α1-Adrenergic receptor–PKC–Pyk2–Src signaling boosts L-type Ca2+ channel CaV1.2 activity and long-term potentiation in rodents

  1. Kwun Nok Mimi Man
  2. Peter Bartels
  3. Peter B Henderson
  4. Karam Kim
  5. Mei Shi
  6. Mingxu Zhang
  7. Sheng-Yang Ho
  8. Madeline Nieves-Cintron
  9. Manuel F Navedo
  10. Mary C Horne  Is a corresponding author
  11. Johannes W Hell  Is a corresponding author
  1. Department of Pharmacology, University of California, United States
  2. Department of Pharmacology, University of Iowa, United States

Abstract

The cellular mechanisms mediating norepinephrine (NE) functions in brain to result in behaviors are unknown. We identified the L-type Ca2+ channel (LTCC) CaV1.2 as a principal target for Gq-coupled α1-adrenergic receptors (ARs). α1AR signaling increased LTCC activity in hippocampal neurons. This regulation required protein kinase C (PKC)-mediated activation of the tyrosine kinases Pyk2 and, downstream, Src. Pyk2 and Src were associated with CaV1.2. In model neuroendocrine PC12 cells, stimulation of PKC induced tyrosine phosphorylation of CaV1.2, a modification abrogated by inhibition of Pyk2 and Src. Upregulation of LTCC activity by α1AR and formation of a signaling complex with PKC, Pyk2, and Src suggests that CaV1.2 is a central conduit for signaling by NE. Indeed, a form of hippocampal long-term potentiation (LTP) in young mice requires both the LTCC and α1AR stimulation. Inhibition of Pyk2 and Src blocked this LTP, indicating that enhancement of CaV1.2 activity via α1AR–Pyk2–Src signaling regulates synaptic strength.

Editor's evaluation

This study reports of a new signaling pathway in hippocampal neurons by which α1 receptors for norepinephrine regulate Cav1.2 calcium channels; activation of α1 receptors enhances a form of long-lasting synaptic plasticity that is dependent on L-type calcium channels. The experiments are comprehensive and well-executed, and the main conclusions are compellingly supported by the data shown. The work has significance for the field of neuroscience in general and for cellular mechanisms of neuroregulation in particular.

https://doi.org/10.7554/eLife.79648.sa0

Introduction

Norepinephrine (NE) causes arousal and augments behavioral acuity and learning (Berman and Dudai, 2001; Cahill et al., 1994; Carter et al., 2010; Hu et al., 2007; Minzenberg et al., 2008). NE signals via the Gq-coupled α1-adrenergic receptor (AR), Gi-coupled α2AR, and Gs-coupled β1, β2, and β3 ARs. βARs act through adenylyl cyclase (AC), cAMP, and PKA (Sanderson and Dell’Acqua, 2011). The β2AR, Gs, AC, and PKA are all associated with the L-type Ca2+ channel (LTCC) CaV1.2 for efficient signaling in neurons (Davare et al., 2001; Dittmer et al., 2014; Murphy et al., 2014; Oliveria et al., 2007; Patriarchi et al., 2016; Qian et al., 2017) and heart (Balijepalli et al., 2006). The formation of this signaling complex identifies CaV1.2 as a major effector of signaling by NE. We now find that CaV1.2 is also a major effector for signaling via the α1AR, which has a higher affinity for NE than βARs (Giustino and Maren, 2018; Ramos and Arnsten, 2007). Importantly, a large body of evidence implicates the α1AR in NE’s role in attention and vigilance (Bari and Robbins, 2013; Berridge et al., 2012; Hahn and Stolerman, 2005; Hvoslef-Eide et al., 2015; Liu et al., 2009; Puumala et al., 1997; Robbins, 2002).

CaV1.2 fulfills a remarkably broad spectrum of functions. Dysfunctions due to mutations in CaV1.2 span from impaired cardiac contractility to the autistic-like behaviors seen in Timothy syndrome (Splawski et al., 2004). Furthermore, CaV1.2 has been linked to filopodia formation in invasive cancer cells (Jacquemet et al., 2016). CaV1.2 is by far the most abundant LTCC in heart and accounts for ~80% of all LTCCs in brain (Hell et al., 1993a; Sinnegger-Brauns et al., 2004). It governs the heartbeat, vascular tone, and neuronal functions including long-term potentiation (LTP) (Ghosh et al., 2017; Grover and Teyler, 1990; Moosmang et al., 2005; Patriarchi et al., 2016; Qian et al., 2017), long-term depression (Bolshakov and Siegelbaum, 1994), neuronal excitability (Berkefeld et al., 2006; Marrion and Tavalin, 1998), and gene expression (Dolmetsch et al., 2001; Li et al., 2016; Li et al., 2012; Ma et al., 2014; Marshall et al., 2011; Murphy et al., 2014; Wheeler et al., 2012). Studies on CaV1.2 mutant mice suggest that this channel plays a central role in anxiety disorders, depression, and self-injurious behavior (Sinnegger-Brauns et al., 2004). Congruently, LTCC blockers elicit antidepressant effects while agonists induce depression-like behavior (Mogilnicka et al., 1987; Mogilnicka et al., 1988) and self-biting in mice, a symptom associated with autism (Jinnah et al., 1999).

CaV1.2 consists of the pore-forming subunit α11.2, a β subunit and the α2δ subunit (Catterall, 2000; Dai et al., 2009; Zamponi et al., 2015). The β and α2δ subunits facilitate release of α11.2 subunits from the endoplasmic reticulum, inhibit ubiquitin-mediated degradation of voltage-gated calcium channels, influence electrophysiological properties of Ca2+ channels, such as activation and inactivation, and play diverse roles in the regulation of these channels (Catterall, 2000; Dai et al., 2009; Zamponi et al., 2015).

In the cardiovascular system, the α1AR, the endothelin receptor ET1, and the angiotensin receptor AT1 are important regulators of LTCC currents via Gq signaling (Catterall, 2000; Kamp and Hell, 2000; Voelker et al., 2023). Gq stimulates phospholipase C-β to induce production of diacylglycerol (DAG) and inositol-1,4,5-trisphosphate (IP3), which triggers Ca2+ release from intracellular stores. DAG and Ca2+ act in concert with phosphatidyl-serine to activate different PKC isoforms. Stimulation of PKC mostly leads to an increase in CaV1.2 activity (Bkaily et al., 1995; Dai et al., 2009; Döşemeci et al., 1988; He et al., 2000; Kamp and Hell, 2000; Lacerda et al., 1988; Navedo et al., 2005). However, an inhibitory effect of PKC on CaV1.2 currents has been reported in cardiomyocytes (Cheng et al., 1995; Voelker et al., 2023). This inhibition is mediated by phosphorylation of residues T27 and T31 by PKC in an isoform of α11.2 that is expressed in heart (McHugh et al., 2000). T27/T31 are not present in the most prevalent brain isoform due to alternative splicing (Snutch et al., 1991); thus, the inhibitory effect of PKC on LTCC currents is typically absent in neurons and neural crest-derived PC12 cells, or in vascular smooth muscle (Navedo et al., 2005; Taylor et al., 2000). Here, we show that stimulation of the α1AR and of PKC consistently augments LTCC in hippocampal neurons.

Despite the prominent role of PKC in augmentation of CaV1.2 activity, how PKC mediates this effect has been unknown. PKC activates the nonreceptor tyrosine kinase Pyk2, a signaling process first shown in PC12 cells (Dikic et al., 1996; Lev et al., 1995) and later primary neurons (Bartos et al., 2010; Huang et al., 2001), and cardiomyocytes (Sabri et al., 1998). Activation of PKC triggers autophosphorylation of residue Y402 on Pyk2 to create a binding site for the SH2 domain of Src, which upon binding to Pyk2 becomes activated (Dikic et al., 1996). Src increases LTCC activity in smooth muscle cells (Gui et al., 2006; Hu et al., 1998; Wu et al., 2001), retinal pigment epithelium (Strauss et al., 1997), and neurons (Bence-Hanulec et al., 2000; Endoh, 2005; Gui et al., 2006). Furthermore, PKC (Navedo et al., 2008; Yang et al., 2005) and Src (Bence-Hanulec et al., 2000; Chao et al., 2011; Hu et al., 1998) are physically and functionally associated with CaV1.2. These findings underscore the physiological relevance of Src in regulating CaV1.2. Importantly, the pathway by which Src is activated in the context of CaV1.2 regulation has not been determined.

Once we established that stimulation of PKC or the Gq/PKC-coupled α1AR strongly augments LTCC activity in neurons, we tested whether Pyk2 mediates this upregulation of channel activity. We link the α1AR–PKC signaling to Src, which thus emerges as an important mediator of tyrosine phosphorylation on CaV1.2 downstream of Gq-coupled receptors. In neurons, the nearly twofold increase in LTCC currents upon stimulation of PKC with phorbol-12-myristate-13-acetate (PMA) or via the α1AR was blocked by inhibitors of Pyk2 and Src, consistent with earlier data showing that Src elevates CaV1.2 activity to a comparable degree (Bence-Hanulec et al., 2000; Gui et al., 2006). Furthermore, we found that Pyk2 co-immunoprecipitated with CaV1.2 in parallel to Src. We identified the loop between domains two and three of α11.2 as the Pyk2-binding site. Stimulation of PKC either directly with PMA or through the Gq-coupled bradykinin (BK) receptor leads to tyrosine phosphorylation of α11.2 in PC12 cells. Abrogation of Pyk2 or Src activity ablated the phosphorylation. Finally, we discovered that the LTP in young mice mediated by LTCC-dependent Ca2+ influx during 200 Hz tetani (termed LTPLTCC) that is not NMDAR dependent, required α1AR stimulation and both Pyk2 and Src activity. These findings implicate upregulation of CaV1.2 activity by α1AR–Pyk2–Src signaling as a critical process for control of synaptic strength. Our findings indicate that CaV1.2 forms a supramolecular signaling complex (signalosome) with PKC, Pyk2, and Src and that α1AR–PKC–Src–CaV1.2 signaling constitutes a central regulatory mechanism of neuronal activity and synaptic plasticity by NE.

Results

α1AR signaling augments LTCC activity in hippocampal neurons via PKC, Pyk2, and Src

We performed cell-attached recordings from cultured hippocampal neurons for single-channel analysis, which allows pharmacological isolation of LTCCs by application of ω-conotoxins GVIA and MVIIC (Hall et al., 2013; Oliveria et al., 2007; Patriarchi et al., 2016; Qian et al., 2017). LTCC channel activity was measured by cell-attached recordings, which yielded the product of the number of channels (N) and the open probability (Po) of each single channel. Application of phenylephrine (PHE), a selective agonist for all three α1ARs, augmented N × Po of LTCCs from 0.18 ± 0.0433 (H2O vehicle Control, n = 11) to 0.6156 ± 0.1386 (PHE; n = 13, p ≤ 0.01; Figure 1A–C). This increase was blocked by the selective α1AR antagonist prazosin (0.2954 ± 0.0607; n = 10, p ≤ 0.05), indicating that PHE acted through α1ARs and not other G-protein-coupled receptors. Prazosin by itself had no effect, vs. vehicle control (0.1846 ± 0.04624; n = 10) suggesting that there is little if any regulation of LTCCs under basal conditions in neurons by α1ARs. PHE also increased the peak current of the ensemble average current in a prazosin-sensitive manner (Figure 1D, E).

The α1AR agonist phenylephrine (PHE) augments NPo of L-type Ca2+ channels (LTCCs) in hippocampal neurons.

(A) Neurons were preincubated with vehicle, PHE and prazosin (PRAZ) before seal formation. (B) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs from cultured hippocampal neurons with vehicle (water; black), 10 µM PHE (red), PHE plus 20 nM prazosin (bright green), and prazosin alone (dark green). (C) The increase in NPo by PHE was blocked by prazosin. F3,40 = 5.474. Control vs. PHE, p = 0.0036; PHE vs. Prazosin + PHE, p = 0.0334; Control vs. Prazosin only, p = 0.9723. (D) Ensemble averages during depolarization. (E) The increase in ensemble average peak currents by PHE was blocked by prazosin. F3,40 = 4.506. Control vs. PHE, p = 0.0101; PHE vs. Prazosin + PHE, p = 0.0316; Control vs. Prazosin only, p = 0.9722. (C, E) Data are presented as means ± standard error of the mean (SEM). n represents the number of cells (*p ≤ 0.05, **p ≤ 0.01; analysis of variance [ANOVA] with post hoc Holm–Sidak’s multiple comparisons test). Panel A was created using Biorender.com.

Because direct phosphorylation of α11.2 by PKC inhibits CaV1.2 activity in heart (McHugh et al., 2000), we explored whether PKC might upregulate CaV1.2 activity indirectly via other kinases. PKC can activate Pyk2 (Bartos et al., 2010; Dikic et al., 1996; Huang et al., 2001; Lev et al., 1995) and thereby Src (Dikic et al., 1996; Huang et al., 2001). Src, in turn, augments LTCC activity (Bence-Hanulec et al., 2000; Endoh, 2005; Gui et al., 2006; Hu et al., 1998; Strauss et al., 1997; Wu et al., 2001). Therefore, we tested whether block of Pyk2 and Src affects upregulation of LTCC activity by PHE. In a new set of recordings augmentation of LTCC activity by PHE from NPo of 0.2008 ± 0.03348 (dimethyl sulfoxide (DMSO) vehicle control, n = 33) to 0.3272 ± 0.04412 (PHE, n = 33; p ≤ 0.01; Figure 2A–C) was completely blocked by two different PKC inhibitors, bisindolylmaleimide I (GF109203X; Bis I; 0.1412 ± 0.03305; n = 11, p ≤ 0.01) and chelerythrine (Chel; 0.05801 ± 0.01508; n = 12, p ≤ 0.001), the Pyk2-selective inhibitor PF-719 (0.09118 ± 0.02828; n = 10, p ≤ 0.01) and two structurally different Src family kinase inhibitors, PP2 (0.01487 ± 0.006808; n = 7, p ≤ 0.001) and SU6656 (0.09149 ± 0.02866; n = 9, p ≤ 0.01). Peak currents of ensemble averages showed respective changes (Figure 2D, E). Accordingly, α1AR signaling increases LTCC activity via a PKC–Pyk2–Src signaling cascade. Notably, stimulation of two other major Gq-protein-coupled receptors in neurons, that is, the metabotropic mGluR1/5 receptors with dihydroxyphenylglycine (DHPG) and muscarinic receptors with muscarine, did not significantly increase LTCC activity, although there was a tendency for DHPG to do so (Figure 2—figure supplement 1).

Figure 2 with 1 supplement see all
The phenylephrine (PHE)-induced increase in NPo of L-type Ca2+ channels (LTCCs) in hippocampal neurons requires PKC, Pyk2, and Src.

(A) Neurons were preincubated with vehicle, PHE, and the indicated kinase inhibitors before seal formation. (B) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs with vehicle (0.1% DMSO; black) and PHE either alone (red) or with the PKC inhibitors chelerythrine (Chel; 10 µM; bright brown) and bisindolylmaleimide I (Bis I; 100 nM; dark brown), the Pyk2 inhibitor PF-719 (1 µM; green), or the Src inhibitors PP2 (10 µM; blue) and SU6656 (10 µM; purple). (C) The increase in NPo by PHE was blocked by all inhibitors. F6,108 = 6.434. Control vs. PHE, p = 0.0076; PHE vs. Chel + PHE, p = 0.0001; PHE vs. Bis I + PHE, p = 0.0076; PHE vs. PF-719 + PHE, p = 0.0018; PHE vs. PP2 + PHE, p = 0.0003; PHE vs. SU6656 + PHE, p = 0.0022. (D) Ensemble averages during depolarization. (E) The increase in ensemble average peak currents by PHE was blocked by PKC inhibitors chelerythrine, bisinolylmaleimide I, and Src inhibitor PP2. F6,108 = 4.839. Control vs. PHE, p = 0.0242; PHE vs. Chel + PHE, p = 0.0004; PHE vs. Bis I + PHE, p = 0.0242; PHE vs. PF-719 + PHE, p = 0.0723; PHE vs. PP2 + PHE, p = 0.0006; PHE vs. SU6656 + PHE, p = 0.0723. (C, E) Data are presented as means ± standard error of the mean (SEM). n represents the number of cells (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001; analysis of variance [ANOVA] with post hoc Holm–Sidak’s multiple comparisons test). Panel A was created using Biorender.com.

PKC augments LTCC activity in hippocampal neurons via Pyk2 and Src

To further establish a role of Pyk2 and Src, we directly stimulated PKC by including PMA in the bath solution during single-channel recording of LTCCs in hippocampal neurons. PMA increased NPo of LTCCs by around twofold from 0.1099 ± 0.0173 (DMSO control, n = 45) to 0.232 ± 0.03269 (PMA, n = 38; p ≤ 0.001, Figure 3A–C). This increase was blocked by Pyk2 inhibitors PF-719 (NPo = 0.1407 ± 0.02705, n = 13, p ≤ 0.05) and PF-431396 (NPo = 0.09282 ± 0.01765, n = 18, p ≤ 0.001) and by Src inhibitors PP2 (NPo = 0.05614 ± 0.01815, n = 14, p ≤ 0.001) and SU6656 (NPo = 0.02951 ± 0.00555, n = 8, p ≤ 0.001). Peak currents of ensemble averages showed respective changes (Figure 3D, E). The L-type calcium channel blocker isradipine completely blocked L-type currents in the presence of PMA, indicating successful isolation of L-type single-channel currents (Figure 3—figure supplement 1). These results show that in hippocampal neurons, PKC activation stimulates LTCC activity and this augmentation requires Pyk2 and Src activity.

Figure 3 with 1 supplement see all
The increase in NPo of L-type Ca2+ channels (LTCCs) in hippocampal neurons by PKC requires Pyk2 and Src.

(A) Neurons were preincubated with vehicle, the phorbol ester phorbol-12-myristate-13-acetate (PMA), and the indicated kinase inhibitors before seal formation. (B) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs with vehicle (0.06% DMSO; black) and 2 µM PMA either alone (red) or with the Pyk2 inhibitors PF-719 (1 µM; green) and PF-431396 (3 µM; orange), or the Src inhibitors PP2 (10 µM; blue) and SU6656 (10 µM; purple). (C) The increase in NPo by PMA was blocked by all inhibitors. F5,130 = 6.530. DMSO vs. PMA, p = 0.0003; PMA vs. PF-719 + PMA, p = 0.0372, PMA vs. PF-431396 + PMA, p = 0.0009; PMA vs. PP2 + PMA, p = 0.0003; PMA vs. SU6656 + PMA, p = 0.0005. (D) Ensemble averages during depolarization. (E) The increase in ensemble average peak currents by PMA was blocked by all inhibitors. F5,130 = 5.665. DMSO vs. PMA, p = 0.0003; PMA vs. PF-719 + PMA, p = 0.0303, PMA vs. PF-431396 + PMA, p = 0.0051; PMA vs. PP2 + PMA, p = 0.0003; PMA vs. SU6656 + PMA, p = 0.0051. (C, E) Data are presented as means ± standard error of the mean (SEM). n represents the number of cells (*p ≤ 0.05, **p 0.01, ***p ≤ 0.001; analysis of variance [ANOVA] with post hoc Holm–Sidak’s multiple comparisons test). Panel A was created using Biorender.com.

α1AR signaling augments single-channel open probability Po of LTCCs in neurons

Preincubation of neurons with PHE could promote either surface insertion or Po of LTCCs. To test whether PHE augmented specifically Po, we used pipettes with smaller diameters to minimize patch size and channel number in the patch, as reflected by pipette resistences of 7–12 vs. 3.5–5.5 MΩ in the preceding experiments. This approach typically resulted in <4 channels per patch, allowing exact determination of channel number and thereby calculation of single-channel Po. PHE was acutely washed on after establishing baseline activity to avoid delays as occurring when recording the effect of preincubation of neurons with PHE during which new channels could have been inserted (Figure 4A). PHE consistently increased within 2–3 min Po and peak currents as determined by ensemble averages (Figure 4B–D).

α1AR signaling augments Po of L-type Ca2+ channels (LTCCs) in hippocampal neurons.

(A, E) Seals were formed by the recording pipettes before application of phenylephrine (PHE) or norepinephrine (NE) and ultimately of either isradipine or nimodipine to ensure channel activity was mediated by LTCCs. (B) Sample diary shows time course of Po before and after application of 10 µM PHE and then 10 µM isradipine. The number of channels under the patch was estimated based on the maximal number of observed stagged openings in each patch (k; upper left). (C) Ten consecutive traces from representative cell-attached single-channel LTTC recordings before and after application of PHE and then isradipine. Bottom panels show ensemble averages. (D) PHE increases Po (left) and peak currents of ensemble averages (n = 12 cells; right). (F) Sample diary shows time course of Po before and after application of 10 µM NE and then 10 µM isradipine. (G) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs before and after application of NE and then nimodipine. Bottom panels show ensemble averages. (H) NE increases Po (left) and peak currents of ensemble averages (n = 8 cells; right). (D, H) Data are presented as means ± standard error of the mean (SEM). Statistical significance was tested by a paired, two-tailed Student’s t-test, *p ≤ 0.05. Panels A and E were created using Biorender.com.

Application of the endogenous agonist NE to the outside of the cell-attached pipette was equally able to augment single-channel Po and peak currents of ensemble averages (Figure 4E–G). Of note, the β2AR-selective adrenergic agonist albuterol can also augment Po of CaV1.2 by stimulating the CaV1.2-associated β2AR, adenylyl cyclase and PKA (Davare et al., 2001; Dittmer et al., 2014; Murphy et al., 2014; Oliveria et al., 2007; Patriarchi et al., 2016; Qian et al., 2017). However, it does so only when applied inside the patch pipette and not when applied after seal formation to the outside, reflective of highly localized, spatially restricted signaling events (Davare et al., 2001; Dittmer et al., 2014; Murphy et al., 2014; Oliveria et al., 2007; Patriarchi et al., 2016; Qian et al., 2017). Accordingly, NE applied to the outside of the pipette augments Po not via β2AR but rather via α1AR signaling. Consistently, the increases in single-channel Po and peak currents of ensemble averages seen with NE were remarkably similar to the respective PHE effects.

To further test the role of α1AR vs. β2AR signaling in this recording configuration, we applied NE either alone or together with the α1AR antagonist prazosin to the neurons before seal formation and recording of channel activity (Figure 5A). NE increased Po and peak current of ensemble averages more strongly in this approach than when applied only to the outside of the pipettes (Figure 5B–D). This effect was inhibited but not fully blocked when prazosin was co-applied with NE. These two effects are consistent with upregulation of CaV1.2 activity by NE via both α1AR and β2AR signaling.

Norepinephrine (NE) can augment Po of L-type Ca2+ channels (LTCCs) via α1AR signaling in hippocampal neurons.

(A) Neurons were preincubated with NE ± prazosin (PRAZ) before seal formation. (B, C) Sample diaries show time courses of Po recordings obtained after preincubation with either NE alone or NE + PRAZ and seal formation. The number of channels under the patch was estimated based on the maximal number of observed stagged openings in each patch (k; upper left). (D) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs under control conditions or upon pre-incubation with either NE alone or NE plus PRAZ. Bottom panels show ensemble averages. (E) NE strongly increases Po (left) and peak currents of ensemble averages (right), which was strongly but not fully inhibited by PRAZ. Data are presented as means ± standard error of the mean (SEM; Control, n = 8 cells; NE, n = 12 cells; NE/PRAZ, n = 11 cells). Statistical significance was tested by a one-way analysis of variance (ANOVA) with Bonferroni correction, *p ≤ 0.05. Panel A was created using Biorender.com.

BK augments Po of LTCCs in neurons

The above results indicate that signaling by the Gq-coupled α1AR promotes LTCC activity in a manner that is spatially much less localized if at all as opposed to signaling by the Gs-coupled β2AR. Stimulation of other prominent Gq-coupled receptors, mGluR and muscarinic receptors, yielded little or no effects, respectively, on LTCC activity (Figure 2—figure supplement 1), possibly because those might be to far removed from the LTCCs in soma where the recordings were performed. Another Gq-coupled receptor that is prominent in the hippocampus is the BK receptor 2 (BK2). Application of BK to the outside of the patch pipette after establishing baseline activity of LTCCs (Figure 6A) significantly augmented Po (Figure 6B–D). In this set of experiments, the identity of the Ca2+ channels in the patch was confirmed by applying the LTCC activity promoting Bay K8644, which, consistently, augmented the current under the patch.

Bradykinin (BK) signaling augments Po of L-type Ca2+ channels (LTCCs) in hippocampal neurons.

(A) Seals were formed by the recording pipettes before application of BK and ultimately of BayK8644 (BayK) to ensure channel activity was mediated by LTCCs. (B) Sample diary shows time course of Po before and after application of 5 µM BK and then 5 µM BayK to not only provide further evidence that the channels in the patch were LTCC but also aid in determining channel number k (upper left), which is the number of channels under the patch as estimated based on the maximal number of observed stagged openings in each patch. (C) Ten consecutive traces from representative cell-attached single-channel recordings of LTCCs before and after application of BK and then BayK. Bottom panels show ensemble averages. (D) BK increases Po (left) and peak currents of ensemble averages (right). Data are presented as means ± standard error of the mean (SEM; n = 7 cells). Statistical significance was tested by a paired, two-tailed Students t-test, *p ≤ 0.05. Panel A was created using Biorender.com.

Pyk2 co-immunoprecipitates with CaV1.2 from brain and heart

Kinases and proteins that regulate kinase activity are often found in complexes with their ultimate target proteins (i.e., their ultimate substrates) including different ion channels for efficient and specific signaling (Dai et al., 2009; Dodge-Kafka et al., 2006). Both, PKC (Navedo et al., 2008; Yang et al., 2005) and Src (Bence-Hanulec et al., 2000; Chao et al., 2011; Hu et al., 1998), are associated with CaV1.2. We tested in brain and heart (where CaV1.2 is most abundant) whether the same is true for Pyk2. The Pyk2 antibody detected a single immunoreactive band with an apparent MR of ~120 kDa in brain lysate (Figure 7A) and two bands in the same range in heart (Figure 7A, B), as reported earlier (Dikic et al., 1998). The shorter form is missing 42 residues in the proline-rich region of Pyk2, which affects its binding selectivity to proteins with SH3 domains. The single size form of Pyk2 present in brain and its two size forms expressed in heart co-immunoprecipitated with CaV1.2 (Figure 7A, B). No Pyk2 immunoreactive band was detectable when the immunoprecipitation (IP) was performed with control IgG, demonstrating that the co-IP of Pyk2 with CaV1.2 was specific. The detergent extracts from brain and heart were cleared of non-soluble material by ultracentrifugation prior to co-IP of Pyk2 with CaV1.2. Thus, our findings indicate that Pyk2 forms a bona fide protein complex with CaV1.2 rather than just co-residing in a detergent-resistant subcellular compartment. We also confirmed earlier work (Figure 7A, bottom panel) that indicated association of Src with CaV1.2 in vitro (Bence-Hanulec et al., 2000; Endoh, 2005; Gui et al., 2006; Hu et al., 1998; Strauss et al., 1997; Wu et al., 2001) and in intact cells (Bence-Hanulec et al., 2000; Chao et al., 2011; Hu et al., 1998).

Pyk2 binds to the loop between domains II and III of α11.2. Co-immunoprecipitation of Pyk2 and Src with CaV1.2 from brain (A) and heart (B).

Triton X-100 extracts were cleared from non-soluble material by ultracentrifugation before immunoprecipitation (IP) with antibodies against α11.2, Pyk2 itself, or non-immune control antibodies (rabbit IgG) and immunoblotting (IB) with anti-Pyk2 and anti-Src. Brain lysate (A, Input; 20 μl) and Pyk2 immunoprecipitates (B) served as positive control for detection of Pyk2 and Src by IB. Lanes for rabbit IgG control and α11.2 IP in B are from the same IB as the Pyk2 IP, which is depicted from a shorter exposure than the IgG and α11.2 IP lanes because IB signal was much stronger after Pyk2 IP than α11.2 IP. Comparable results were obtained in four independent experiments. (C) Schematic diagram of the intracellular α11.2 fragments used in the pulldown assay (Supplementary file 1). (D) Pulldown assay of Pyk2 binding to α11.2 fragments. GST fusion proteins of the N-terminus, the loops between domains I and II, II and III, III and IV, the whole C-terminus, and three different overlapping fragments covering the C-terminus were expressed in Escherichia coli, immobilized on glutathione Sepharose, washed and incubated with purified His-tagged Pyk2. Comparable amounts of fusion proteins were present (data not shown but see Hall et al., 2013; Hall et al., 2007; Patriarchi et al., 2016; Xu et al., 2010). Comparable results were obtained in five independent experiments.

Figure 7—source data 1

Original files of the full raw unedited blots with bands labeled in red boxes.

https://cdn.elifesciences.org/articles/79648/elife-79648-fig7-data1-v2.zip

Pyk2 binds to the loop between domains II and III of α11.2

To further confirm a direct interaction between Pyk2 and CaV1.2 we performed pulldown experiments using purified solubilized His-tagged Pyk2 and purified bead-bound GST-tagged α11.2 fragments covering all intracellular regions of α11.2 (Supplementary file 1, Snutch et al., 1990). As demonstrated earlier, all α11.2 fragments were present in comparable amounts (Hall et al., 2013; Patriarchi et al., 2016). The GST fusion protein covering the loop between domains II and III of α11.2 specifically pulled down Pyk2 (Figure 7C, D) indicating that Pyk2 directly binds to this region of the α1 subunit.

Inhibitors of Pyk2 and Src block the increase in α11.2 tyrosine phosphorylation upon stimulation of PKC

PC12 cells are of neural-endocrine crest origin and widely used as model cells for neuronal signaling and development. They express high levels of CaV1.2 (Eiki et al., 2009; Mustafa et al., 2010; Taylor et al., 2000; Walter et al., 2000), the BK receptor, and Pyk2 (Bartos et al., 2010; Dikic et al., 1996; Lev et al., 1995), making them an ideal model system for the difficult biochemical analysis of CaV1.2 phosphorylation. To characterize tyrosine phosphorylation of α11.2 we performed IP with the general anti-phosphotyrosine antibody 4G10 (Clifton et al., 2004; Ward et al., 1992). For this purpose, lysates were extracted with 1% sodium dodecyl sulfate (SDS) at 65°C followed by neutralization of SDS and ultracentrifugation before IP with the general anti-phosphotyrosine antibody 4G10 (Clifton et al., 2004; Ward et al., 1992). IP with 4G10 followed by immunoblotting (IB) with antibodies against the protein of interest is more reliable and more broadly applicable than the inverse. Because α11.2 does not re-associate with its binding partners after complex dissociation with SDS and the neutralization and dilution of SDS with Triton X-100 (Davare et al., 1999; Hell et al., 1995; Hell et al., 1993b; see also Leonard and Hell, 1997), detection of α11.2 by IB in the 4G10 IP would reflect specific tyrosine phosphorylation of the α11.2 subunit and not its artefactual re-association with an α11.2-associating tyrosine-phosphorylated protein that had been pulled down by the 4G10 antibody. This approach also allows analysis of tyrosine phosphorylation of Pyk2 within the same sample.

PC12 cells were pretreated with vehicle (0.02% DMSO), the Pyk2 inhibitor PF-431396, or the Src inhibitors SU6656 and PP2 or its inactive analogue PP3 for 5 min before application of BK or PMA for 10 min. BK strongly activates Pyk2 in PC12 cells via its Gq-coupled cognate receptor (Dikic et al., 1996; Lev et al., 1995). Using the 4G10 IP method, we found that both PMA and BK increased tyrosine phosphorylation of Pyk2 as previously described (Dikic et al., 1996; Lev et al., 1995; Figure 8A–C). This increase was prevented by PF-431396. In parallel, we determined phosphorylation of Pyk2 on Y402 and Y579 by direct IB of PC12 lysates with corresponding phosphospecific antibodies. Upon stimulation via PKC, Pyk2 phosphorylates itself in trans on Y402 (Bartos et al., 2010; Park et al., 2004) and then binds with phosphoY402 to the SH2 domain of Src (Dikic et al., 1996). This binding stimulates Src (Dikic et al., 1996), which in turn phosphorylates Pyk2 on Y579 in its activation loop for full activation (Avraham et al., 2000; Figure 8A). Src also phosphorylates itself in trans on Y416 in its activation loop for its own full activation (Roskoski, 2015), which was determined in parallel with a phosphospecific antibody. We found that BK and PMA increased phosphorylation of Pyk2 on Y402 (Figure 8B–D) and Y579 (Figure 8E, F) and of Src on Y416 (Figure 8G, H). PF-431396 blocked all of these phosphorylations indicating that Pyk2 acts downstream of PKC and upstream of Src. Furthermore, the Src inhibitor PP2, but not its inactive analog, PP3, also prevented PMA-induced Src autophosphorylation on Y416 (Figure 8I, J), as expected. Finally, PP2 inhibited PMA-induced phosphorylation of Pyk2 on Y402 and Y579 indicative of a self-maintaining positive feedback loop between Pyk2 and Src (Figure 8K–M). These results support the specific activation of both, Pyk2 and Src under our conditions and suggest that this activation occurs in a self-sustaining manner, which creates a quasi-molecular memory (Figure 8A).

PKC activates interdependent Pyk2 and Src.

PC12 cells were pretreated with vehicle (0.02% DMSO), the Pyk2 inhibitor PF-431396 (3 μM), and the Src inhibitor PP2 (10 μM) or its inactive analogue PP3 (10 μM) for 5 min before application of bradykinin (Brad., 2 μM) or phorbol-12-myristate-13-acetate (PMA, 2 μM) for 10 min, extraction with 1% sodium dodecyl sulfate (SDS) at 65°C to ensure dissociation of all proteins, neutralization of SDS with excess of Triton X-100, and ultracentrifugation. Supernatants were analysed by direct immunoblotting (IB) with the indicated Pyk2 and Src antibodies.

Some samples underwent immunoprecipitation (IP) with the anti-phosphotyrosine antibody 4G10 before IB with anti-Pyk2 antibody (top panel in A and quantification in B). IgG indicates control IP with non-immune mouse IgG. (A) Schematic diagram depicting the bradykinin receptor–PKC–Pyk2/Src signaling cascade and drugs used to target each molecular entity. (B) Upper panel: Total pY levels of Pyk2 determined by IP with 4G10 and IB with anti-Pyk2. Middle panel: pY402 levels of Pyk2 detected with anti-pY402 in corresponding lysates. Lower panel: Levels of total Pyk2 detected with anti-Pyk2 in same lysates. (C) Ratios of total pY of Pyk2 after 4G10 IP to total Pyk2 in lysates, normalized to control. F5,63 = 12.73. DMSO vs. Brad., p = 0.012; DMSO vs. PMA, p < 0.0001; Brad. vs. PF-431396 + Brad., p < 0.0001; PMA vs. PF-431396 + PMA, p = 0.0001. (D) Ratios of pY402 to total Pyk2 signals in lysates, normalized to control. F5,35 = 10.94. DMSO vs. Brad., p = 0.039; DMSO vs. PMA, p = 0.0052; Brad. vs. PF-431396 + Brad., p = 0.0005; PMA vs. PF-431396 + PMA, p < 0.0001. (E) Upper panel: pY579 levels of Pyk2 detected with anti-pY579. Lower panel: Levels of total Pyk2 detected with anti-Pyk2 in same lysates. (F) Ratios of pY579 to total Pyk2 signals in lysates, normalized to control. F5,36 = 10.18. DMSO vs. Brad., p = 0.0072; DMSO vs. PMA, p = 0.021; Brad. vs. PF-431396 + Brad., p = 0.0008; PMA vs. PF-431396 + PMA, p = 0.0011. (G, I) Upper panels: pY416 levels of Src detected with anti-pY416. Lower panels: Levels of total Src detected with anti-Src in same lysates. (H, J) Ratios of pY416 to total Src signals in lysates, normalized to control. (H) F5,72 = 4.464. DMSO vs. Brad., p = 0.0167; DMSO vs. PMA, p = 0.0226. (J) F5,65 = 11.06. DMSO vs. PMA, p = 0.001; PMA vs. PP2 + PMA, p < 0.0001; DMSO vs. PP3 + PMA, p = 0.0042; PP3 vs. PP3 + PMA, p = 0.0086. (K) Upper panel: pY402 levels of Pyk2 detected with anti-pY402. Middle panel: pY579 levels of Pyk2 detected with anti-pY579. Lower panel: Levels of total Pyk2 detected with anti-Pyk2 in same lysates. (L, M) Ratios of pY402 and pY579 to total Pyk2 signals in lysates, normalized to control. (L) F5,42 = 35.85. DMSO vs. PMA, p < 0.0001; PMA vs. PP2 + PMA, p < 0.0001; PP3 vs. PP3 + PMA, p = 0.0001; DMSO vs. PP3 + PMA, p = 0.0068; DMSO vs. PP2 + PMA, p = 0.0001; DMSO vs. PP2, p < 0.0001. (M) F5,68 = 13.40. DMSO vs. PMA, p < 0.0001; PMA vs. PP2 + PMA, p < 0.0001; PP3 vs. PP3 + PMA, p = 0.0362; DMSO vs. PP3 + PMA, p = 0.0202. (C, D, F, H, J, L, M) Data are presented as mean ± standard error of the mean (SEM). Number (n) of independent experiments for each condition are indicated inside bars. Statistical analysis was by analysis of variance (ANOVA) with post hoc Bonferroni’s multiple comparisons test; *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001. Bradykinin- and PMA-induced phosphorylation of Pyk2 on Y402 and Y579 and of Src on Y416, all of which were blocked by PF-431396 and PP2 but not the inactive PP3. Panel A was created using Biorender.com.

Figure 8—source data 1

Original files of the full raw unedited blots with bands labeled in red boxes.

https://cdn.elifesciences.org/articles/79648/elife-79648-fig8-data1-v2.zip

Importantly, PMA and BK induced tyrosine phosphorylation of α11.2 (Figure 9). This effect was blocked by the Pyk2 inhibitor PF-431396 (Figure 9A–C) and the Src inhibitors SU6656 and PP2, whereas the inactive PP2 analogue PP3 was without effect (Figure 9D, E). These data show that activation of PKC translates into tyrosine phosphorylation of α11.2 and that this requires both Pyk2 and Src.

Increase in α11.2 tyrosine phosphorylation by PKC is blocked by inhibitors or Pyk2 and Src. PC12 cells were treated as in Figure 8 for analysis of tyrosine phosphorylation by immunoprecipitation (IP) with 4G10 and immunoblotting (IB) with anti-α11.2.

IgG indicates control IP with non-immune mouse IgG. Vehicle (0.02% DMSO), PF-431396 (3 μM), PP2 (10 μM), PP3 (10 μM), or SU6656 (SU, 10 μM) were applied 5 min before phorbol-12-myristate-13-acetate (PMA) or bradykinin (Brad.) when indicated. (A) Schematic diagram depicting the bradykinin receptor–PKC–Pyk2/Src–CaV1.2 signaling cascade and drugs used to target each molecular entity. (B, D) Upper panels: pY of α11.2 determined by 4G10 IP and α11.2 IB. Lower panels: Levels of total α11.2 detected with anti-α11.2 in corresponding lysates. (C, E) Ratios of pY signals in 4G10 IPs by IB with anti-α11.2 to α11.2 signals in lysates, normalized to control. Data are presented as mean ± standard error of the mean (SEM). Number (n) of independent experiments for each condition are indicated inside bars. Statistical analysis was by analysis of variance (ANOVA) with post hoc Bonferroni’s multiple comparisons test. (C) F5,50 = 10.65. DMSO vs. Brad., p = 0.0021; DMSO vs. PMA, p = 0.0036; Brad. vs. PF-431396 + Brad., p = 0.0003; PMA vs. PF-431396 + PMA, p < 0.0001. (E) F7,31 = 23.67. DMSO vs. PMA, p < 0.0001; PMA vs. PP2 + PMA, p < 0.0001; PMA vs. SU + PMA, p < 0.0001 (**p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001). Bradykinin- and PMA-induced α11.2 tyrosine phosphorylation was blocked by PF-431396, SU6656 and PP2 but not the inactive PP3. Panel A was created using Biorender.com.

Figure 9—source data 1

Original files of the full raw unedited blots with bands labeled in red boxes.

https://cdn.elifesciences.org/articles/79648/elife-79648-fig9-data1-v2.zip

Knock down of Pyk2 and Src prevents the increase in α11.2 tyrosine phosphorylation upon stimulation of PKC

To control for any potential side effects of PF-431396 and determine whether Pyk2 is required for PKC-induced tyrosine phosphorylation of α11.2 we employed FIV and HIV lentiviral expression vectors for shRNAs targeting Pyk2 in PC12 cells. We first designed and cloned an shRNA-targeting rat Pyk2 (Sh1) into the FIV-based plasmid pVETL-GFP (Bartos et al., 2010; Boudreau and Davidson, 2012; Harper et al., 2006) and tested the ability and specificity of this construct to knockdown ectopically expressed Pyk2 in HEK293T/17 cells. Cells were co-transfected with vectors for expression of GFP-tagged rat Pyk2 (rPyk2-GFP) and the pVETL-Sh1-GFP or no shRNA control pVETL-GFP (Figure 10A) and Pyk2 expression levels in the transfected cell lysates were examined via IB. Expression of rPyk2-GFP was virtually abolished by pVETL-Sh1-GFP whereas the control pVETL-GFP had no effect (Figure 10A). IB with both tubulin and GAPDH antibodies confirmed that total protein levels were not affected by transfection of these plasmids (Figure 10A).

Increase in α11.2 tyrosine phosphorylation by PKC is blocked by knockdown of Pyk2 and Src.

(A) Lysates from HEK293T/17 cells transfected with vectors encoding rat Pyk2 (rPyk2-GFP) and either the Pyk2-targeting FIV lentivirus-derived, pVETL-Sh1-GFP (pFV-Pyk2-Sh1) or control (empty) pVETL-GFP (pFV-GFP) expression vectors, were immunoblotted (IB) with indicated antibodies. (B, C) IB analysis of indicated proteins in PC12 cultures incubated with viral particles containing pFV-Sh1-GFP (Sh1) FIV-based expression vector used in A or medium vehicle alone for 72 hr prior to treatment with either phorbol-12-myristate-13-acetate (PMA, B), bradykinin (Brad.; C), or vehicle alone (−; B, C). Upper blots in B and C show anti-α11.2 IBs of 4G10-anti-phosphotyrosine (pY) immunoprecipitation (IP) while middle and lower blots show direct IBs of indicated protein levels in input lysates. (D) Statistical analysis of the relative pY α11.2 levels. F5,41 = 8.276. NT vs. PMA, p = 0.0031; NT vs. Brad., p = 0.0017; PMA vs. Sh1 + PMA, p = 0.001; Brad vs. Sh1 + Brad, p = 0.0433. (E, F) Direct IB analysis of indicated proteins in lysates of PC12 cultures transduced with HIV vector-derived lentiviral particles (e.g., pGFP-Pyk2-ShB-Lenti) containing expression cassettes for GFP and either the Pyk2-targeting (denoted pHV-Pyk-ShB and -ShC), Src-targeting (denoted pHV-Src-ShC and -ShD), or scrambled hairpin control (Cont.) shRNAs. In some cases (right blot in F) cultures were treated with PMA (+) or vehicle alone (−) before harvesting for IB. (G, H) IB analysis of indicated proteins from PC12 cultures infected with lentiviral particles containing HIV-GFP expression vectors as in E and F prior to treatment with either PMA (+) or vehicle (−). Upper panels show anti-α11.2 IBs of 4G10-anti-pY IP while lower blots show direct IBs of input lysates with indicated antibodies. (I) Statistical analysis of relative α11.2 pY levels. F11,129 = 6.180. NT vs. PMA, p < 0.0001; PMA vs. Pyk2-ShB, p = 0.0005; PMA vs. Pyk2-ShB + PMA, p = 0.0029; PMA vs. Pyk2-ShC, p < 0.0001; PMA vs. Pyk2-ShC + PMA, p = 0.0002; PMA vs. Cont.-Sh, p = 0.0019; PMA vs. Cont.-Sh + PMA, p > 0.9999; PMA vs. Src-ShB, p = 0.0007; PMA vs. Src-ShB + PMA, p < 0.0001; PMA vs. Src-ShC, p < 0.0001; PMA vs. Src-ShC + PMA, p < 0.0001. The bar graphs in (D) and (I) show ratios of quantified anti-α11.2 IB signals in 4G10 IPs relative to α11.2 IB signals in total lysates, normalized to not treated (NT) control. Comparisons are made between samples treated with PMA (or bradykinin in D) and each of the other indicated conditions. Data are presented as mean ± standard error of the mean (SEM). Number (n) of independent experiments for each condition are indicated inside bars. Statistical analysis by analysis of variance (ANOVA) with post hoc Bonferroni’s multiple comparisons test (ns = not significant vs. PMA, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001).

Figure 10—source data 1

Original files of the full raw unedited blots with bands labeled in red boxes.

https://cdn.elifesciences.org/articles/79648/elife-79648-fig10-data1-v2.zip

Next we tested whether pVETL-Sh1-GFP would inhibit PMA- and BK-induced α11.2 phosphorylation in PC12 cells. pVETL-Sh1-GFP lentiviral particles carrying the Sh1-shRNA and GFP expression cassettes were used to efficiently infect PC12 cells. Infected cells were monitored for GFP expression and then subjected to overnight serum starvation (to ensure low signaling levels) before treatment with PMA or BK. Fully SDS-dissociated tyrosine-phosphorylated proteins were immunoprecipitated with 4G10 before SDS–polyacrylamide gel electrophoresis (PAGE) and α11.2 IB (Figure 10B, C). As before, PMA and BK induced in average an about 2.5-fold increase in tyrosine phosphorylation of the α11.2 subunit, which was strongly repressed by Sh1 (Figure 10B–D). IB for total Pyk2 content confirmed Pyk2 knockdown by ~70–90% (Figure 10B, C, bottom panels). These findings indicate that depletion of Pyk2 potently blunts the PKC-mediated increase in α11.2 tyrosine phosphorylation. Total α11.2 content was not altered by Sh1. These findings indicate that Pyk2 knockdown does not affect α11.2 expression levels and that the reduction in tyrosine-phosphorylated α11.2 is likely not due to any potential off-target effects of the pVETL-Sh1-shRNA.

To further verify and extend these findings we obtained HIV-GFP lentiviral vectors for expression of validated unique 29mer shRNAs targeting Pyk2 (HIV-GFP-Pyk2ShA-D) and Src (HIV-GFP-SrcShA-D) as well as a scrambled, non-silencing control (HIV-GFP-Shscr). HIV-GFP-Pyk2ShB and C and HIV-GFP-SrcShB and C were most effective in knocking down endogenous Pyk2 and Src, respectively (Figure 10E, F and data not shown). PC12 cells were transduced with HIV-GFP-Pyk2ShB and C and HIV-GFP-Shscr, serum starved, stimulated with PMA, harvested, and lysed before 4G10 IP and IB for α11.2, Pyk2, Src, and tubulin. Total protein levels of α11.2, Pyk2, Src, and tubulin in lysate were monitored in parallel. The Pyk2-targeting HIV-GFP-Pyk2ShB and C but not the scrambled control shRNA abrogated the PMA-induced increase in α11.2 tyrosine phosphorylation (Figure 10G). Similarly, the Src-targeting HIV-GFP-SrcShB and C but not the scrambled control shRNA blocked the increase in α11.2 tyrosine phosphorylation upon PMA application (Figure 10G, H). For quantification, phosphotyrosine signals were normalized to total α11.2 in lysate (Figure 10I). None of the HIV viral constructs exhibited any detectable effects on protein expression of α11.2, Pyk2, Src, or α-tubulin, vinculin, and GAPDH as determined in lysates suggesting these constructs did not affect general protein expression. Collectively, the above findings indicate that knockdown effects were specific and not simply the consequence of viral infection or expression of non-specific stem-loop RNAs. Taken together, our findings strongly support the hypothesis that PKC signaling mediates its effects on CaV1.2 through Pyk2 and Src.

Inhibition of Pyk2 and Src blocks LTCC-dependent LTP

CaV1.2 is concentrated in dendritic spines (Hall et al., 2013; Hell et al., 1996; Leitch et al., 2009) where it mediates Ca2+ influx (Bloodgood and Sabatini, 2007; Hoogland and Saggau, 2004) and several forms of LTP (Grover and Teyler, 1990; Moosmang et al., 2005; Patriarchi et al., 2016; Qian et al., 2017; Tigaret et al., 2021). Notably, in older mice and rats, about half of the LTP (called LTPLTCC) induced by four 200 Hz tetani, each 0.5 s long and 5 s apart, is insensitive to NMDAR blockade but abrogated by inhibition or elimination of CaV1.2 (Boric et al., 2008; Grover and Teyler, 1990; Moosmang et al., 2005; Shankar et al., 1998; Wang et al., 2016). Pharmacological inhibition and genetic disruption of CaV1.2 also abolish LTP induced by either pairing presynaptic stimulation with backpropagating action potentials (Magee and Johnston, 1997; Tigaret et al., 2021; Tigaret et al., 2016) or by 5 Hz/3 min tetani, the latter form of LTP requiring β2AR signaling to upregulate CaV1.2 activity (Patriarchi et al., 2016; Qian et al., 2012; Qian et al., 2017). Thus, we hypothesized that upregulation of CaV1.2 activity by α1AR signaling can augment LTCC-dependent forms of LTP.

LTPLTCC is prominent in mice older than 1 year (30–40% above baseline) but small in mice younger than 3 months (10–15% above baseline) (Boric et al., 2008; Shankar et al., 1998). LTPLTCC requires CaV1.2 activity (Moosmang et al., 2005) and stimulation of PKC signaling via type I metabotropic glutamate receptors (mGluR) (Wang et al., 2016). We tested whether increasing CaV1.2 activity through α1AR–PKC–Pyk2–Src signaling can augment LTPLTCC. Similar to previous reports (Boric et al., 2008; Shankar et al., 1998), LTPLTCC was ~10% and was not statistically significant above baseline in our 13- to 20-week-old mice (Figure 11A). However, when CaV1.2 activity was upregulated by stimulation of α1ARs with PHE, robust LTPLTCC occurred (p ≤ 0.05, Figure 11A). This augmentation of LTPLTCC was completely blocked by the LTCC inhibitor nimodipine and the α1AR antagonist prazosin (both p ≤ 0.001, Figure 11A). Thus, this elevated potentiation strictly depends on both the activity of LTCCs and signaling through α1ARs. Importantly, this LTPLTCC is also blocked by the Pyk2 inhibitor PF-719 and the Src inhibitor PP2 (both p ≤ 0.001, Figure 11B). These data indicate that robust LTPLTCC in 13- to 20-week-old mice requires Pyk2 and Src activity downstream of engaging α1AR to boost LTCC activation to sufficient levels.

α1AR signaling augments LTPLTCC through L-type Ca2+ channel (LTCC) activity, Pyk2, and Src.

LTPLTCC was induced by four 200 Hz tetani, each 0.5 s long, in the CA3 Schaffer collateral projections to CA1 in acute hippocampal slices from 13- to 20-week-old mice. (A) LTPLTCC required phenylephrine (PHE; 10 μM) and was prevented by the LTCC blocker nimodipine (10 μM; NIMO) and the α1AR antagonist prazosin (1 μM; PRAZ). F3,36 = 9.937. Control vs. PHE, p = 0.012; PHE vs. PHE/PRAZ, p = 0.0001; PHE vs. PHE/NIMO, p = 0.0003. (B) PHE-mediated long-term potentiation (LTP) is blocked by inhibitors of Pyk2 (1 μM PF-719) and Src (10 μM PP2). F2,30 = 13.90. PHE vs. PHE/PF-719, p = 0.0002; PHE vs. PHE/PP2, p = 0.0003. Dot plots on the right show potentiation of field excitatory postsynaptic potentials (fEPSPs) determined as the averages of all responses between 45 and 50 min after high-frequency stimulation (HFS) as % of averages of all responses in the 5 min preceding HFS. Bars and whiskers represent means ± standard error of the mean (SEM; *p ≤ 0.05, ***p ≤ 0.001; one-way analysis of variance [ANOVA] with the Bonferroni correction). The number of slices and mice used is indicated.

Discussion

NE is arguably the most important neuromodulator for alertness and attention, augmenting multiple behavioral and cognitive functions (Berman and Dudai, 2001; Cahill et al., 1994; Carter et al., 2010; Hu et al., 2007; Minzenberg et al., 2008). The Gq-coupled α1AR has a higher affinity for NE than βARs and has been implicated in many studies in attention and vigilance (Bari and Robbins, 2013; Berridge et al., 2012; Hahn and Stolerman, 2005; Hvoslef-Eide et al., 2015; Liu et al., 2009; Puumala et al., 1997; Robbins, 2002). Inspired by our earlier findings that CaV1.2 forms a unique signaling complex with β2AR, Gs, AC, and PKA, making it a prominent effector of NE (Davare et al., 2001; Patriarchi et al., 2016; Qian et al., 2017), we tested and found that CaV1.2 is also a main target for NE signaling via the α1AR. Given that CaV1.2 fulfills numerous functions in many cells this is a key and critical finding (Jacquemet et al., 2016; Splawski et al., 2004). In the following paragraphs, we discuss the four central and notable outcomes of our study.

Firstly, we found that stimulation of the α1AR or the BK receptor strongly increased LTCC activity in neurons (Figures 1, 2,, 46). Stimulation of two other major classes of Gq-coupled receptors in neurons, mGluR1/5 and muscarinic M1/3/5 receptors affected LTCC activity at the cell soma only modestly or not at all, respectively (Figure 2—figure supplement 1). Accordingly, Gq-mediated signaling augments LTCC activity upon stimulation of defined but not all Gq-coupled receptors. Thus, activity of LTCCs is selectively regulated by α1AR and BK receptor signaling. Perhaps Gq-coupled mGluR and muscarinic receptors are not as close to the LTCCs that were recorded in somata than the α1AR or BK receptor, limiting their contribution to regulating CaV1.2. Defining what restricts the receptor type that can regulate LTCCs will be an interesting avenue of future investigation.

Remarkably, inhibitors of PKC, Pyk2, and Src reduce under nearly all conditions CaV1.2 baseline activity and also tyrosine phosphorylation of CaV1.2, Pyk2, and Src even when activators for α1AR and PKC were present. Especially notable is the strong reduction of channel activity way below the control conditions by the Src inhibitor PP2 as well as the PKC inhibitor chelerythrine in Figure 2C. This effect is consistent with PP2 strongly reducing down below control conditions tyrosine phosphorylation of Src (Figure 8J), Pyk2 (Figure 8L), and CaV1.2 (Figure 9E) even with the PKC activator PMA present. These findings suggest that Pyk2 and Src experience significant although clearly by far not full activation under basal conditions as reflected by their own phosphorylation status, which translates into tyrosine phosphorylation of CaV1.2 under such basal conditions.

Secondly, we identified a complex PKC/Pyk2/Src cascade that mediates regulation of CaV1.2 by the α1AR. Clear evidence for this signaling pathway is provided by the inhibition of PHE-induced upregulation of LTCC activity by inhibitors of PKC, Pyk2, and Src (Figure 2), which is further supported by the finding that direct stimulation of PKC also upregulates LTCC activity via Pyk2 and Src (Figure 3). The role of the PKC/Pyk2/Src pathway in regulating CaV1.2 is also substantiated by the association of Pyk2 in addition to Src and PKC with CaV1.2 (Figure 7) and inhibition of PKC-induced tyrosine phosphorylation of CaV1.2 by Pyk2 and Src inhibitors (Figure 9) and Pyk2 and Src knockdown (Figure 10). Multiple shRNAs specifically targeting both Pyk2 and Src efficiently prevented the PKC-mediated increase in α11.2 tyrosine phosphorylation. These observations not only confirm that Pyk2 mediates the CaV1.2 regulation downstream of PKC but also indicates that Src itself is in this context a relevant member of the Src kinase family.

Thirdly, we found that Pyk2 is firmly associated with CaV1.2 under basal conditions as reflected by their co-IP (Figure 7). This association places Pyk2 into a complex that also contains its immediate upstream activator and downstream effector, that is, PKC and Src. PKC can directly bind to the distal C-terminal region of α11.2, which also contain S1928 (Yang et al., 2005). Given that S1928 is a phosphorylation site for PKC (Yang et al., 2005), it is conceivable that PKC binding to this region reflects a temporary kinase–substrate interaction rather than a more permanent association of PKC with CaV1.2, although this consideration does not rule out that PKC can stably bind to another region in the C-terminus of α11.2. In addition, the A kinase anchor protein AKAP150, which is a major interaction partner for CaV1.2 (Davare et al., 1999; Hall et al., 2007; Oliveria et al., 2007), binds not only PKA but also PKC (Klauck et al., 1996) and constitutes another potentially constitutive link between PKC and CaV1.2 (Navedo et al., 2008). Furthermore, like Pyk2, Src co-precipitates with CaV1.2 (Figure 7) and binds directly to α11.2 (Bence-Hanulec et al., 2000; Chao et al., 2011; Hu et al., 1998). Our determination that Pyk2 co-precipitates with CaV1.2 from not only brain but also heart indicates that CaV1.2 forms a signaling complex with Pyk2 and Src and possibly also PKC in various tissues.

We identified the loop between domains II and III of α11.2 as the binding site for Pyk2. This observation lends further support to the association of Pyk2 with CaV1.2. Of note, Src binds to residues 1955–1973 in rat brain α11.2 (corresponding to residues 1982–2000 in the original rabbit cardiac α11.2 Mikami et al., 1989; Bence-Hanulec et al., 2000; Chao et al., 2011). This interaction with α11.2 might bring Src in close proximity to loop II/III-associated Pyk2 to augment their structural and functional interaction once Pyk2 has been activated by PKC.

Formation of supramolecular signaling complexes or ‘signalosomes’ consisting of kinases and their ‘customers’ ensures fast, efficient, and specific signaling (Dai et al., 2009; Dodge-Kafka et al., 2006). Our work establishes the PKC–Pyk2–Src–CaV1.2 complex as such a signalosome. Furthermore, it defines how various Gq-coupled receptors stimulate the activity of CaV1.2 in different cells. The remarkably strong upregulation of CaV1.2 channel activity by Src (Bence-Hanulec et al., 2000; Gui et al., 2006) and upon activation of the PKC–Pyk2–Src signaling cascade as shown here rivals the upregulation by β-adrenergic signaling, which is a central and thus widely studied mechanism of regulating Ca2+ influx into cardiomyocytes during the fight or flight response (Balijepalli et al., 2006; Bean et al., 1984; Fu et al., 2013; Fu et al., 2014; Fuller et al., 2010; Lemke et al., 2008; Liu et al., 2020; Reuter, 1983). Of note, CaV1.2 assembles all components required for β-adrenergic signaling including the β2AR, Gs, adenylyl cyclase, and PKA in brain (Davare et al., 2001; Davare et al., 1999; Man et al., 2020) and heart (Balijepalli et al., 2006). Formation of this complex is important for upregulation of CaV1.2 activity (Balijepalli et al., 2006; Patriarchi et al., 2016) and LTP of glutamatergic synapses induced by a 5-Hz theta rhythm during β-adrenergic stimulation (Patriarchi et al., 2016; Qian et al., 2017). Analogously, assembly of the PKC–Pyk2–Src–CaV1.2 signalosome may be important for fast and specific regulation of CaV1.2 by the α1AR. This hypothesis can now be tested by pursuing determination of the precise binding site of Pyk2 in the loop between domains II and III of α11.2 and then disrupting this interaction with peptides and point mutations. However, our initial attempts to narrow down the binding region by binding studies with six synthetic ~25 residue long overlapping peptides that spanned loop II/III failed (data not shown). Perhaps the Pyk2-binding site in loop II/III requires tertiary structural elements or sequences that were distributed between two neighboring peptides (which overlapped by five residues).

In rat brain neurons, LTCC activity can be increased by Src via phosphorylation of α11.2 on Y2122 (Bence-Hanulec et al., 2000; Gui et al., 2006). However, this phosphorylation site is not conserved even within rodents. It is equivalent to position 2150 in rabbit cardiac α11.2, which is a Cys and not Tyr residue (Mikami et al., 1989). Accordingly, other Tyr residues must serve as phosphorylation sites. It will be an interesting challenge for future work to identify the exact phosphorylation site and then test its functional relevance.

Remarkably, the Src inhibitor PP2 also completely blocked PKC-induced autophosphorylation of Pyk2 on Y402 (Figure 8K, L). This finding indicates a close interdependence between Pyk2 and Src activation by PKC in PC12 cells (depicted in Figure 8A). It is consistent with earlier results indicating that Pyk2 activation (assessed by Y402 phosphorylation) requires catalytically active Src (Cheng et al., 2002; Shi and Kehrl, 2004; Sorokin et al., 2001; Zhao et al., 2016), although in other systems Y402 phosphorylation was not dependent on Src (Corvol et al., 2005; Park et al., 2004; Yang et al., 2013). Accordingly, Pyk2 autophosphorylation on Y402 and the consequent binding of Src to phosphoY402 induces Src-mediated phosphorylation of Pyk2 on Y579 or Y580 in its activation loop, which further enhances Pyk2 activity beyond the level achieved by Pyk2 autophosphorylation on Y402 (Dikic et al., 1996; Lakkakorpi et al., 2003; Li et al., 1999; Park et al., 2004). Such interdependence was supported by the observation that Y579 phosphorylation upon PKC stimulation by either PMA or BK was also completely blocked by the Src inhibitor PP2 (Figure 8K, M).

Fourthly and finally, LTPLTCC induced by 200 Hz tetani in 13- to 20-week-old mice required stimulation of α1ARs and is completely blocked by inhibitors of LTCC, Pyk2, and Src (Figure 11). Incidentally, we were not able to induce any LTPLTCC in mice younger than 13 weeks. Taken together, our findings suggest that LTPLTCC requires stimulation of CaV1.2 activity by α1AR–PKC–Pyk2–Src signaling. While we focus here on the importance of α1AR signaling for LTPLTCC, this is not the only form of LTP that requires upregulation of Ca2+ influx through CaV1.2. Prolonged theta tetanus LTP (PTT-LTP), which is induced by a 3-min-long 5 Hz tetanus, also depends on upregulation of CaV1.2 activity (Boric et al., 2008; Cavuş and Teyler, 1996; Grover and Teyler, 1990; Moosmang et al., 2005; Wang et al., 2016). In PTT-LTP, this upregulation is accomplished by β2AR–Gs–adenylyl cyclase/cAMP–PKA signaling and the ensuing phosphorylation of the central pore-forming α11.2 subunit of CaV1.2 on S1928 by PKA (Patriarchi et al., 2016; Qian et al., 2012; Qian et al., 2017). Whether signaling by NE through α1AR and β2AR can act in parallel and is additive will be an interesting question for future studies. However, we already know that at least for classic PTT-LTP β2AR signaling is sufficient and does not require engagement of α1AR signaling (Qian et al., 2012). Because regulation of CaV1.2 by β2AR signaling is highly localized (Davare et al., 2001; Patriarchi et al., 2016), it is conceivable that α1AR signaling might engage a subpopulation of CaV1.2 channels whose spatial distribution differs from that of β2AR-stimulated CaV1.2 in dendrites. Alternatively, parallel engagement of α1AR and β2AR signaling might ensure more robust and possibly additive or synergistic responses both at the CaV1.2 channel level and in the synaptic potentiation that results.

LTP is thought to underlie learning and memory (Choi et al., 2018; Whitlock et al., 2006). Conditional knock out of CaV1.2 in the hippocampus and forebrain impaired LTPLTCC as well as initial learning (Moosmang et al., 2005) and long-term memory of spatial Morris water maze tasks (White et al., 2008). Moreover, decreased CaV1.2 expression or infusion of LTCC blockers into the hippocampus impaired both, LTP induced by pairing backpropagating action potentials in dendrites with synaptic stimulation and latent inhibition (LI) of contextual fear conditioning, the latter requiring learning to ignore non-relevant environmental stimuli (Tigaret et al., 2021). These CaV1.2-related learning deficits might be in part due to impaired attention the animals pay to their experimental environment during learning phases, processes requiring concerted attention (Panichello and Buschman, 2021). Attention, in turn, depends on the neurotransmitter NE, which might augment spatial learning through regulation of CaV1.2 via α1AR–PKC–Pyk2–Src signaling.

CaV1.2 is increasingly implicated in not just the postsynaptic physiological functions discussed above. Multiple genome-wide association studies point to variants in the CaV1.2 gene, CACNA1C, as major risk factors for schizophrenia, bipolar disorder, and other mental diseases (Bhat et al., 2012; Ferreira et al., 2008; Green et al., 2010; Nyegaard et al., 2010; Smoller, 2013; Splawski et al., 2004). Other studies link chronic upregulation of CaV1.2 activity to etiologies behind senility and Alzheimer’s disease (e.g., Davare and Hell, 2003; Deyo et al., 1989; Disterhoft et al., 1994; Thibault and Landfield, 1996). Thus, it appears likely that dysfunctional regulation of CaV1.2 contributes to these diseases, making the detailed molecular analyses of the signaling paradigms that regulate its functionality especially important to advance our mechanistic understanding for development of future therapies.

Here, we establish for the first time that NE upregulates CaV1.2 activity via a complex α1AR signaling cascade through PKC, Pyk2, and Src, the activity of each component being essential for LTPLTCC and thus most likely relevant for learning. Our work forms the foundation for future studies to uncover the physiological context in which this action of NE is specifically engaged, what the precise role for each kinase is in this signaling cascade regulating CaV1.2 activity, and how the individual kinases could be coordinately regulated to further fine-tune CaV1.2 function. Given the central role of NE in attention and the many physiological and pathological aspects of CaV1.2, regulation of this channel via NE–α1AR signaling predictably will elicit widespread and profound functional effects.

Materials and methods

Materials availability statement

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Further information and requests for resources and reagents should be directed to and will be fulfilled by the corresponding authors, Mary C. Horne (mhorne@ucdavis.edu) and Johannes W. Hell (jwhell@ucdavis.edu).

Experimental model and subject details

Animals

Pregnant Sprague-Dawley (SD) rats were ordered from Envigo (Order code 002) or Charles River (Strain code 001) and E18 embryos were used for preparation of dissociated hippocampal neuronal cultures. SD rats used for preparation of tissue extracts from heart and brain were of either sex and around 3 months old. For LTP experiments, mice of the strain B6129SF1/J aged between 13 and 18 weeks (both males and females) were used.

Animals were maintained with a 12/12 hr light/dark cycle and were allowed to access food and water ad libitum. All procedures followed NIH guidelines and had been approved by the Institutional Animal Care and Use Committee (IACUC) at UC Davis (Protocol # 20673 and 22403).

Primary hippocampal neuronal cultures

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Primary hippocampal neurons were maintained at 37°C in humidified incubators under 5% CO2 and 95% air. Both male and female rat embryos were used to prepare the cultures. Neurons were maintained in a medium containing 1× B-27 supplement (Gibco Cat#17504044), 1× Glutamax (Gibco Cat#35050061), 5% fetal bovine serum (FBS, Corning Cat#35-010-CV), and 1 µg/ml gentamicin (Gibco Cat#15710-064) in Neurobasal medium (Gibco Cat#21103-049). 10 µM each of 5-fluoro-2′-deoxyuridine (Sigma-Aldrich Cat#F0503) and uridine (Sigma-Aldrich Cat#U3003) were added around DIV7 to block the growth of glial cells.

Cell lines

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All cells were grown at 37°C in humidified incubators under 5% CO2 and 95% air. Rat pheochromocytoma cell line PC12 (ATCC Cat# CRL-1721; RRID:CVCL_0481, male) was grown in RPMI 1640 media (Gibco Cat#11875-101) containing 10% horse serum (HS, Gemini Bio Products Cat#100-508) and 5% FBS. For serum starvation, PC12 were incubated for 18 hr in RPMI 1640 media containing 1% HS and 0.5% FBS. HT-1080 cells (ATCC CCL-121; RRID:CVCL_0317, male) used for virus titration were grown and maintained in MEM (Gibco Cat#11095-080) supplemented with 10% FBS. HEK293T/17 (ATCC Cat# CRL-11268, RRID:CVCL_1926, female) cells were routinely cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% FBS (Gibco Cat#11995-065). Cell lines used were obtained from ATCC, expanded and frozen at low passage number. Care was taken during the use of cell lines to ensure that only one cell line was processed in the culture hood at a time, and that they were used within 25–30 passages. Their morphology in culture and doubling time were routinely monitored as were other distinguishing properties such as high transfectability (HEK293T/17 cells) or high CaV1.2 expression (PC12 cells) before the time of experimental use.

Authentication of cell lines

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All three cell lines HEK293T/17, HT1080,and PC12 cells were obtained from ATCC, a well-established and highly reliable source for cell lines. These are the only cell lines currently used in our lab, minimizing further any potential for confusion.

HEK293T/17 was only used for production of virus for knockdown of Pyk2 and Src and initial testing for efficacy of respective knockdown and not for data collection. It was mostly authenticated by inspection of shape and determination of viability as well as the absence of voltage-gated ion channels including CaV1.2 as tested electrophysiologically (all hallmarks of endothelial cells like HEK293 cells). All viruses produced with this cell line were of the expected titer and infectivity as tested. Further, the knockdown results for ectopically expressed Pyk2 and Src in these HEK293T cells were consistent with subsequent knockdown of endogenous Pyk2 and Src in our PC12 cells by several viruses with respective shRNA (Figure 9 and data not shown).

HT1080 was exclusively used for testing viral titer and mostly authenticated by inspection of shape and determination of viability.

PC12 cells are derived from a pheochromocytoma tumor and were verified in different ways. Firstly, they had the typical appearance described earlier, with some ‘rugged’ edges under basal conditions. Upon addition of nerve growth factor (NGF) they adopted a more neuron-like appearance with elongated protrusions reminiscent of short neurites. This response to NGF is a clear hallmark of PC12 cells and the reason why they are popular for use in biochemical experiments when neuron-like cultured cells are needed. Additional parameters were expression of L-type Ca channels as determined electrophysiologically (data not shown) and biochemically specifically for CaV1.2 as thoroughly analyzed in this study (Figures 810). In addition, expression of the BK receptor and its downstream effectors Pyk2 and Src is known to be very prominent in PC12 cells. (Pyk2 was first identified in PC12 cells) and again regularly observed in our thorough biochemical analysis.

Test for mycoplasma was performed per commercial PCR and was negative.

Methods details

Culture of primary hippocampal neurons

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Hippocampal neurons were cultured from wild-type E18 male and female embryos from SD rats. Hippocampus was excised from the brains of embryos in ice-cold Hank’s Buffer (Sigma-Aldrich Cat#H2387) with 10 mM 4-(2-Hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) (Gibco Cat#15630-080), 0.35 g/l NaHCO3 and 5 µg/ml gentamicin (Gibco Cat#15710-064) and digested in 0.78 mg/ml papain (Roche Cat#10108014001) in 5 ml of the same buffer at 37°C for 30 min, in an incubator containing 5% CO2 and 95% air. Digested hippocampal tissue was washed with neuron medium twice, and triturated in the medium. The medium used for washes, trituration and culture of neurons consists of 1× B-27 supplement, 1× Glutamax, 5% FBS, and 1 µg/ml gentamicin in Neurobasal medium (as stated in Experimental model and subject details). 15,000 neurons were plated per well in 24-well plates on coverslips coated with poly-DL-ornithine (Sigma-Aldrich Cat#P0671) and laminin (Corning Cat#354232) and cultured in an incubator at 37°C and 5% CO2 and 95% air.

Single-channel recording – determination of overall channel activity (N × Po)

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Single-channel recording was performed at room temperature on hippocampal neurons on DIV10–15 using the cell-attached configuration at an Olympus IX50 inverted microscope as before (Patriarchi et al., 2016; Qian et al., 2017). The membrane potential was fixed at ~0 mV using a high K+ external solution. The external (bath) solution contained (in mM) 145 KCl, 10 NaCl, 10 HEPES, and 30 D-glucose (pH 7.4 with NaOH, 325–330 mOsM). The internal (pipette) solution contained 110 mM BaCl2, 20 mM tetraethylammonium chloride (TEA-Cl), 10 mM HEPES, 500 nM BayK 8644 (Tocris Cat#1546; 200 nM used for Figures 1 and 2; 500 nM used for Figure 3), and 1 µM each of ω-conotoxins MVIIC and GVIA (China Peptides, custom synthesized) (pH 7.2 with TEA-OH, 325–330 mOsM). 3.5–5.5 MΩ resistance pipettes were used. The concentrations of kinase inhibitors, α1AR receptor blocker and agonist are as indicated in the figure legends. Neurons were preincubated with kinase inhibitors or receptor blocker in culture medium for 10 min prior to the experiment, and kinase inhibitors and receptor blocker were, where relevant, present in the external solution during recording. In experiments where isradipine was used, it was placed in the pipette solution, and no pre-incubation with isradipine was performed. Recordings started within 10 min of placing coverslips in the recording chamber in a bath solution with or without PHE (Sigma-Aldrich Cat#P6126), PMA (Merck Millipore Cat#524400), and different kinase inhibitors and receptor blocker. Currents were sampled at 100 kHz and low-pass filtered at 2 kHz using an Axopatch 200B amplifier (Axon Instruments) and digitized using Digidata 1440A digitizer (Axon Instruments). Step depolarizations of 2-s duration (one sweep) were elicited to the patch from −80 to 0 mV at a start-to-start stimulation interval of 7 s. Typically, 100 sweeps were recorded per neuron and only cells with more than 70 sweeps recorded were analyzed. The single-channel search event detection algorithm of Clampfit 10.7.0.3 (Axon Instruments) was used to analyze single-channel activities. Ensemble average traces were computed by averaging all sweeps from one neuron and averaging the averaged traces from all neurons in each group.

Single-channel recording – determination of Po

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To specifically determine unitary channel open probability Po, borosilicate pipettes with a resistance of 7–12 MΩ were used. Only patches with no more than 4 channels (k ≤ 4) were included in the Po analysis to not overinterpret Po (Horn, 1991). Data were corrected by the number of channels (k = 1) as previously described (Bartels et al., 2018; Turner et al., 2020). Unitary LTCC events from hippocampal neurons (DIV15–25) where isolated through blocking N/P/Q-type calcium channels by using 1 µM each of ω-conotoxins MVIIC and GVIA (China Peptides, custom synthesized) in the patch pipette and recorded as above at room temperature by step depolarizations from −80 to 0 mV. Extracellular bath solution contained 125 mM K-glutamate, 25 mM KCl, 2 mM MgCl2, 1 mM CaCl2, 1 mM ethylene glycol bis(2-aminoethyl)tetraacetic acid (EGTA), 10 mM HEPES, 10 mM glucose, and 1 mM Na-ATP, pH 7.4 with KOH. Depolarizing pipette solution contained 110 mM BaCl2 and 10 mM HEPES, adjusted to a pH of 7.4 with TEA-OH. Data acquisition was performed at a sampling frequency of 10 kHz with an interpulse time of 5 s and data were low pass filtered at 2 kHz. The positive identification of LTCC activity was consequently tested by bolus application of either the dihydropyridine (DHP) BayK8644 (10 µM), which promotes L-type channel opening, or the channel-blocking DHPs isradipine (10 µM) or nimodipine (10 µM) to the bath solution at the end of each experimental run.

Drugs

were prepared as stock solution in dH2O, freshly on the day of experiment respectively, 40 mM prazosin–HCl (Sigma-Aldrich), 20 mM NE bitartrate (Sigma-Aldrich) and 20 mM BK acetate (Sigma-Aldrich). Stocks were diluted again 1:10 or 1:100 and as a bolus directly applied to the bath solution during the recordings.

Co-immunoprecipitation of CaV1.2 with Pyk2 and Src

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Brains and hearts were homogenized with a Potter tissue homogenizer in 10 ml of a homogenization buffer containing 50 mM Tris–HCl (pH 7.4), 150 mM NaCl, 5 mM EGTA pH 7.4, 10 mM ethylenediaminetetraacetic acid (EDTA), 1% Triton X-100, 25 mM NaF, 25 mM sodium pyrophosphate, 1 mM 4-nitrophenyl phosphate, 2 μM microcystin and protease inhibitors (1 μg/ml leupeptin [Millipore Cat#108975], 2 μg/ml aprotinin [Millipore Cat#616370], 10 μg/ml pepstatin A [Millipore Cat#516481] and 200 nM phenylmethylsulfonyl fluoride [PMSF]). High-speed centrifugation was performed at 40,000 rpm for 30 min at 4°C. 500 μg of total brain or heart lysate extracts were incubated with 15 μl of Protein-A Sepharose beads (CaptivA protein resin, Repligen, Cat#CA-PRI-0100) and 2 μg of anti-CaV1.2 α1-subunit or control rabbit IgG antibody. Samples were incubated at 4°C for 4 hr before being washed three times with ice-cold wash buffer (0.1% Triton X-100 in 150 mM NaCl, 10 mM EDTA, 10 mM EGTA, 10 mM Tris, pH 7.4). Samples were then resolved by SDS–PAGE and transferred onto polyvinylidene difluoride (PVDF) membranes before IB with anti-CaV1.2 α1-subunit (J.W. Hell lab), -Pyk2 (Millipore Cat#05-488; RRID:AB_2174219), and -Src (J.S. Brugge lab) antibodies. The antibody dilutions used are listed in Supplementary file 2.

GST pulldown assay

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Fragments of intracellular loops of CaV1.2 α1-subunit (Supplementary file 1; Davare et al., 2000; Gao et al., 2001) were expressed in Escherichia coli strain BL21 as GST fusion proteins, purified, and integrity verified by IB essentially as previously described (Bennin et al., 2002; Frangioni and Neel, 1993; Hall et al., 2013; Hall et al., 2006). Overnight cultures from single colonies of the corresponding plasmids were cultured initially in 50 ml of LB medium containing ampicillin (100 μg/ml) with aeration until saturation. Incubation temperature was optimized for each expression construct to optimize translation and stability and varied between 28 and 37°C. After a 1:10 dilution into the same medium, cultures were grown for about 2–4 hr until an A600 of about 0.8 was reached when isopropyl-β-D-thiogalactopyranoside was added for induction. After 4–5 hr bacteria were collected by centrifugation (5000 rpm, SLA 3000 rotor, Thermo Fisher Cat#07149) for 15 min and resuspended by gentle trituration in ice-cold 50 ml of Tris-buffered saline (TBS) Buffer (150 mM NaCl, 15 mM Tris-Cl, pH 7.4) containing protease inhibitors 1 μg/ml pepstatin A, 1 μg/ml leupeptin, 1 μg/ml aprotinin, and 200 nM PMSF. 0.1 mg/ml lysozyme was added to lyse cell walls. The mixture was kept on ice for 30 min before addition of Sarcosyl (1.5% final concentration), β-mercaptoethanol (10 mM), and DNAse (50 U) for 15 min to fully solubilize the fusion proteins. In order to neutralize Sarcosyl, Triton X-100 was then added to a final concentration of 5%. Insoluble material was removed by ultracentrifugation (1 hr, 4°C, 40,000 rpm, Ti70 rotor, Beckman Coulter Cat#337922). The fragments were immobilized onto glutathione Sepharose (Millipore/Cytiva Cat#17-5132-02) for 3 hr, washed three times with Buffer A (0.1% TX-100, 10 mM Tris–HCl, pH. 7.4) and incubated with affinity-purified His-tagged Pyk2 separately expressed in E. coli (3 hr, 4°C). Beads were washed three times in Buffer A and bound proteins were eluted and denatured in SDS sample buffer, resolved by SDS–PAGE and transferred to a nitrocellulose membrane. IB with anti-Pyk2 antibody (Millipore Cat#05-488; RRID:AB_2174219) was used to detect Pyk2 binding during pulldown.

Analysis of phosphorylation in PC12 cells

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Drugs were used at the following concentrations: 2 µM PMA (Merck Millipore Cat#524400), 1 µM BK (Sigma-Aldrich Cat#05-23-0500), 3 µM PF-431396 (Tocris Cat#4278), 10 µM PP2 (Sigma-Aldrich Cat#P0042), 10 µM PP3 (Tocris Cat#2794), and 10 µM SU6656 (Sigma-Aldrich Cat#S9692).

For phospho-tyrosine analysis PC12 cells were washed after drug treatment twice in ice-cold phosphate-buffered saline (PBS) containing 1 mM pervanadate and 25 mM NaF. Samples were collected in PBS containing pervanadate, NaF, and protease inhibitors (see above), sonicated and extracted with SDS dissociation buffer (50 mM Tris–HCl, 1% SDS) at 65°C for 10 min. The SDS was neutralized with a fivefold excess of Buffer A containing phosphatase and protease inhibitors. 500 μg of total protein from PC12 cell extracts were incubated over night at 4°C with 2 μg of the phospho-tyrosine 4G10 (Sigma-Alrich/Upstate Cat# 05-321; RRID:AB_2891016) or mouse control antibody (Jackson Immunoresearch Cat#015-000-003) and 15 μl of Protein-G Sepharose (Millipore/Cytiva Cat#GE-17-0618-05), washed three times in ice-cold wash buffer (0.1% Triton X-100 in 150 mM NaCl, 10 mM EDTA, 10 mM EGTA, 10 mM Tris, pH 7.4), resolved by SDS–PAGE and transferred onto PVDF membranes for IB. The antibody dilutions used are listed in Supplementary file 2. For re-probing, blots were stripped in 62.5 mM Tris-Cl, 20 mM dithiothreitol (DTT), and 2% SDS at 50°C for 30 min. Chemiluminescence immunosignals were quantified using ImageJ (Rueden et al., 2017) by multiple film exposures of increasing length to ensure signals were in the linear range (Davare and Hell, 2003; Hall et al., 2006). Variations in total amounts of α11.2, Pyk2, and Src in the different PC12 cell lysates were monitored by direct IB of lysate aliquots. Lysate signals were used to correct α11.2 signals after 4G10 IP for such variations by dividing the latter by the former.

Lentiviral constructs for shRNA to Pyk2 and Src

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A list of all shRNA target sequences is provided in Supplementary file 3. The shRNA sequence Sh1 against Pyk2 has been validated for Pyk2 knockdown (Sayas et al., 2006). The Sh1 sequence was cloned in the reverse orientation into the MfeI site of the lentiviral transfer vector pVETL-eGFP (Bartos et al., 2010; Boudreau and Davidson, 2012; Harper et al., 2006) for expression of Pyk2 shRNA and GFP to visualize infection. All HIV plasmids (HIV-GFP-Pyk2shA-D; HIV-GFP-SrcshA-D) for knocking down rat Pyk2 or Src as well as the scrambled, non-silencing hairpin control (HIV-GFP-shscr) were obtained from Origene (Cat# TL710108 and #TL711639). All expression plasmids (listed in Supplementary file 4) were confirmed by DNA sequencing.

Production of lentivirus for Pyk2 and Src knockdown

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HEK293T/17 (ATCC Cat# CRL-11268, RRID:CVCL_1926) cells were plated onto 10 cm dishes at 1.8 × 106 cells per dish and maintained until confluency (60–90%). Cells were transiently transfected with viral expression constructs using the calcium phosphate precipitation method (Jordan et al., 1996). For FIV virus production, cells were transfected in a 3:2:1 ratio of parental vector (pVETL, FIV 3.2): pCPRD-Env: pCI-VSVG for a total of 24 μg of DNA per plate. For production of HIV viral particles targeting Src and Pyk2, cells were transfected at a ratio of 5:2:2:2 of parental vector (e.g., pGFP-Pyk2-shC-Lenti:pCI-VSVG:pMDL g/p RRE:pRSV-REV) according to the manufacturer’s guidelines (OriGene). Media was exchanged 16 hr after transfection. Media containing the packaged recombinant virus was collected at 48 and 72 hr, filtered through 0.45 μm filters, and concentrated by centrifugation (7400 × g for 16 hr at 4°C). The viral pellet was resuspended in ice-cold PBS, aliquoted and stored at −80 °C. Before use for transduction of PC12 cells all viral particle solutions were titered in the HT-1080 cell line (ATCC Cat#CCL-121; RRID:CVCL 0317) by seeding 12-well plates at 5 × 104 cells per well 1 day before infection. 1, 5, and 10 μl of solutions containing concentrated HIV or FIV particles was added to each well and expression of GFP was monitored for 72 hr post-infection before titer was calculated.

Slice preparation and electrophysiology

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After decapitation, brains were removed from 13- to 18-week-old mice. 400-μm-thick transverse slices were made using a vibratome in cold, oxygenated (95% O2 and 5% CO2) dissection buffer (in mM: 87 NaCl, 2.5 KCl, 1.25 NaH2PO4, 26.2 NaHCO3, 25 glucose, 0.5 CaCl2, 7 MgCl2, 50 sucrose). Slices were allowed to recover at room temperature for at least 1 hr in oxygenated artificial cerebrospinal fluid (ACSF) (in mM: 119 NaCl, 3 KCl, 2.5 CaCl2, 1.25 NaH2PO4, 1.3 MgSO4, 26 NaHCO3, 11 glucose). Following recovery, slices were transferred to a recording chamber and maintained at 32–33°C in oxygenated ACSF. Field excitatory postsynaptic potential (fEPSP) was evoked by stimulating the Schaffer collateral pathway using bipolar electrode, and synaptic responses were recorded with ACSF-filled microelectrodes (1–10 MΩ) placed in the stratum radiatum of CA1 region. Recordings were acquired using an Axoclamp-2B amplifier (Axon Instruments) and a Digidata 1332 A digitizer (Axon Instruments). Baseline responses were collected at 0.07 Hz with a stimulation intensity that yielded 40–50% of maximal response. LTP was induced by four episodes of 200 Hz stimulation (0.5 s) with 5-s intervals. To measure LTCC-mediated LTP, 50 μM D-APV (Tocris Cat#0106) was included in ACSF. When used the inhibitors [10 μM nimodipine (Bayer Charge: BXR4H3P), 1 μM prazosin, 1 μM PF-719 (Tse et al., 2012), and 10 μM PP2] were added to ACSF from the start of the recording. PHE (10 μM) was added after at least 15 min of stable baseline, and LTP was induced ~10 min after the addition of PHE.

Quantification and statistical analysis

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Statistical analyses were performed using Prism 5 or 9 (GraphPad). Data are presented as mean ± standard error of the mean. Sample sizes, p values, and statistical tests are indicated in the figure legends. For analysis of channel NPo (Figures 13, Figure 2—figure supplement 1, Figure 3—figure supplement 1), first outliers were identified using iterative Grubb’s method inbuilt in Prism. Then, statistical significance was determined using one-way analysis of variance (ANOVA) with post hoc Holm–Sidak’s multiple comparisons test. For analysis of specifically Po (Figures 46), data were tested either by an unpaired or paired Student’s t-test. For significance testing with more than two groups, a one-way ANOVA with additional Bonferroni correction was applied, p < 0.05%. For analysis of protein phosphorylation, statistical significance was determined using ANOVA with post hoc Bonferroni’s multiple comparisons test (Figures 810). For analysis of LTP (Figure 11), a one-way ANOVA was applied followed by Bonferroni correction.

Data availability

Raw datasets are available on Dryad (https://doi.org/10.25338/B86G9K).

The following data sets were generated
    1. Man K
    2. Bartels P
    3. Henderson PB
    4. Kim K
    5. Shi M
    6. Zhang M
    7. Ho S
    8. Nieves-Cintron M
    9. Navedo MF
    10. Horne MC
    11. Hell JW
    (2023) Dryad Digital Repository
    Raw data for Manuscript entitled "Alpha-1 adrenergic receptor - PKC - Pyk2 - Src signaling boosts L-type Ca2+ channel Cav1.2 activity and long-term potentiation in rodents".
    https://doi.org/10.25338/B86G9K

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    (1992)
    Regulation of Phosphoinositide Kinases in T cells evidence that Phosphatidylinositol 3-kinase is not a substrate for T cell antigen receptor-regulated tyrosine Kinases
    The Journal of Biological Chemistry 267:23869.

Decision letter

  1. Yukiko Goda
    Reviewing Editor; Okinawa Institute of Science and Technology, Japan
  2. Kenton J Swartz
    Senior Editor; National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "α1 adrenergic receptor -PKC -Pyk2 -Src signaling boosts L-type ca2+ channel Cav1.2 activity and long-term potentiation in rodents" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Gary Westbrook as the Senior Editor. The reviewers have opted to remain anonymous.

The reviewers consider the study to be important in identifying a novel signaling pathway involving norepinephrine with consequences on synaptic plasticity, although some key points needing further clarifications that may require some additional experiments and/or modification of the conclusions. The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) Please provide further clarification of whether and how the linker domains II and III act in mediating Pyk2 and Src activation of Cav1.2, for example, by identifying the phosphorylation site and demonstrating its necessity by introducing a mutation.

2) Please confirm that the same pathway is targeted between PC12 cells and hippocampal neurons by testing whether bradykinin elicits the same response in hippocampal neurons.

3) Please provide additional evidence for the claim that alpha1-AR agonist increases Po by ruling out an increase in N caused e.g. by a rapid channel insertion to the membrane surface.

4) Clarify the basis for an apparent baseline modulation of channel activity by the alpha1-AR pathway that is revealed by the effects of inhibitors (Figures 2B, 2D).

In addition, please fully address all the comments raised by the three reviewers involving quantification of data, replacing of immunoblot in Figure 4B, addition of a schematic figure, and clarification/editing of the text.

Reviewer #1 (Recommendations for the authors):

1) My main critique would be that the study, while very well executed and rigorous, is fragmented, consisting of three parts that each feel incomplete: i, hippocampal neuron studies, mainly single channel recordings; ii, biochemical studies mainly in PC12 cells, using a different agonist bradykinin, and iii, the examination of LTP in young mice.

2) Does Norepinephrine activate this pathway in hippocampal neurons? This should be testable given the high affinity for NE of the α1-AR (line 487).

3) The single channel recordings cannot distinguish between L-type channels cav1.2 and cav1.3. This would require the use of selective knockout mice.

4) Patches identified to contain only one channel should be used to determine conclusively whether N and/or Po is increased by the α1-AR agonist Phe. This could be done by BayK8644 application at the end of the experiment, for example, as well as data mentioned at line 116. At the moment this cannot be conclusively stated that Po is increased.

5) Line 147, it is unclear why other Gq coupled receptors do not affect this pathway in hippocampal neurons. This is problematic as the study goes on to use bradykinin, rather than an α1-AR agonist in PC12 cells to dissect the pathway (Figure 5 onwards). Does bradykinin stimulate this pathway in hippocampal neurons?

6) If the same pathway is present in PC12 cells then the α1-AR should be expressed in these cells, rather than using bradykinin.

7) It is unclear why PP2 inhibits NPo and ensemble average current far below the baseline control (Figures2B and 2D), whereas SU6656 does not. This suggests non-specificity.

8) The II-III linker is identified as a binding site for Pyk2; but where are the src phosphorylation sites on CaV1.2 specifically mediating this effect? This needs to be identified, otherwise it is possible that the effect is not direct.

9) A diagram of the pathway is important to add, preferably in each figure, to show where every drug is supposed to act.

Reviewer #2 (Recommendations for the authors):

Overall, the work is carefully carried out but there are a few pitfalls, where information lacking. I suggest the authors to address these issues.

1. The pathway from PKC/ca2+, Pyk2, to Src has been already reported more than 20 years ago (see, for example, Sabri et al., Circ. Res 1998 and reference therein). But in this paper, the mechanism how noradrenaline activates Pyk2 through PKC is not known. Also the authors stated that phosphorylation of alpha11.2 by PKC inhibits Cav1.2 activity (52). Why this pathway is not active here?

2. The mechanism how Src activates Cav1.2 is not clear. The authors should make more effort to identify the site and use a mutant to show that it abolishes the increase in the channel activity. They discussed possible tyrosine phosphorylation at Y2122 but they did not confirm this. Also, this residue is located at the very end of protein, far away from the channel. It is not clear how it modulates the channel activity, if it has any function.

Reviewer #3 (Recommendations for the authors):

The authors should consider adding experiments that show whether the linker between domains II and III is indeed the site of regulation.

Editorial Points

Lines 203-207. These sentences are a bit garbled. Please revise.

Lines 272-273. Better wording would be.."binds via phosphoY402 to the SH2 domain".

Line 503. Better wording would be "regulate through".

https://doi.org/10.7554/eLife.79648.sa1

Author response

Essential revisions:

1) Please provide further clarification of whether and how the linker domains II and III act in mediating Pyk2 and Src activation of Cav1.2, for example, by identifying the phosphorylation site and demonstrating its necessity by introducing a mutation.

The relevance of Pyk2 binding to loop II/III lies in the general concept that frequently kinase signaling cascades depend on close proximity of the kinase with the target, often through direct binding. The exact binding sequence might not be close to the location of the phosphorylation site in the linear sequence because the 3-dimensional folding could bring binding and phosphorylation sites close together even if far apart in the linear sequence. Accordingly, loop II/III might not harbor the phosphorylation site, which could be anywhere in the primary sequence of the channel. Thus, identification of the phosphorylation site would likely take significantly longer than one year and without a reasonable level of guarantee of success.

However, along the lines of the Reviewers’ notion to try and define more precisely binding sites and mechanisms for further mechanistic work on Pyk2 interacting with Cav1.2 and specifically loop II/III, we ordered six overlapping fluorescein-tagged peptides that covered the whole loop II/III segment. We attempted binding studies based on fluorescence polarization, as has worked for a number of other binding sites for us in the past. Unfortunately, none of the peptides showed specific binding. Perhaps the binding region is more complex than a simple ~ 20 residue long linear segment, possibly being significantly longer or consisting of multiple short, discontinuous attachment sites that are more than several residues apart but brought together by the three-dimensional folding of loop II/III.

2) Please confirm that the same pathway is targeted between PC12 cells and hippocampal neurons by testing whether bradykinin elicits the same response in hippocampal neurons.

We used the PC12 cell system for our biochemical analysis because such biochemical analysis in hippocampal cultures is impossible due to material limitation. We simply would not be able to grow enough primary hippocampal cultures for this biochemical analysis. PC12 cells have a very strong presence of both, Cav1.2 and Pyk2. They, thus, constitute a perfect system for the biochemical analysis of Pyk2 signaling to Cav1.2. In fact, Pyk2 was first identified and characterized in PC12 cells (e.g., Lev et al., 2005: Nature 376, 737-745; Dikic et al., 2006: Nature 383, 547-549).

The rationale behind analyzing different GPCRs is that different cell types can harbor different sets of GPCRs that are coupled to Gq-PKC signaling. Stimulating Gq – PKC ‘signaling modules’ like the Gq – PKC – Pyk2 – Src module should be transferable between cell types if they share this module even if it would be engaged by different GqPCRs, like the bradykinin receptor versus α 1 AR. In addition, we went to great length in our work to also directly stimulate PKC with the phorbol ester PMA in hippocampal neurons to observe and characterize the increase in LTCC activity and in PC12 cells to observe and characterize the increase in tyrosine phosphorylation. All of these effects were inhibited by Pyk2 and Src inhibitors.

Nevertheless, expression of the Gq-coupled bradykinin receptors is quite prominent in hippocampal neurons. We tested whether their activation would also augment LTCC activity in hippocampal neurons and now report that there is a clear and strong increase in Po in Figure 6.

In these experiments we added BayK8644 at the end of the recording (as suggested by Reviewer 1, #4), which is expected to further upregulate the currents under our cell-attached patch electrode if those are mediated by LTCCs, which was consistently the case (Figure 6). This approach allowed us to confirm the identity of the channels in the patches as L-type and aided in determining the number of channels N in each patch.

3) Please provide additional evidence for the claim that alpha1-AR agonist increases Po by ruling out an increase in N caused e.g. by a rapid channel insertion to the membrane surface.

We now provide more data that support an increase in Po versus N by first forming a cell-attached seal, which isolates the small surface area from which single-channel activity is recorded, and then apply PHE. This acute application of PHE avoids delays in recording as happening when PHE is bath applied before the recording pipette is attached to the cell during which time new channels could have been inserted (Figure 4).

The acute PHE application in these new experiments induced a fast increase in the activity of Cav1.2 channels isolated under the pre-formed patch, arguing that this increase is really due to an increase in Po rather than insertion of new channels into the patch, which appears unlikely in this configuration due to spatial restrains and the time course with which the increase in channel activity happens. Furthermore, we used a recoding pipette with a much smaller diameter than in our original work (resistance of pipets used in our original recordings was 3.5-5.5 MOhm and in these new experiments it was 7-12 MOhm). The reduction in diameter results in patches that contain typically <4 channels, which is required for reliably determining the channel number N whereas the original recordings often contained >4 channels and thus cannot truly be analyzed for N versus Po. To increase our confidence in our capability to count all channels we added BayK8644 at the end of the recordings in one set of experiments (i.e., the bradykinin stimulation; Figure 6).

At the same time, and cautioned by the Reviewers’ comments, we do not want to rule out that there is also an effect of alpha1 AR signaling on channel number N in our original experiments in which cells were pre-treated with PHE or PKC activators before forming the seal. We are now using a more carefully worded interpretation of these original experiments leaving open the possibility that in these initial experiments we also could have had an effect on N. However, we would like to re-emphasize that our new data leave little room for doubt that PHE augments channel activity at least in part by increasing Po.

4) Clarify the basis for an apparent baseline modulation of channel activity by the alpha1-AR pathway that is revealed by the effects of inhibitors (Figures 2B, 2D).

We now explicitly state in the Discussion: “Inhibitors of PKC, Pyk2, and Src reduce under nearly all conditions Cav1.2 baseline activity and also tyrosine phosphorylation of Cav1.2, Pyk2, and Src even when activators for alpha1 AR and PKC were present. Especially notable is the strong reduction of channel activity way below the control conditions by the Src inhibitor PP2 as well as the PKC inhibitor chelerythrine in Figure 2C. This effect is consistent with PP2 strongly reducing down below control conditions tyrosine phosphorylation of Src (Figure 8J), Pyk2 (Figure 8L), and Cav1.2 (Figure 9E) even with the PKC activator PMA present. These findings suggest that Pyk2 and Src experience significant although clearly by far not full activation under basal conditions as reflected by their own phosphorylation status, which translates into tyrosine phosphorylation of Cav1.2 under such basal conditions.” Because there are multiple ways Pyk2 and Src can be activated including Ca influx and cell-matrix interactions, defining the cause of this baseline activity has to remain beyond the scope of the current work.

In addition, please fully address all the comments raised by the three reviewers involving quantification of data, replacing of immunoblot in Figure 4B, addition of a schematic figure, and clarification/editing of the text.

Please note that association of Src with Cav1.2 had previously been described by several authors. To ensure that the reader understands that our Src coIP with Cav1.2 is only confirmatory we now state explicitly: “We also confirmed earlier work (Figure 7A bottom panel) that indicated association of Src with CaV1.2 in vitro (Bence-Hanulec et al., 2000; Endoh, 2005; Gui et al., 2006; Hu et al., 1998; Strauss et al., 1997; Wu et al., 2001) and in intact cells (Bence-Hanulec et al., 2000; Chao et al., 2011; Hu et al., 1998).” Also, we now provide the uncropped immunoblot for Figure 7B, which shows more convincingly that there is a clear band for the Src immunosignal.

Reviewer #1 (Recommendations for the authors):

1) My main critique would be that the study, while very well executed and rigorous, is fragmented, consisting of three parts that each feel incomplete: i, hippocampal neuron studies, mainly single channel recordings; ii, biochemical studies mainly in PC12 cells, using a different agonist bradykinin, and iii, the examination of LTP in young mice.

We would argue that both, the single-channel data and biochemical data, are at a level of completion that is by itself appropriate for eLife, each characterizing a multistep signaling pathway with agonists and antagonists and also shRNA addressing each step in the signaling cascade. The LTP studies are meant to put the signaling pathway we characterized in hippocampal neurons into a larger, network level context by testing effects of key treatment conditions as established for the single-channel and tyrosine phosphorylation data.

2) Does Norepinephrine activate this pathway in hippocampal neurons? This should be testable given the high affinity for NE of the α1-AR (line 487).

We now provide data that show that application of NE after seal formation and after establishing a baseline activity also augments LTCC Po to the same extent as PHE does (compare new Figure 4A-D with new Figure 4E-H). Cav1.2 activity can also be increased by beta2 AR signaling (but not beta1 AR signaling) (Qian et al., 2017: Sci Signal 10, eaaf9659; see also Patriarchi et al., 2016: EMBO J 35, 1330-1345). This upregulation by beta2 AR stimulation is strictly mediated by localized signaling from the b2 AR to Cav1.2 and cannot be engaged when the b2 adrenergic agonist is applied from the outside of the cell attached patch formed by the recoding electrode (Davare et al., 2001: Science 293, 98-101, as cited). Thus, the increase in Po upon bath application of NE after seal formation suggests that NE as the cognate ligand for alpha1 AR can stimulate Cav1.2 activity to the same degree as PHE.

3) The single channel recordings cannot distinguish between L-type channels cav1.2 and cav1.3. This would require the use of selective knockout mice.

It is possible that the alpha1AR signaling also regulates Cav1.3 but Cav1.3 only constitutes ~20% when Cav1.2 constitutes ~80% of all L-type channels in hippocampus (Hell et al., 1993: JCB 123, 949-962; Sinnegger-Brauns et al., 2004: J Clin Invest 113, 1030-1439). Accordingly, it seems hard to imagine that the observed effects on LTCC activity could be explained solely by upregulation of Cav1.3, which would have to be extremely high to solely explain an increase in Po by 3- to 4-fold as seen in Figure 1B. With Cav1.3 only contributing 20% of the activity, this activity would have to be increased by well over 10-fold to explain an overall increase of Po of all L-type channels by twofold if the effect is solely via Cav1.3. It would be very involving to obtain conditional Cav1.2 KO mice to further prove this point and likely take well beyond one year given that we would have to import appropriate floxed mice to UC Davis (which often takes 6 months by itself, given paperwork and regulations) and then set up the breeding scheme. A full KO of Cav1.2 would in theory be easier to set up but is embryonically lethal.

4) Patches identified to contain only one channel should be used to determine conclusively whether N and/or Po is increased by the α1-AR agonist Phe. This could be done by BayK8644 application at the end of the experiment, for example, as well as data mentioned at line 116. At the moment this cannot be conclusively stated that Po is increased.

To get patches with a single channel are very rare. Figures 1, 2, and 3 are based on a total of 295 recordings under the various conditions conducted over more than 3 years. Of all of these recordings, only 21 (7%) had a single channel active at any point in time perhaps reflecting that only a single activatable channel was present in the patch. The rest (93%) of all recordings had at least 2 and typically more channels. Accordingly, it is impossible to limit analysis to patches with single channels in these experiments.

The new experiments described in response to Essential revisions point #3 (i.e., PHE increases Po when acutely applied from outside the recording electrode; Figure 4) indicates that we can detect an increase in Po when PHE is applied after seal formation. This approach complements the previous experiments when PHE was pre-applied before seal formation when more channels could be inserted into the plasma membrane during the time period between the start of the drug treatment and seal formation. In addition, we used in these new experiments recording pipettes with a smaller diameter (resistance was increased from originally 3.5-5.5 to 7-12 MOhm in these experiments), which typically yields between 1-4 channels. To confirm that the new recording conditions did typically not yield more than 4 channels, BayK8644 was added at the end of the recordings in one set of experiments (Figure 6) to ensure that our quantification of channel number N is accurate and complete. Accordingly, this approach allowed us to define patches with <4 channels for which we can reliably extract N and thereby also Po. Thus, we can now be certain that PHE specifically augments Po and not more generally NPo.

5) Line 147, it is unclear why other Gq coupled receptors do not affect this pathway in hippocampal neurons. This is problematic as the study goes on to use bradykinin, rather than an α1-AR agonist in PC12 cells to dissect the pathway (Figure 5 onwards). Does bradykinin stimulate this pathway in hippocampal neurons?

We now document that bradykinin can augment Po of LTCC in hippocampal neurons (new Figure 6). Please see response to Essential revisions point #2 for additional details.

6) If the same pathway is present in PC12 cells then the α1-AR should be expressed in these cells, rather than using bradykinin.

Systematic radioligand binding studies and functional stimulation assays did not detect any evidence for the presence of any adrenergic receptor subtypes in PC12 cells (neither alpha1, alpha2 or β AR; Williams et al., 1998: J Biol Chem 273, 24624-24632). In fact, this publication and several subsequent studies reported the use of PC12 cells to heterologously express AR subtypes to study the signaling mechanisms and functional effects of individual subtypes (e.g., Zhong and Minnemann, 1999: J Neurochem 72, 2388-2396; Olli-Lähdesmäki et al., 1999: J Neurosci. 19, 9281-9288). This strategy speaks to the relevance of the concept of ‘transposable’ signaling modules between different GqPCRs, which can engage PKC-Pyk2-Src signaling with the trimeric Gq – phospholipase C β – PKC module being the common denominator that then triggers the rest of the cascade in some but may be not all contexts.

Because our main goal is to define how Cav1.2 is regulated in neurons, for the revision we opted to test Bradykinin in neurons, as suggested by the Reviewing Editor. Also, we had tested in both experimental systems the effect of direct PKC activation by the phorbol ester PMA and of the different Pyk2 and Src inhibitors with completely congruent results (for details, please see response to point #2 by the Reviewing Editor).

7) It is unclear why PP2 inhibits NPo and ensemble average current far below the baseline control (Figures2B and 2D), whereas SU6656 does not. This suggests non-specificity.

This differential effect of PP2 versus SU6656 could hint that Src is not the only Src family kinase (SFK) that is involved with other SFKs perhaps also playing a role as they have different sensitivities to PP2 and SU6656 (see, e.g., Blake et al., 2000: Mol Cell Biol. 20, 9018-9027; Bain et al., 2007: Biochem J 408, 297-315). However, this effect was not consistently observed. In detail, the PP2 effect is not as strong and the SU6656 stronger in Figure 3 compared to Figure 2 (although both inhibitors reduce Po below baseline levels in both figures). These observations are potentially reflecting some experimental or biological variability between experiments as these data were collected over a long time period (>3 years) because these experiments are very time consuming and dependent on, among other factors, obtaining good hippocampal cultures and having very low electric noise in the recording cage, both of which are not trivial. This variability provides an alternative explanation to the notion that another SFK member could be involved.

8) The II-III linker is identified as a binding site for Pyk2; but where are the src phosphorylation sites on CaV1.2 specifically mediating this effect? This needs to be identified, otherwise it is possible that the effect is not direct.

Although Gq-PKC-Pyk2-Src signaling clearly induces tyrosine phosphorylation of the Cav1.2 alpha1 subunit, we cannot exclude that our effects on Po are indirect, i.e., through phosphorylation of another subunit or channel component. However, we feel that the Po effects are of strong functional interest, whether due to direct or indirect phosphorylation. The biochemical work provides now impetus that justifies testing whether phosphorylation of Cav1.2 is mediating the functional effect (we are currently applying for funding for continuation of this project). However, given the already huge time commitment of the current work it seems outside the scope of the current project to determine the relevant phosphorylation sites, which can take years.

As stated in response to Essential revisions point #1 we were not able to define a synthetic peptide derived from loop II/III that would bind Pyk2 and thus cannot use a peptide displacement approach to acutely test the relevance of Pyk2 binding to Loop II/III.

9) A diagram of the pathway is important to add, preferably in each figure, to show where every drug is supposed to act.

We now added a scheme to each figure to make it easier for readers to follow the pathways and experiment design and data interpretation.

Reviewer #2 (Recommendations for the authors):

Overall, the work is carefully carried out but there are a few pitfalls, where information lacking. I suggest the authors to address these issues.

1. The pathway from PKC/ca2+, Pyk2, to Src has been already reported more than 20 years ago (see, for example, Sabri et al., Circ. Res 1998 and reference therein). But in this paper, the mechanism how noradrenaline activates Pyk2 through PKC is not known. Also the authors stated that phosphorylation of alpha11.2 by PKC inhibits Cav1.2 activity (52). Why this pathway is not active here?

In addition to Sabri et al., 1998, the PKC-Pyk2-Src signaling cascade was first identified in PC12 cells (Lev et al., 1995: Nature 376, 737-745; Dikic et al., 1996: Nature 383, 547-549) but no previous work linked this signaling cascade to Ca channel regulation. The primary importance of our work is to define whether and how alpha1 AR signaling regulates Cav1.2 in neurons because norepinephrine is a key neuromodulator that governs attention and, at higher levels, stress responses. The role of alpha1 AR in regulating neuronal Cav1.2 is indicated by our finding that the alpha1 AR-selective agonist PHE increases Po and that this increase is blocked by the alpha1 AR-selective antagonist prazosin. Another important aspect is to define regulation of Cav1.2 by the PKC-Pyk2-Src cascade with PKC, Pyk2, and Src forming a signaling complex with Cav1.2 on a functional and biochemical level as discussed in the manuscript.

As we now point out explicitly in the Introduction, the sites for direct phosphorylation of Cav1.2 by PKC (S27 and S31) that inhibit channel activity (McHugh et al., 2000) (former Ref 52) are located in a differentially spliced exon that is prominently expressed in heart but not neurons as further detailed by (Snutch et al., 1991) to explain why PKC does not inhibit Cav1.2 in neurons. We state: “T27/T31 are not present in the most prevalent brain isoform due to alternative splicing (Snutch et al., 1991), thus the inhibitory effect of PKC on LTCC currents is typically absent in neurons and neural crest-derived PC12 cells, or in vascular smooth muscle (Navedo et al., 2005; Taylor et al., 2000).”

2. The mechanism how Src activates Cav1.2 is not clear. The authors should make more effort to identify the site and use a mutant to show that it abolishes the increase in the channel activity. They discussed possible tyrosine phosphorylation at Y2122 but they did not confirm this. Also, this residue is located at the very end of protein, far away from the channel. It is not clear how it modulates the channel activity, if it has any function.

Please see response to Essential revisions point #1 and point #7 of Reviewer 2. Y2122 is only seen in rodents but not present in other mammals including humans. Y2122 is, thus, unlikely to be a general major regulatory site, which we now discuss more explicitly. Furthermore, as the Reviewer points out, it is very distal to the channel. Finally, perhaps we should emphasize that determining regulation of Cav1.2 by either cAMP/PKA or Gq/PKC signaling has been hampered for the last 3 decades in the many different labs that had been working on these issues by not being able to consistently and reproducibly being able to reconstitute either regulatory mechanism for Cav1.2 in HEK293 or other cell lines (mostly personal communications from multiple PIs but see some primary data and discussion of this issue in our review Dai, Hall, and Hell 2009: Physiol Rev 89, 411-452; p420, left column; see also Man, Bartels, Horne, and Hell, 2020: Sci Signal 13, eabc6438). Accordingly, we cannot readily express WT and mutant Cav1.2 (Iike Y2122F) in HEK293 cells and test whether regulation by PKC-Pyk2-Src is affected or not.

Reviewer #3 (Recommendations for the authors):

The authors should consider adding experiments that show whether the linker between domains II and III is indeed the site of regulation.

Please see response to Essential revisions point #1 and #8 by Reviewer 1. Briefly, we attempted but were not able to identify shorter loopII/III-derived peptides that would constitute the Pyk2 binding site.

Editorial Points

Lines 203-207. These sentences are a bit garbled. Please revise.

We revised this section mostly by simplifying the statement, which now reads: “Kinases and proteins that regulate kinase activity are often found in complexes with their ultimate target proteins (i.e., their ultimate substrates) including different ion channels for efficient and specific signaling (Dai et al., 2009; Dodge-Kafka et al., 2006).”

Lines 272-273. Better wording would be …"binds via phosphoY402 to the SH2 domain".

We revised this statement accordingly.

Line 503. Better wording would be "regulate through".

We revised this statement accordingly.

https://doi.org/10.7554/eLife.79648.sa2

Article and author information

Author details

  1. Kwun Nok Mimi Man

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0132-9129
  2. Peter Bartels

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Data curation, Formal analysis, Validation, Visualization, Methodology, Writing – review and editing
    Contributed equally with
    Peter B Henderson
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5852-1835
  3. Peter B Henderson

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Methodology
    Contributed equally with
    Peter Bartels
    Competing interests
    No competing interests declared
  4. Karam Kim

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Data curation, Formal analysis, Validation, Visualization, Methodology
    Competing interests
    No competing interests declared
  5. Mei Shi

    Department of Pharmacology, University of Iowa, Iowa City, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  6. Mingxu Zhang

    1. Department of Pharmacology, University of California, Davis, United States
    2. Department of Pharmacology, University of Iowa, Iowa City, United States
    Contribution
    Data curation, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  7. Sheng-Yang Ho

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Data curation, Methodology
    Competing interests
    No competing interests declared
  8. Madeline Nieves-Cintron

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Data curation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1935-8400
  9. Manuel F Navedo

    Department of Pharmacology, University of California, Davis, United States
    Contribution
    Data curation, Funding acquisition, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6864-6594
  10. Mary C Horne

    1. Department of Pharmacology, University of California, Davis, United States
    2. Department of Pharmacology, University of Iowa, Iowa City, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing – review and editing
    For correspondence
    mhorne@ucdavis.edu
    Competing interests
    No competing interests declared
  11. Johannes W Hell

    1. Department of Pharmacology, University of California, Davis, United States
    2. Department of Pharmacology, University of Iowa, Iowa City, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing – review and editing
    For correspondence
    jwhell@ucdavis.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7960-7531

Funding

National Institutes of Health (R01 MH097887)

  • Johannes W Hell

National Institutes of Health (RF1 AG055357)

  • Johannes W Hell

National Institutes of Health (R01 HL098200)

  • Manuel F Navedo

National Institutes of Health (R01 HL121059)

  • Manuel F Navedo

National Institutes of Health (T32 GM099608)

  • Peter B Henderson

National Institutes of Health (R01 NS123050)

  • Madeline Nieves-Cintron

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. Stephen Strittmatter (Yale University) for providing PF-719. Dr. K Man executed the electrophysiological recordings shown in Figures 13; Dr. P Bartels executed the electrophysiological recordings shown in Figures 46; Drs. Mei Shi and Mingxu Zhang performed the biochemical analysis in Figure 7; Dr. Peter Henderson performed the biochemical analysis in Figures 810; Dr. Karam Kim performed the LTP measurements in Figure 11. FUNDING This work was supported by National Institutes of Health grant R01 NS123050 (JWH), National Institutes of Health grant RF1 AG055357 (JWH), National Institutes of Health grant R01 MH097887 (JWH), National Institutes of Health grant R01 HL098200 (MFN), National Institutes of Health grant R01 HL121059 (MFN), and National Institutes of Health grant T32 GM099608 (PBH).

Ethics

All procedures followed NIH guidelines and had been approved by the Institutional Animal Care and Use Committees (IACUC) at UC Davis (Protocol #20673 and #22403).

Senior Editor

  1. Kenton J Swartz, National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States

Reviewing Editor

  1. Yukiko Goda, Okinawa Institute of Science and Technology, Japan

Version history

  1. Received: April 21, 2022
  2. Preprint posted: July 3, 2022 (view preprint)
  3. Accepted: June 19, 2023
  4. Accepted Manuscript published: June 20, 2023 (version 1)
  5. Version of Record published: July 6, 2023 (version 2)

Copyright

© 2023, Man et al.

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  1. Kwun Nok Mimi Man
  2. Peter Bartels
  3. Peter B Henderson
  4. Karam Kim
  5. Mei Shi
  6. Mingxu Zhang
  7. Sheng-Yang Ho
  8. Madeline Nieves-Cintron
  9. Manuel F Navedo
  10. Mary C Horne
  11. Johannes W Hell
(2023)
α1-Adrenergic receptor–PKC–Pyk2–Src signaling boosts L-type Ca2+ channel CaV1.2 activity and long-term potentiation in rodents
eLife 12:e79648.
https://doi.org/10.7554/eLife.79648

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https://doi.org/10.7554/eLife.79648

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    1. Neuroscience
    Maureen van der Grinten, Jaap de Ruyter van Steveninck ... Yağmur Güçlütürk
    Tools and Resources

    Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or ‘phosphenes’) has limited resolution, and a great portion of the field’s research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator’s suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.

    1. Neuroscience
    Simon Lui, Ashleigh K Brink, Laura H Corbit
    Research Article

    Extinction is a specific example of learning where a previously reinforced stimulus or response is no longer reinforced, and the previously learned behaviour is no longer necessary and must be modified. Current theories suggest extinction is not the erasure of the original learning but involves new learning that acts to suppress the original behaviour. Evidence for this can be found when the original behaviour recovers following the passage of time (spontaneous recovery) or reintroduction of the reinforcement (i.e. reinstatement). Recent studies have shown that pharmacological manipulation of noradrenaline (NA) or its receptors can influence appetitive extinction; however, the role and source of endogenous NA in these effects are unknown. Here, we examined the role of the locus coeruleus (LC) in appetitive extinction. Specifically, we tested whether optogenetic stimulation of LC neurons during extinction of a food-seeking behaviour would enhance extinction evidenced by reduced spontaneous recovery in future tests. LC stimulation during extinction trials did not change the rate of extinction but did serve to reduce subsequent spontaneous recovery, suggesting that stimulation of the LC can augment reward-related extinction. Optogenetic inhibition of the LC during extinction trials reduced responding during the trials where it was applied, but no long-lasting changes in the retention of extinction were observed. Since not all LC cells expressed halorhodopsin, it is possible that more complete LC inhibition or pathway-specific targeting would be more effective at suppressing extinction learning. These results provide further insight into the neural basis of appetitive extinction, and in particular the role of the LC. A deeper understanding of the physiological bases of extinction can aid development of more effective extinction-based therapies.