosomes and lysosomes is mediate by ubiquitination (as shown here PMID: 18212250), does mutation of these ubiquitination sites (3 lysine residues on KOR C-terminus) block its trafficking and the sustained signaling from the late endosomes/lysosomes?

The reviewer raises an interesting topic that has been a subject of considerable debate in the opioid receptor field, and in the GPCR trafficking field in general. The mutation of the three lysine residues on the KOR C-terminus cause more residual KOR levels after 4 hours of Dyn A, suggesting that degradation/downregulation of KOR is reduced in these mutants, even though internalization is comparable (PMID: 18212250). For some opioid receptors, although ubiquitination might be required for involution and entry into the intralumenal vesicles, lysosomal localization is arguably independent of ubiquitination (e.g., PMID: 21106040, PMID: 22547407). Ubiquitination and/or lysine residues that interact with Ub-transferases could also affect downstream signaling, especially in the endosomes, by some GPCRs (e.g., reviewed in PMID: 30353650). Therefore, we feel that interpretation of results from the lysine mutant receptors will not be straightforward, whichever results we get from them. Nevertheless, we appreciate that this is an interesting point that needs to be addressed, and we have revised the manuscript to mention the complex roles of ubiquitination in receptor trafficking.

4. Is there any evidence for Gi protein localization on the late endosome/lysosomes?

This is another interesting point raised by the reviewer, as the majority of data on signaling from endosomes are on Gs-coupled or Gq-coupled receptors. However, Gi-coupled GPCRs, such as cannabinoid receptors or MOR can exist in the active conformation in endosomes (e.g., PMID: 18267983, PMID: 29754753), and internalization is required for sustained cAMP inhibition for the Class B S1P receptor (PMID: 24638168). These provide indirect evidence that Gi proteins might be present and active on endosomes. Unfortunately, directly testing whether Gi proteins are active on endosomes has been technically challenging. The main limitation has been the lack of conformation sensors for Gi proteins. We thank the reviewer for raising this important discussion, and we have discussed this point in the revised manuscript.

5. Additional functional readouts would also be helpful to support their model of Gi-mediated inhibition of cAMP response from late endosomes/lysosomes and not the plasma membrane or early endosomes. Perhaps mTOR activation (as authors have suggested in their discussion) could be used as a read out to show differences between DynA and B-mediated signaling?

We thank the reviewer for the suggestion. We used phosphorylation of the p70S6 kinase as a readout to test whether we could detect differences in mTOR signaling. However, under the conditions we tested, we did not see a significant increase in p70S6 phosphorylation upon activation of KOR with either dynorphin A or B. This could potentially be because there was high baseline p70S6 phosphorylation in the PC12 cells we were using. We have included the data as Supplemental Figure 4, and discussed the implications and considerations of the lack of a noticeable change in p70S6 phosphorylation. Since our data already suggest that there is an impact on cAMP signaling, we have still focused our discussion on the implications to cAMP signaling.

Reviewer #3

This is an interesting idea and creative paper implicating a differential mechanism of intracellular trafficking and subsequently signaling that is triggered by different dynorphins binding to the kappa opioid receptor. However, there are some questions for the authors:

We thank the reviewer for the comments that the paper is interesting and creative, and for the insightful comments provided to improve the paper. We have addressed them as follows.

1. My reading is that some dynorphins are extremely rapidly degraded in serum and with these experiments performed in 15% Horse/FCS there is concern that some of the differential results could be explained by differential degradation. One hypothesis could be a differential frequency of receptor activation over time of a fast recycling receptor population. Can the authors convince me that this difference in trafficking and subsequent signaling is an intrinsic property of the peptide and not an exhaustion of peptide (would be DynB) over the 30min assay?

We agree this is an important point, and we apologize for not specifically explaining this point in the original manuscript. For the trafficking experiments, we directly compared results from experiments done with and without protease inhibitors. We saw no difference between the two conditions, possibly because we were using short time points, high enough concentrations, and dialyzed serum. We have included these data in the revised manuscript as Supplemental Figure 1A. The signaling experiments, which required longer incubations, were performed in the presence of protease inhibitors, consistent with previous studies. We have clarified this important point in the revised manuscript.

2. In Figure 2D, 2G and 2J at what time after addition peptides was this data obtained?

For measuring individual recycling events (2D and G), cells were treated with agonist for 5 minutes at 37°C. Receptor clustering was visualized using TIRF microscopy, and then a recycling movie was recorded at 10 Hz for 1 minute in TIRF. For 2J, we measured 2 time points, 30 min and 120 min after agonist addition. We apologize for overlooking these details, and we have included these details in the revised manuscript.

3. In Figure 2F the divergence of internalized receptor only occurs from time 20-30 mins which was difficult for me to understand since DynA should be resulting in lost surface receptor number. What confuses me is that in Fig2H the initial recycling induced by DynA17 is fast and slows down so I am wondering if a second hit is needed which feeds into my concern about peptide degradation in the media. Since released peptide would be pulsatile maybe in vivo DynA17 could act like DynB?

We apologize for not explaining the recycling experiment performed in 2F in more detail. The cells were imaged for a period of 2 minutes to collect baseline SpH fluorescence, which corresponds to the steady-state amount of KOR on the cell surface. After this period, cells were imaged for 15 min after Dyn A or Dyn B was added. In this period, because internalization is the predominant factor affecting surface levels, we see a loss in fluorescence as the receptors are internalized and SpH is quenched in the relatively acidic compartments. Because KOR internalization rates are not dramatically different between Dyn A and B, the fluorescence traces were not that different. The agonist was then washed out at this time (t=17), and cells were imaged in media containing antagonist. Because there is very little agonist-induced internalization after this point, the fluorescence change depends predominantly on reappearance of receptors via recycling. Therefore, if the main difference between Dyn A and Dyn B is in KOR recycling, we expect to see a divergence only in the late points of the trace. We thank the reviewer for carefully viewing the traces in 2F and 2H. We understand the interpretation that there might be fast and slow components to Dyn A induced recycling. While it certainly is possible, we are not comfortable making a strong conclusion on that, based on the sensitivity of the assays used and the variability between cells.

As mentioned in point#1, it is unlikely that this divergence in recycling is due to significant degradation of Dyn A. Nevertheless, it is an important point to discuss in light of the new data we provide, and we have explained this in detail in the revised manuscript.

4. The assays seem to be done with a single concentration of peptide – 1µM. Do the authors have data to show that at lower (or higher) concentrations than 1µM result in the same trafficking patterns, albeit to a lesser or greater extent. Also, for the cAMP inhibition what concentration gives max inhibition? For a binding affinity of 0.01nM in the cells and with high expression, the 1micromolar concentration seem high.

We thank the reviewer for raising this point. We used the 1µM dose based on dose-response measurements for cAMP signaling. Part of the dose-response data has been published (PMID: 32393639). However, we realize that this is a point that needs to be addressed in our system.

In the revised manuscript, we have included a dose-response for trafficking and signaling as Supplemental Figure 1. The reviewer is correct that we were using doses above saturation as far as the binding affinity goes, but the dose response depends also on receptor expression levels and availability of downstream components that determine the signaling and trafficking consequences. However, we were using saturating concentrations, and it is possible that this is what mitigates the potential degradation of small amounts of the peptides.

5. In Figure 2H 100% of receptors appear to be recycled after DynB however 25% of kappa colocalize in Rab7 in 3C so do these Rb 7 co-localized receptors recycle?

This is an interesting point, as it is certainly possible that some receptors from Rab7 endosomes can recycle. Current views, however, are more aligned with endosomes being overlapping populations as labeled by biochemical markers, especially by trafficking components like Rabs. Therefore, our characterization likely describes a spread of receptor distributions across these overlapping compartments. Moreover, the recycling of receptors in Figure 2H was quantitated using ELISA over 2 hours after agonist washout. The endosome colocalizations in 3C was measured after 20 min of agonist treatment. As we hope the reviewer would agree, it is difficult to directly compare data from these two experiments.

That said, we certainly did not mean to imply that all of Dyn B-activated KOR is recycled and that all Dyn A-activated KOR is degraded. Current data on trafficking support a more dynamic and flexible model for receptor sorting, where a fraction of the receptors is recycled while a fraction is degraded from each endosome. Our results are consistent with this model. We feel that, because the receptor populations undergo many rounds of rapid iterative sorting as the endosome matures, a larger fraction is recycled back to the surface in the case of Dyn B at a steady state, while a larger fraction stays behind in the case of Dyn A. Importantly, this difference in steady state localization is enough to cause a difference in endosomal receptor activation and cAMP signaling, suggesting that small differences in steady state localization can cause relevant changes in signaling. We apologize for not making this important point clearer, and have clarified this in the Discussion in the revised manuscript.

6. Could some of the signaling differences be explained by continued activation of receptor as a consequence of peptide processing in the endocytosed vesical as opposed to different vesicles? I guess the continued signaling could also direct subsequent trafficking and this could be tested with a membrane permeable antagonist.

We thank the reviewer for raising this point. As we described in our response to reviewer#1, peptide processing by ECE proteases could contribute to the differences, but the data suggest that this is not a direct correlation or the main explanation for the differences we observe. We have addressed this point in the revised manuscript.

7. The impact statement" Co-released dynorphins, which signal similarly from the cell surface, can differentially localize GPCRs to specific subcellular compartments, and cause divergent receptor fates and distinct spatiotemporal patterns of signaling" could be misconstrued. If one of the pathways is dominant and blocks the other, then co-release may only have one signaling outcome. Have any dynorphin mix experiments been conducted? What might be anticipated?

We agree that the question of whether one peptide is dominant is an interesting one in the context of the paper, and we thank the reviewer for pointing this out. That said, assay sensitivity has remained a long-standing problem when trying these mixed experiments in the endogenous opioid system. We tried an equimolar mix of dynorphins A and B in our high-resolution imaging assay and in traditional recycling assays. We have included this data in Author response image 2. We feel that including the data in the manuscript takes away from the main point of the manuscript, as there could be many reasons for this result, but we will be happy to defer to the reviewer. To focus our discussion on the differences between the two dynorphins and reduce ambiguity, we have deleted that sentence and discussed the release of dynorphins A and B in the discussion in more depth.

Author response image 2
Dyn B is dominant over Dyn A for KOR endocytic trafficking.

(A) Quantitation of the number of exocytic events/μm2/min, as in Figure 2, in SpH-KOR PC12 cells co-treated with 1μM of Dyn A and 1μM of Dyn B, compared to either on its own. The co-treatment mimics Dyn B. (B) SpH-KOR PC12 cells were treated with 100nM Dyn A, Dyn B or a combination of both for 30 min. Peptides were washed out and cells incubated for 60 min in media without the agonist. Surface receptors were measured by ELISA as described in Methods. Percentage of recycled receptors were calculated by subtracting surface receptors at t = 0 (30 min internalization; 0% recycling) from each recycling time point. Co-treatmentcauses KOR recycling comparable to Dyn B alone. The data represent mean ± SEM from threindependent experiments carried out in triplicate.

8. It looks like details for the ELISA measurements in the methods section was missing. Were the ELISA measurements done with untagged KOR or SpH-KOR? One might worry about the effects of the N-terminal SpH tag on KOR trafficking, and it would be nice if the fluorescence SpH-KOR data were supported by ELISA for untagged KOR. (At least some of the data is immunostaining of FLAG-KOR, which probably introduces only minimal perturbation).

We apologize for not including the details of the ELISA experiments. The ELISA experiments were performed essentially as described previously (PMID: 24990314; PMID: 24847082). We have corrected this oversight and included these details in the revised manuscript.

The reviewer’s concern about the tag is a valid one, and one that we are very careful about. Nterminal tags are commonly used to study GPCR trafficking, and are usually preferred as they reduce interference with the cytoplasmic sequences and trafficking machinery. We have used two different tags to label the receptor, both on the N-terminus. The ELISA measurements were done using FLAGtagged KOR. The trafficking and microscopy experiments were done with both FLAG-tagged and SpH-tagged KOR. The signaling experiments were also performed with SpH-KOR and FLAG-KOR. The results are consistent between all these experiments, suggesting that the differences we observe are not due to the tag. We have clarified this point in the revised manuscript.

9. Dynorphin A17 is a very sticky peptide and difficult to wash out. Since we don't have a dose response it may require only very doses to have full activation for cAMP inhibition. It would be nice to be able to discount this as a potential for prolonged activation after washout.

The reviewer brings up a good point. Dyn A is less sticky in media or solutions containing 150mM NaCl, but we realize that this is a concern that should be addressed. In our case, we picked the doses we used based on dose-response curves that we have performed for cAMP signaling for these peptides. Also, experiments where we added both B and A, where the effect of B seems dominant, suggests that the results are not due to the stickiness of Dyn A.

We realize that it is important to explain the choice of our concentrations better, and we have done so in the revised manuscript.

We thank the reviewers for the careful analysis of the manuscript and for all their comments. We feel that the inclusion of new data and the extensive revision has substantially strengthened the manuscript. We hope that the reviewers find the revised version acceptable for publication.

https://doi.org/10.7554/eLife.60270.sa2

Article and author information

Author details

  1. Jennifer M Kunselman

    Cellular and Molecular Biology Training Program, University of Michigan Medical School, Ann Arbor, United States
    Contribution
    Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Achla Gupta
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9772-4149
  2. Achla Gupta

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Contributed equally with
    Jennifer M Kunselman
    Competing interests
    No competing interests declared
  3. Ivone Gomes

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  4. Lakshmi A Devi

    Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Manojkumar A Puthenveedu

    1. Cellular and Molecular Biology Training Program, University of Michigan Medical School, Ann Arbor, United States
    2. Department of Pharmacology, University of Michigan Medical School, Ann Arbor, United States
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Project administration, Writing - review and editing
    For correspondence
    puthenve@umich.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3177-4231

Funding

National Institute of General Medical Sciences (T32GM007315)

  • Jennifer M Kunselman

National Institute of General Medical Sciences (GM117425)

  • Manojkumar A Puthenveedu

National Science Foundation (1935926)

  • Manojkumar A Puthenveedu

National Institute of Neurological Disorders and Stroke (NS026880)

  • Lakshmi A Devi

National Institute on Drug Abuse (DA008863)

  • Lakshmi A Devi

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

Acknowledgements

We thank Dr. Daniel Shiwarski, Marlena Darr, and Caroline Hernandez-Casner for essential initial technical assistance with the project. We thank Drs. Bryan Roth, Tao Che, Daniel Wacker, Mark von Zastrow, and Miriam Stoeber for generously providing key reagents. We thank Drs. Robert Fuller, Carole Parent, Alan Smrcka, and Lloyd Fricker for expert discussions. JMK was supported by NIH T-32-GM007315, LAD by NIH NS026880 and DA008863, and MAP by NIH GM117425 and by NSF 1935926.

Senior and Reviewing Editor

  1. Suzanne R Pfeffer, Stanford University School of Medicine, United States

Reviewer

  1. Christopher Evans, UCLA, United States

Publication history

  1. Received: June 23, 2020
  2. Accepted: April 19, 2021
  3. Accepted Manuscript published: April 28, 2021 (version 1)
  4. Version of Record published: May 11, 2021 (version 2)

Copyright

© 2021, Kunselman 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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