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Inhibition of striatonigral autophagy as a link between cannabinoid intoxication and impairment of motor coordination

  1. Cristina Blázquez
  2. Andrea Ruiz-Calvo
  3. Raquel Bajo-Grañeras
  4. Jérôme M Baufreton
  5. Eva Resel
  6. Marjorie Varilh
  7. Antonio C Pagano Zottola
  8. Yamuna Mariani
  9. Astrid Cannich
  10. José A Rodríguez-Navarro
  11. Giovanni Marsicano
  12. Ismael Galve-Roperh
  13. Luigi Bellocchio  Is a corresponding author
  14. Manuel Guzmán  Is a corresponding author
  1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Spain
  2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spain
  3. Centre National de la Recherche Scientifique (CNRS) and University of Bordeaux, Institut des Maladies Neurodégénératives, France
  4. Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, France
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Cite this article as: eLife 2020;9:e56811 doi: 10.7554/eLife.56811

Abstract

The use of cannabis is rapidly expanding worldwide. Thus, innovative studies aimed to identify, understand and potentially reduce cannabis-evoked harms are warranted. Here, we found that Δ9-tetrahydrocannabinol, the psychoactive ingredient of cannabis, disrupts autophagy selectively in the striatum, a brain area that controls motor behavior, both in vitro and in vivo. Boosting autophagy, either pharmacologically (with temsirolimus) or by dietary intervention (with trehalose), rescued the Δ9-tetrahydrocannabinol-induced impairment of motor coordination in mice. The combination of conditional knockout mouse models and viral vector-mediated autophagy-modulating strategies in vivo showed that cannabinoid CB1 receptors located on neurons belonging to the direct (striatonigral) pathway are required for the motor-impairing activity of Δ9-tetrahydrocannabinol by inhibiting local autophagy. Taken together, these findings identify inhibition of autophagy as an unprecedented mechanistic link between cannabinoids and motor performance, and suggest that activators of autophagy might be considered as potential therapeutic tools to treat specific cannabinoid-evoked behavioral alterations.

Introduction

Cannabis is one of the most common drugs of abuse in the world (Alpár et al., 2016; Englund et al., 2017; Volkow et al., 2014). Consequently, its major intoxicating constituent, the cannabinoid Δ9-tetrahydrocannabinol (THC), is the third most popular recreational addictive chemical following ethanol and nicotine. Of note, several states in the USA, as well as a few countries in the world, have legalized the recreational use of cannabis. Cannabis preparations have also been used in medicine for millennia, and nowadays there is a vigorous renaissance in the study and application of their therapeutic effects (Pertwee, 2012). In this context, THC and other cannabinoids are already approved by various regulatory agencies, including the Food and Drug Administration (FDA), the European Medicines Agency and Health Canada, as anti-emetic, anti-cachexic, analgesic and anti-spastic compounds (Hill, 2015; Whiting et al., 2015). Moreover, medical-grade cannabis dispensation programs have been implemented in about half of the states in the USA and in a growing number of countries globally. However, cannabis use is associated to several undesired and possibly dangerous side effects, so it is crucial that innovative procedures aimed to understand and potentially reduce cannabis-evoked harms are explored (Alpár et al., 2016; Englund et al., 2017; Volkow et al., 2014).

THC exerts its biological effects mainly by activating cannabinoid CB1 receptor, one of the most abundant metabotropic receptors in the mammalian central nervous system (Katona and Freund, 2008; Pertwee et al., 2010). This receptor is particularly expressed in discrete brain areas involved in the control of learning and memory (cortex, hippocampus), motor behavior (striatum, cerebellum), emotions (amygdala), and autonomic and endocrine functions (hypothalamus, pons, medulla), therefore participating in the control of a wide plethora of biological processes (Katona and Freund, 2008; Mechoulam and Parker, 2013). A family of retrograde lipid messengers, the endocannabinoids, biologically engages the CB1 receptor, mediating a feedback mechanism aimed to prevent excessive neuronal activity and, thereby, tuning the functionality and plasticity of many synapses (Castillo et al., 2012; Piomelli, 2003). Recent evidence suggests that the CB1 receptor can control autophagy, a highly conserved and pleiotropic process of cellular ‘self-digestion’ in which cytoplasmic materials are sequestered into double-membrane vesicles called autophagosomes, and subsequently delivered to lysosomes for degradation or recycling (Costa et al., 2016; Hiebel and Behl, 2015). Autophagy is an essential mechanism of cellular quality control, and the knowledge on its biological functions in the brain and other organs is rapidly increasing (Menzies et al., 2017; Ohsumi, 2014). Strikingly, in some cell-culture settings cannabinoids via the CB1 receptor enhance autophagy (Koay et al., 2014; Salazar et al., 2009), while in others they inhibit autophagy (Hiebel et al., 2014; Piyanova et al., 2013). Moreover, it is not known yet whether the CB1 receptor controls autophagy in the brain in vivo, and, eventually, what the functional consequences of this potential CB1 receptor/autophagy connection could be. Here, we show that THC inhibits autophagy selectively in the mouse striatum, and that this process participates in the THC-induced impairment of motor coordination. Moreover, administration of clinically safe autophagy activators to mice prevents the dyscoordinating effect of THC. These findings unveil an unprecedented link between cannabinoids, autophagy and motor performance, and provide preclinical evidence for the design of potential new therapeutic strategies aimed at treating specific cannabinoid-induced behavioral alterations.

Results

THC impairs striatal autophagy both in vivo and in vitro

To study the effect of THC on autophagy in the brain we first treated wild-type mice with a single i.p. injection of the drug at 10 mg/kg or its vehicle. After 4 hr, we evaluated the status of key autophagy protein markers. This dose and time window allows assessing persistent and pharmacologically tractable behavioral actions of THC administration, as previously reported (Metna‐Laurent et al., 2017; Puighermanal et al., 2013). We analyzed the expression pattern of microtubule-associated light chain three protein (LC3), the most widely used marker of autophagic vesicles (autophagosomes) (Mizushima et al., 2011; Ohsumi, 2014), in representative brain structures. Upon induction of autophagy, LC3 is converted from a soluble, non-lipidated form (LC3-I) to an aggregated, phosphatidylethanolamine-conjugated form (LC3-II), thereby becoming recruited to autophagosomal membranes (Mizushima et al., 2011). THC increased LC3-II levels in the striatum, either when referred to LC3-I (THC vs. vehicle, t = 4.680; df = 10; p=0.0009) or to β-actin (THC vs. vehicle, t = 4.331; df = 10; p=0.0015) as control, but not in other representative brain regions as the cortex, the hippocampus and the cerebellum (Figure 1A). An elevation of LC3-II levels, however, may indicate either that THC increases autophagosome generation (and so increases autophagic flux) or that THC decreases autophagosome clearance (and so decreases autophagic flux) (Mizushima et al., 2011; Ohsumi, 2014). To discern between these two possibilities, we measured the levels of p62 (sequestosome 1), a pivotal adaptor protein that carries cargo proteins to the autophagosome, being subsequently degraded upon fusion of the autophagosome to the lysosome (autophagolysosome or autolysosome) (Katsuragi et al., 2015; Mizushima et al., 2011). Hence, an increase of LC3-II together with a decrease of p62 usually denotes an active clearance of autophagosomes (and so an increased autophagic flux), while a simultaneous elevation of LC3-II and p62 usually defines an impaired clearance of autophagosomes (and so a decreased autophagic flux) (Katsuragi et al., 2015; Mizushima et al., 2011). THC induced an accumulation of p62 in the striatum (THC vs. vehicle, t = 5.303; df = 10; p=0.0003), but not in the other brain regions tested (Figure 1A), thus indicating that THC impairs the execution of autophagy and that this process occurs selectively in the striatum. Of note, the levels of LC3-I and p62 were not significantly different in the striatum than in the cortex, hippocampus or cerebellum from vehicle-treated mice (Figure 1B), suggesting that the selective impact of THC on striatal autophagy does not rely on the basal expression of those two key autophagy proteins but on additional, hitherto unknown molecular factors.

THC impairs autophagy in the mouse striatum.

Wild-type C57BL/6N mice were treated with THC (10 mg/kg as a single i.p. injection) or its vehicle. Four hours later, the striatum (St), cortex (Cx), hippocampus (Hc) and cerebellum (Cb) were dissected for Western blot analysis. (A) Effect of THC on autophagy markers in the different brain regions. (B) Relative levels of LC3-I and p62 in the different brain regions from vehicle-treated animals. In both panels, representative blots of each condition, together with optical density values relative to those of the respective loading controls, are shown (n = 6 animals per group). Blots were cropped for clarity. Electrophoretic migration of molecular weight markers is depicted on the right-hand side of each blot. **p<0.01 from vehicle-treated group by unpaired Student t-test. Raw numerical data and further statistical details are shown in Figure 1—source data 1.

To support a direct action of THC on the striatum, we prepared primary cultures of mouse striatal neurons and treated them with THC (0.75 µM). The synthetic THC analogue HU-210 (10 nM) was used as a further tool to proof pharmacological specificity. The two cannabinoid drugs increased LC3-II levels, as determined by immunofluorescence (aggregated-LC3 puncta), in both the total intracellular compartment (F(2,28) = 39.48; THC vs. vehicle, p=0.0004; HU-210 vs. vehicle, p<0.0001) and the lysosomal compartment, as identified by the lysosomal marker LAMP1 (F(2,28) = 22.43; THC vs. vehicle, p<0.0001, HU-210 vs. vehicle: p<0.0001) (Figure 2A). Concertedly, they also enhanced p62 levels (F(2,30) = 38.81; THC vs. vehicle, p=0.0130; HU-210 vs. vehicle, p=0.0335) (Figure 2B). We next evaluated the effect of the direct inhibition of lysosomal degradation. Upon this downstream blockade of autophagic flux, an autophagy-stimulating compound conceivably induces a further accumulation of autophagosomal markers (LC3-II and p62), while an autophagy-inhibiting compound is not expected to raise those markers further (Mizushima et al., 2011). We thus treated striatal neurons with two types of lysosomal inhibitors, specifically the lysosomotropic drug hydroxychloroquine or the lysosomal-protease inhibitors E64d and pepstatin A. As expected, these lysosome-blocking drugs induced per se an accumulation of LC3-II (total LC3-II: F(2,28) = 39.48; hidroxychloroquine vs. vehicle, p<0.0001; E64d/pepstatin A vs. vehicle, p=0.0024. LC3-II/LAMP1: F(2,28) = 22.43; hidroxychloroquine vs. vehicle: p<0.0001; E64d/pepstatin A vs. vehicle: p=0.0002) (Figure 2A) and p62 (F(2,30) = 38.81; hidroxychloroquine vs. vehicle, p=0.0001; E64d/pepstatin A vs. vehicle, p<0.0001) (Figure 2B). Of note, cannabinoids did not significantly heighten those pre-augmented levels of LC3-II (Figure 2A) and p62 (Figure 2B).

THC impairs autophagy in primary striatal neurons.

Primary striatal neurons from C57BL/6N mice were exposed for 24 hr to THC (0.75 µM) or HU-210 (10 nM), alone or in combination with hydroxychloroquine (0.1 mM), E64d (0.1 µM) and/or pepstatin A (10 ng/ml), or their vehicles. (A) LC3-II immunoreactivity (number of cells with three or more LC3-positive dots relative to total cells; upper panel) and LC3-II/LAMP1 immunoreactivity (number of LAMP1-positive cells with three or more LC3 dots relative to total cells; lower panel). Representative images with encircled examples of double-positive cells are shown (n = 3–6 independent cell preparations per condition). (B) p62 immunoreactivity (p62 fluorescence intensity relative to total cells). Representative images of selected experimental conditions with encircled examples of high-intensity cells are shown (n = 3–6 independent cell preparations per condition). *p<0.05, **p<0.01 from vehicle-treated group by two-way ANOVA with Tukey’s multiple comparisons test. Raw numerical data and further statistical details are shown in Figure 2—source data 1.

Taken together, these data support that cannabinoids inhibit autophagic flux in striatal neurons both in vivo and in vitro.

Temsirolimus prevents the THC-induced impairment of striatal autophagy and motor coordination in vivo

THC and other cannabinoids modulate various intracellular signalling pathways in the brain by engaging CB1 receptors (Castillo et al., 2012; Pertwee et al., 2010). One of the most relevant CB1 receptor-evoked actions is the activation of the phosphatidylinositol-3-kinase/Akt/mammalian target of rapamycin complex 1 (mTORC1) pathway (Blázquez et al., 2015; Gómez del Pulgar et al., 2000; Ozaita et al., 2007; Puighermanal et al., 2009). The serine/threonine kinase mTOR, the catalytic component of mTORC1, is critically involved in the control of neural plasticity through the regulation of protein synthesis and other basic cellular functions (Bockaert and Marin, 2015; Lipton and Sahin, 2014). Of note, mTORC1 is also the most relevant signaling platform that exerts a negative control on autophagy by phosphorylating UNC-51-like kinase 1 (ULK1), and so inhibiting autophagosome formation (Dunlop and Tee, 2014; Saxton and Sabatini, 2017). However, it is not known whether a cannabinoid-evoked activation of the mTORC1 pathway would be linked to an inhibition of autophagy, and, especially, what the biological consequences of this process could be.

To address this question, we made use of temsirolimus, an FDA-approved rapamycin analogue that selectively blocks mTOR within mTORC1, thereby disinhibiting autophagy (Dunlop and Tee, 2014). Mice were treated with temsirolimus (1 mg/kg, i.p.) or its vehicle, and, 20 min later, with THC (10 mg/kg, i.p.) or its vehicle. As THC inhibited autophagy selectively in the striatum, animals were subjected to tests of motor behavior, an archetypical process that - together with, for example, cognition, affection and reward - is controlled by the striatum and is impacted by cannabinoids in both laboratory animals and humans (Koketsu et al., 2008; Kreitzer, 2009; Lovinger, 2010). Four hours after injection, THC impaired motor coordination, as determined by the RotaRod test, and temsirolimus, under conditions that did not influence behavior by itself, rescued the effect of THC (F(3,30) = 6.635; THC vs. vehicle, p=0.0016; temsirolimus + THC vs. THC, p=0.0096) (Figure 3A). In contrast, the inhibitory action of THC on general locomotor activity, as determined by various parameters in the open field test (THC vs. vehicle, ambulation: F(3,24) = 24.14; p=0.0002; activity: F(3,24) = 10.67; p=0.0241; resting time: F(3,24) = 13.89; p=0.0067; fast movements: F(3,24) = 14.15; p=0.0002; stereotypic movements: F(3,24) = 8.240; p=0.0137), was not significantly affected by temsirolimus (Figure 3—figure supplement 1Puighermanal et al., 2013). This supports the idea that the THC-induced activation of the mTORC1 pathway selectively affects the coordination component of motor behavior. Under these experimental conditions, western blot analysis of mouse striata supported that THC concomitantly inhibited autophagy, as determined by the simultaneous accumulation of LC3-II (THC vs. vehicle, F(3,12) = 10.77; p=0.0119) and p62 (THC vs. vehicle, F(3,12) = 12.29; p=0.0017) (Figure 3B), and activated the mTORC1 pathway, as determined by an enhanced phosphorylation of the mTORC1-dependent sites in two of its main substrates, namely T389 in 70 kDa ribosomal protein S6 kinase (S6K) (THC vs. vehicle, F(3,12) = 28.70; p=0.0009), and S757 in ULK1 (THC vs. vehicle, F(3,12) = 8.506; p=0.0214) (Figure 3C). Of note, temsirolimus rescued these cannabinoid-evoked effects on p62 (temsirolimus + THC vs. THC, F(3,12) = 12.29; p=0.0008) (Figure 3B) and the mTORC1 pathway markers (pS6K-T389: temsirolimus + THC vs. THC, F(3,12) = 28.70; p<0.0001. pULK1-S757: temsirolimus + THC vs. THC, F(3,12) = 8.506; p=0.0470) (Figure 3C). Similar data were obtained by immunofluorescence analysis of p62 levels (F(3,12) = 16.80; THC vs. vehicle, p=0.0009; temsirolimus + THC vs. THC, p=0.0011) (Figure 3D), and of the phosphorylation state of the mTORC1/S6K downstream effector ribosomal protein S6 at two target residues (S235/S236) (F(3,12) = 8.34; THC vs. vehicle, p=0.0052; temsirolimus + THC vs. THC, p=0.0047) (Figure 3E), in striatal medium spiny neurons (MSNs), as identified by their standard marker dopamine- and cAMP-regulated phosphoprotein of 32 kDa (DARPP32). As a control, we found that the phosphorylation state of the main AMP-activated protein kinase (AMPK)-dependent site in ULK1, namely S555, was not significantly affected by THC and/or temsirolimus (Figure 3C). We were unable to immunodetect significant amounts of LC3 puncta in brain sections, which is usually ascribed to the rapid autophagic turnover and very high abundance of LC3-I over LC3-II occurring in living brain tissue (McMahon et al., 2012; Mizushima et al., 2004; Sarkar et al., 2014; Yang et al., 2011).

Figure 3 with 1 supplement see all
Temsirolimus prevents the THC-induced impairment of striatal autophagy and motor coordination in vivo.

Wild- type C57BL/6N mice were treated with temsirolimus (1 mg/kg as a single i.p. injection) or its vehicle for 20 min, and, subsequently, with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr. (A) Motor coordination (RotaRod test, time to fall relative to pre-treatment; n = 8–9 animals per group). (B, C) Western blot analysis of autophagy markers (panel B) and mTORC1 signaling pathway markers (panel C) in the striatum. Representative blots of each condition, together with optical density values relative to those of loading controls, are shown (n = 4 animals per group). Blots were cropped for clarity. Electrophoretic migration of molecular weight markers is depicted on the right-hand side of each blot. (D, E) Immunofluorescence analysis of p62 (p62 fluorescence intensity per DARPP32-positive cell; panel D) and phosphorylated ribosomal protein S6 (phospho-S6/DARPP32 double-positive cells relative to total cells; panel E) in the dorsal striatum (n = 4 animals per group). Representative images with encircled examples of a high-intensity cell (panel D) or double-positive cells (panel E) are shown. *p<0.05, **p<0.01 from vehicle-treated group, or #p<0.05, ##p<0.01 from THC-treated group, by one-way ANOVA with Tukey’s multiple comparisons test. Raw numerical data and further statistical details are shown in Figure 3—source data 1.

Taken together, these findings suggest that an inhibition of autophagy participates in the motor-dyscoordinating action of THC.

Trehalose prevents the THC-induced impairment of striatal autophagy and motor coordination in vivo

As a second approach to manipulate autophagy in vivo, we used the natural disaccharide trehalose, which directly stimulates autophagic flux (Emanuele, 2014; Sarkar et al., 2007). Mice were given trehalose (10 g/L in drinking water) or plain water for 24 hr, and, subsequently, were treated with THC (10 mg/kg, i.p.) or vehicle. Experimental measures were performed 4 hr after acute THC injection. Trehalose, under conditions that did not affect behavior by itself, rescued the THC-evoked impairment of motor coordination (F(3,45) = 3.858; THC vs. vehicle, p=0.0321; trehalose + THC vs. THC, p=0.0358) (Figure 4A). As shown above for temsirolimus, the inhibitory action of THC on general locomotor activity, as determined by various parameters in the open field test (THC vs. vehicle, ambulation: F(3,27) = 7.548; p=0.0402; activity: F(3,27) = 8.536; p=0.0134; resting time: F(3,27) = 7.420; p=0.0154; fast movements: F(3,27) = 8.496; p=0.0356; stereotypic movements: F(3,27) = 9.173; p=0.0032), was not significantly affected by trehalose (Figure 4—figure supplement 1). Western blot analysis of mouse striata indicated that trehalose reduced the THC-induced accumulation of striatal p62 (F(3,12) = 23.66; THC vs. vehicle, p=0.0017; trehalose + THC vs. THC, p<0.0001) (Figure 4B). Trehalose per se did not significantly affect mTORC1 activity markers, but mitigated the THC-evoked stimulation of the pathway (pS6K-T389: F(3,12) = 5.410; THC vs. vehicle, p=0.0388; trehalose + THC vs. THC, p=0.1944. pULK1-S757: F(3,12) = 12.03; THC vs. vehicle, p=0.0032; trehalose + THC vs. THC, p=0.0074) (Figure 4C). ULK1-S555 phosphorylation was not significantly affected by THC and/or trehalose (Figure 4C). These western blot data were corroborated by immunofluorescence analysis of p62 levels (F(3,12) = 7.575; THC vs. vehicle, p=0.0075; trehalose + THC vs. THC, p=0.0495) (Figure 4D) and protein S6 phosphorylation (F(3,12) = 8.822; THC vs. vehicle, p=0.0040; trehalose + THC vs. THC, p=0.0036) (Figure 4E).

Figure 4 with 1 supplement see all
Trehalose prevents the THC-induced impairment of striatal autophagy and motor coordination in vivo.

Wild-type C57BL/6N mice were given trehalose (10 g/L) or plain water ad libitum for 24 hr, and, subsequently, were treated with THC (10 mg/kg as a single i.p.injection) or its vehicle for 4 hr. (A) Motor coordination (RotaRod test, time to fall relative to pre-treatment; n = 11–14 animals per group). (B, C) Western blot analysis of autophagy markers (panel B) and mTORC1 signaling pathway markers (panel C) in the striatum. Representative blots of each condition, together with optical density values relative to those of loading controls, are shown (n = 4 animals per group). (D, E) Immunofluorescence analysis of p62 (p62 fluorescence intensity per DARPP32-positive cell; panel D) and phosphorylated ribosomal protein S6 (phospho-S6/DARPP32 double-positive cells relative to total cells; panel E) in the dorsal striatum (n = 4 animals per group). Representative images with encircled examples of a high-intensity cell (panel D) or double-positive cells (panel E) are shown. *p<0.05, **p<0.01 from vehicle-treated group, or #p<0.05, ##p<0.01 from THC-treated group, by one-way ANOVA with Tukey’s multiple comparisons test. Raw numerical data and further statistical details are shown in Figure 4—source data 1.

Taken together, these findings provide further support to the notion that an inhibition of striatal autophagy participates in the motor-dyscoordinating activity of THC.

Cannabinoid CB1 receptors located on the direct pathway, but not on cortical projections, are required for the THC-induced impairment of striatal autophagy and motor coordination in vivo

We subsequently studied the neuroanatomical substrate of the observed THC effects. As THC exerts most of its neurobiological effects by activating CB1 receptors, we first tested the effect of the CB1 receptor-selective antagonist SR141716 (rimonabant) on the THC-evoked inhibition of motor coordination. Mice were treated with rimonabant (3 mg/kg, i.p.) or vehicle for 20 min, and, subsequently, with THC (10 mg/kg, i.p.) or vehicle. Four hours after injection, THC impaired RotaRod performance, and rimonabant, under conditions that did not influence behavior by itself, abrogated the effect of THC (F(3,16) = 12.86; THC vs. vehicle, p=0.0020; rimonabant + THC vs. THC, p=0.0002) (Figure 5—figure supplement 1).

Striatal MSNs differ in their neurochemical composition and form two major efferent pathways: the direct (striatonigral) pathway, and the indirect (striatopallidal) pathway (Kreitzer, 2009). MSNs in the direct pathway (referred to here as D1R-MSNs) express dopamine D1 receptor (D1R), while MSNs in the indirect pathway (referred to here as D2R-MSNs) express dopamine D2 receptor (D2R). It has been reported that Cnr1fl/fl mice (referred to here as CB1R-floxed mice) that had been bred with Drd1aCre mice to inactivate CB1 receptors selectively in all cells that express D1R (these mice are referred to here as D1R-CB1R KO mice) exhibit a dampened response to the cataleptic effect (but not the overall hypolocomotor effect) of THC (Monory et al., 2007). This supports the notion that CB1 receptors located on D1R-MSNs control particular aspects of motor behavior. Hence, we evaluated the RotaRod test in D1R-CB1R KO mice and their control CB1R-floxed littermates. Remarkably, the motor-dyscoordinating action of THC (10 mg/kg, i.p.) found in CB1R-floxed mice was not evident in D1R-CB1R KO animals (F(3,18) = 6.571; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0067; D1R-CB1R KO-THC vs. CB1R-floxed-THC, p=0.0068) (Figure 5A). In concert, the simultaneous accumulation of LC3-II and p62 evoked by THC in control mice, as assessed by western blot, was not observed in D1R-CB1R KO mice (LC3-II: F(3,12) = 6.981; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0066; D1R-CB1R KO-THC vs. CB1R-floxed-THC, p=0.0122. p62: F(3,12) = 13.36; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0014; D1R-CB1R KO-THC vs. CB1R-floxed-THC, p=0.0005) (Figure 5B). The p62 data were confirmed by immunofluorescence analysis (F(3,9) = 14.36; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0038; D1R-CB1R KO-THC vs. CB1R-floxed-THC, p=0.0029) (Figure 5C).

Figure 5 with 1 supplement see all
Cannabinoid CB1 receptors located on D1R-MSNs, but not on glutamatergic neurons, are required for the THC-induced impairment of striatal autophagy and motor coordination in vivo.

(A–C) D1R-CB1R KO mice and CB1R-floxed control littermates were treated with THC (10 mg/kg as a single i.p.injection) or its vehicle for 4 hr. Panel A, Motor coordination (RotaRod test, time to fall relative to pre-treatment; n = 7 animals per group). Panel B, Western blot analysis of autophagy markers in the striatum. Representative blots of each condition, together with optical density values relative to those of loading controls, are shown (n = 5 animals per group). Blots were cropped for clarity. Electrophoretic migration of molecular weight markers is depicted on the right-hand side of each blot. Panel C, Immunofluorescence analysis of p62 (p62 fluorescence intensity per DARPP32-positive cell) in the dorsal striatum (n = 4 animals per group). Representative images with an encircled example of high-intensity cell are shown. (D–F) Glu-CB1R KO mice and CB1R-floxed control littermates were treated with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr. Panel D, Motor coordination (RotaRod test, time to fall relative to pre-treatment; n = 5 animals per group). Panel E, Western blot analysis of autophagy markers in the striatum. Representative blots of each condition, together with optical density values relative to those of loading controls, are shown (n = 5 animals per group). Blots were cropped for clarity. Electrophoretic migration of molecular weight markers is depicted on the right-hand side of each blot. Panel F, Immunofluorescence analysis of p62 (p62 fluorescence intensity per DARPP32-positive cell) in the dorsal striatum (n = 4 animals per group). Representative images with an encircled example of high-intensity cell are shown. *p<0.05, **p<0.01 from the corresponding vehicle-treated group, or #p<0.05, ##p<0.01 from the corresponding THC-treated CB1R-floxed group, by two-way ANOVA with Tukey’s multiple comparisons test. Raw numerical data and further statistical details are shown in Figure 5—source data 1.

By dampening glutamate outflow onto MSNs, CB1 receptors located on corticostriatal projections are considered a key determinant of striatal activity (Kreitzer, 2009; Lovinger, 2010), mediating, specifically, THC-induced hypolocomotion (Monory et al., 2007). We therefore evaluated the possible implication of this CB1 receptor pool in our model. For this purpose, we bred CB1R-floxed mice with Neurod6Cre mice to inactivate CB1 receptors selectively in all cells that express NeuroD6 (essentially dorsal telencephalic glutamatergic neurons; these mice are referred to here as Glu-CB1R KO mice) (Monory et al., 2006). Administration of THC (10 mg/kg, i.p.) decreased RotaRod performance comparably in Glu-CB1R KO mice and their control CB1R-floxed littermates (F(3,12) = 65.18; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p<0.0001; Glu-CB1R KO-THC vs. Glu-CB1R KO-vehicle, p<0.0001) (Figure 5D). Likewise, as assessed by western blot, THC enhanced LC3-II and p62 levels similarly in Glu-CB1R KO and CB1R-floxed mice (LC3-II: F(3,12) = 9.471; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0182; Glu-CB1R KO-THC vs. Glu-CB1R KO-vehicle, p=0.0107. p62: F(3,12) = 9.462; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0093; Glu-CB1R KO-THC vs. Glu-CB1R KO-vehicle, p=0.0168) (Figure 5E). The p62 data were confirmed by immunofluorescence analysis (F(3,12) = 11.31; CB1R-floxed-THC vs. CB1R-floxed-vehicle, p=0.0043; Glu-CB1R KO-THC vs. Glu-CB1R KO-vehicle, p=0.0108) (Figure 5F).

We finally aimed to strengthen the link between the effects of THC on autophagy and motor coordination in D1R-MSNs. We first treated transgenic mice expressing the tdTomato and EGFP reporter genes under the control of the promoter of the Drd1a gene (which encodes D1R) and the Drd2 gene (which encodes D2R), respectively, with THC (10 mg/kg, i.p.) or vehicle. Four hours later, immunofluorescence analysis revealed that the THC-induced activation of the mTORC1 pathway (as determined by protein S6 phosphorylation) occurred selectively in D1R-MSNs (F(3,15) = 7.387; D1R-MSN-THC vs. D1R-MSN-vehicle, p=0.0058; D2R-MSN-THC vs. D1R-MSN-THC, p=0.0146) (Figure 6—figure supplement 1). Then, we conducted viral vector-enforced protein expression experiments in vivo. We injected stereotactically into the dorsal striatum of D1R-Cre mice a CAG-DIO rAAV vector carrying a Cre-dependent dominant-negative form of Raptor, one of the essential components of mTORC1 (Hara et al., 2002; Koketsu et al., 2008), thus allowing the Cre-driven expression of dominant-negative Raptor in D1R-MSNs (c-myc-dnRaptor+ cells: D1R-Cre vs. WT, t = 33.71; df = 6; p<0.0001. pS6+ cells: F(3,9) = 52.52; THC-WT vs. vehicle-WT, p=0.0002; vehicle-D1R-Cre vs. vehicle-WT, p=0.0205; THC-D1R-Cre vs. THC-WT, p<0.0001) (Figure 6A). Dominant-negative Raptor did not affect RotaRod performance in vehicle-treated animals, but prevented the THC-induced impairment of motor coordination (F(7,28) = 5.309; THC-WT/post-treatment vs. vehicle-WT/post-treatment, p=0.0010; THC-D1R-Cre/post-treatment vs. THC-WT/post-treatment, p=0.0034) (Figure 6A). We next injected stereotactically into the dorsal striatum of D1R-Cre mice a CAG-DIO rAAV vector encoding p62, thus allowing the Cre-driven expression of p62 in D1R-MSNs (p62 intensity: D1R-Cre vs. WT, t = 12.22; df = 6; p<0.0001) (Figure 6B). Of note, p62 overexpression per se decreased RotaRod performance in vehicle-treated animals, and this decrease was not additive to that induced by THC administration (10 mg/kg, i.p.) (F(7,28) = 5.641; THC-WT/post-treatment vs. vehicle-WT/post-treatment, p=0.0152; vehicle-D1R-Cre/pre-treatment vs. vehicle-WT/pre-treatment, p=0.0477; THC-D1R-Cre/pre-treatment vs. THC-WT/pre-treatment, p=0.0450) (Figure 6B).

Figure 6 with 1 supplement see all
mTORC1 and p62 in D1R-MSNs participate in the THC-induced impairment of motor coordination in vivo.

(A) D1R-Cre mice and wild-type control littermates were injected stereotactically into the dorsal striatum with a CAG-DIO-dnRaptor rAAV, and left untreated for 4 weeks. Animals were subsequently treated with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr, and motor coordination was evaluated (RotaRod test, time to fall in seconds; n = 5 animals per group). **p<0.01 from vehicle-treated WT/post-treatment group, or ##p<0.01 from THC-treated WT/post-treatment group, by two-way ANOVA with Tukey’s multiple comparisons test. Representative images of c-myc tag and phosphorylated ribosomal protein S6 staining in the dorsal striatum, together with their quantification (c-myc-positive cells relative to total cells, or phospho-S6-positive cells relative to total cells), are shown (n = 4 animals per group). **p<0.01 from WT group by unpaired Student t-test (c-myc immunofluorescence); *p<0.05, **p<0.01 from vehicle-treated/WT group, or ##p<0.01 from THC-treated/WT group, by two-way ANOVA with Tukey’s multiple comparisons test (phospho-S6 immunofluorescence). (B) D1R-Cre mice and wild-type control littermates were injected stereotactically into the dorsal striatum with a CAG-DIO-p62 rAAV, and left untreated for 4 weeks. Animals were subsequently treated with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr, and motor coordination was evaluated (RotaRod test, time to fall in seconds; n = 5 animals per group). *p<0.05 from vehicle-treated WT/post-treatment group, or #p<0.05 from the respective WT/pre-treatment group, by two-way ANOVA with Tukey’s multiple comparisons test. Representative images of p62 staining in the dorsal striatum, together with their quantification (p62 fluorescence intensity relative to total cells), are shown (n = 4 animals per group). **p<0.01 from WT group by unpaired Student t-test. Raw numerical data and further statistical details are shown in Figure 6—source data 1.

Taken together, all these findings indicate that CB1 receptors located on D1R-MSNs, but not on corticostriatal projections, are required for the autophagy-inhibiting and motor-dyscoordinating activity of THC.

Discussion

Here, we identify impairment of autophagy as an unprecedented mechanism involved in cannabinoid-induced motor alterations. On molecular grounds, our data favour a ‘two-hit’ model by which engagement of striatal CB1 receptors may impair autophagy. First, CB1 receptor activation, by coupling to the phosphatidylinositol-3-kinase/Akt/mTORC1 pathway, would lead to ULK1 phosphorylation, which, subsequently, would inhibit autophagosome formation/autophagy initiation. Second, CB1 receptor activation, by a hitherto undefined mechanism that may conceivably involve an impact on lysosomal function (Hiebel and Behl, 2015), would inhibit autophagosome clearance/autophagy completion. We are aware, however, that our work has several shortcomings that could limit the generalization of its conclusions. Specifically, (i) the data (except for the cell-culture experiments) come from a single cannabinoid agonist (THC) given at a single dose (10 mg/kg, i.p.), and were collected at a single time point after administration (4 hr); (ii) only two (albeit well-established) motor behavior measures were examined (RotaRod and open field); and (iii) only male animals were studied.

By targeting mTORC1 with temsirolimus, we report a feasible pharmacological intervention to rescue the concerted THC-evoked impairment of autophagy and motor coordination. Temsirolimus prevents other unwanted effects of THC, such as short-term memory loss and anxiety, leaving potential therapeutically sought cannabinoid actions as analgesia and anxiolysis unaffected (Puighermanal et al., 2013). Temsirolimus has similar potency and specificity for mTOR than rapamycin, but longer stability and increased solubility, and is already approved by the FDA as first-line treatment for metastatic renal cancer patients classified as poor risk (Hudes et al., 2007). In these patients, temsirolimus is well-tolerated, increases overall survival, and improves quality of life (Zanardi et al., 2015). Taken together, these pieces of evidence suggest that administration of temsirolimus, or other FDA-approved rapalogs like everolimus (Janku et al., 2018; Lebwohl et al., 2013), might help to counteract some particular unwanted effects of cannabis.

Dietary manipulation with trehalose also prevented the THC-evoked impairment of autophagy and motor dyscoordination. Trehalose, a nontoxic disaccharide found in numerous plants, microorganisms and invertebrates, contains an α,α−1,1-glucoside bond between two α-glucose units, thus being an extremely stable sugar. In many countries, including USA, trehalose is added to various food products as nutritional supplement and ‘natural flavor’ (Richards et al., 2002). On physiological grounds, trehalose is believed to stabilize proteins and to protect them from stress-induced unfolding, aggregation and degradation (Emanuele, 2014; Hosseinpour-Moghaddam et al., 2018). Vertebrates cannot synthesize trehalose, but exogenous trehalose administration induces the clearance of toxic protein aggregates in cultured mammalian cells, and exerts therapeutic effects in a plethora of mouse models of protein-misfolding disorders (including Huntington’s disease, Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis) concomitantly to autophagy induction (Hosseinpour-Moghaddam et al., 2018; Menzies et al., 2017). Although its mechanism of action is not completely understood (Lee et al., 2018), trehalose has been proposed to activate autophagy via competitive inhibition of GLUT glucose transporters, thus impairing cellular energy supply and stimulating AMPK (DeBosch et al., 2016). In our hands, however, the phosphorylation state of the main AMPK-dependent site in ULK1 remained unaffected upon trehalose treatment. We also observed that, in line with some reports (e.g. Sarkar et al., 2007), trehalose did not affect the basal activity of mTORC1-pathway molecular markers; and, in line with other reports (e.g. DeBosch et al., 2016), it attenuated stimulus-evoked mTORC1 overactivation. Thus, it is likely that AMPK, mTORC1, and the contextual crosstalk between these two pivotal signalling axes (Alers et al., 2012) are required for the full pro-autophagic effects of trehalose to be observed.

We also define here the neuroanatomical basis for the autophagy-inhibiting and motor-dyscoordinating actions of THC. The CB1 receptor is one of the most abundant metabotropic receptors in the striatum, where it is mainly expressed in D1R-MSNs, D2R-MSNs, GABAergic interneurons, and astrocytes, as well as in glutamatergic terminals projecting from the cortex (Castillo et al., 2012; Davis et al., 2018; Uchigashima et al., 2007). This complex anatomical profile dictates an intricate repertoire of modulatory actions controlled by endocannabinoids through different CB1 receptor pools, ranging from synaptic plasticity (Covey et al., 2017; Kreitzer, 2009) to astrocyte-neuron communication (Araque et al., 2017) and neuronal integrity (Chiarlone et al., 2014; Naydenov et al., 2014). Specifically, our data show that the pool of CB1 receptors located on D1R-MSNs plays an indispensable role in cannabinoid-induced impairment of autophagy and motor coordination. Of note, it has been shown that this precise CB1 receptor subpopulation is also necessary for cannabinoid-induced catalepsy, although not for overall cannabinoid-induced hypomotility (Monory et al., 2007), thus supporting that, in agreement with our data, it controls selected aspects of motor behavior. In addition, CB1 receptors located on corticostriatal terminals, by controlling glutamatergic signalling, contribute to THC-induced hypolocomotion (Monory et al., 2007), participate in endocannabinoid-dependent long-term depression as evoked by D1R-MSNs (Bagetta et al., 2011; Wu et al., 2015) and protect D1R-MSNs from toxic insults (Ruiz-Calvo et al., 2018). Thus, endocannabinoid signalling fine-tunes the functions and viability of D1R-MSNs through a delicate armamentarium of CB1 receptor pools located on both D1R-MSNs, presynaptic terminals impinging on them, and other surrounding cell types.

We note that our work does not unveil the precise cellular and molecular mechanisms by which the CB1 receptor-evoked inhibition of autophagy in D1R-MSNs affects brain functionality to change motor coordination. Neuronal communication is finely sensitive to proteostatic processes as autophagy, which, for example, clears dysfunctional proteins and fine-tunes the trafficking/recycling of membrane neurotransmitter receptors (e.g. ionotropic glutamate receptors; Birdsall and Waites, 2019). Neuronal activity is associated to the mTORC1 pathway and autophagy, and this could in turn participate in NMDA receptor-dependent synaptic plasticity and brain function (Shehata et al., 2012). Hence, the control of long-term depression exerted by CB1 receptors on D1R-MSNs (Bagetta et al., 2011; Wu et al., 2015) might be mechanistically connected to the THC-evoked effects on mTORC1/autophagy reported here, perhaps by signaling in a cell-autonomous manner through the accumulation of the multifunctional scaffold protein p62 (Sánchez-Martín and Komatsu, 2018). These possibilities notwithstanding, our findings might also be relevant in other neurobiological processes that are known to be controlled by the striatum and impacted by cannabinoids - for example cognition, affection and reward (Katona and Freund, 2008; Kreitzer, 2009; Lovinger, 2010). Moreover, from a translational point of view, it is tempting to speculate that D1R-MSNs, but not corticostriatal terminals, would constitute the neuroanatomical target of strategies aimed at managing some specific cannabis-induced behavioral alterations as catalepsy and dyscoordination.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Mus musculus, C57BL/6N, male)Cnr1fl/fl;Drd1aCreMonory et al., 2007; doi:10.1371/journal.pbio.0050269N/AConditional mutant mice in which the CB1 receptor gene (Cnr1) is absent from D1R (Drd1a)-expressing cells
Strain, strain background (Mus musculus, C57BL/6N, male)Drd1aCreLemberger et al., 2007; doi:10.1186/1471-2202-8-4N/ATransgenic mice expressing Cre recombinase in D1R (Drd1a)-expressing cells
Strain, strain background (Mus musculus, C57BL/6N, male)Cnr1fl/fl;Neurod6CreMonory et al., 2006; doi:10.1016/j.neuron.2006.07.006N/AConditional mutant mice in which the CB1 receptor gene (Cnr1) is absent from dorsal telencephalic glutamatergic (Neurod6-expressing) neurons
Strain, strain background (Mus musculus, C57BL/6N, male)Drd1a-tdTomato;Drd2-EGFPSuárez et al., 2014; doi:10.1016/j.biopsych.2013.05.006N/ATransgenic mice expressing the tdTomato and EGFP reporter genes under the control of the Drd1a gene promoter and the Drd2 gene promoter, respectively
Strain, strain background (Mus musculus, C57BL/6N, male)C57BL/6NHarlan LaboratoriesRRID:MGI:5902763Wild-type mice
Transfected construct (Homo sapiens)Myc-Raptor (ΔCT) expression vectorAddgene
Hara et al., 2002; doi:10.1016/s0092-8674(02)00833–4.
Koketsu et al., 2008; doi:10.1152/ajpendo.00253.2007
Plasmid #1859;
RRID:Addgene_1859
Vector backbone: pRK-5; construct generated by PCR-mediated deletion of1293 base pairs at the Raptor C-terminus
Transfected construct (Homo sapiens)HA-p62
expression vector
AddgenePlasmid #28027;
RRID:Addgene_28027
Vector backbone: pcDNA4/TO
Genetic reagent (Homo sapiens)CAG-DIO rAAV expression vectorKlugmann et al., 2005; doi:10.1016/j.mcn.2004.10.002
Bellocchio et al., 2016; doi:10.1523/JNEUROSCI.1192–16.2016
CAG-DIO rAAV
Hybrid serotype 1/2
Recombinant adeno-associated virus (rAAV) for Cre-driven transgene expression with a CAG promoter
Biological sample (Mus musculus)Primary striatal neuronsHarlan Laboratories (C57BL/6N mice)C57BL/6N
RRID:MGI:5902763
In vitro cell cultures
AntibodyAnti-LC3B
(rabbit polyclonal)
Sigma-AldrichCat. #L7543;
RRID:AB_796155
IF (1:300);
WB (1:4000)
AntibodyAnti-p62
(rabbit polyclonal)
Enzo Life SciencesCat. #BML-PW9860-0025;
RRID:AB_2052149
IF (1:250);
WB (1:1000)
AntibodyAnti-p62
(rabbit polyclonal)
ProgenCat. #GP62-C;
RRID:AB_2687531
WB (1:1000)
AntibodyAnti-LAMP1
(rabbit polyclonal)
AbcamCat. #ab25245
RRID:AB_449893
IF (1:1000)
AntibodyAnti-DARPP32
(mouse monoclonal)
BD BiosciencesCat. #611520;
RRID:AB_398980
IF (1:700)
AntibodyAnti-phospho-S6-S235/S236
(rabbit polyclonal)
Cell SignalingCat. #2211;
RRID:AB_331679
IF (1:300)
AntibodyAnti-phospho-S6-S240/S244
(rabbit polyclonal)
Cell SignalingCat. #5364;
RRID:AB_10694233
IF (1:800)
 AntibodyAnti-c-Myc
(mouse monoclonal)
Sigma-AldrichCat. #11-667-149-001;
RRID:AB_390912
IF (1:500)
AntibodyAnti-phospho-S6K-T389
(mouse monoclonal)
Cell SignalingCat. #9206;
RRID:AB_2285392
WB (1:1000)
AntibodyAnti-total-S6K
(rabbit polyclonal)
Cell SignalingCat. #9202;
RRID:AB_331676
WB (1:1000)
AntibodyAnti-phospho-ULK1-S757
(rabbit polyclonal)
Cell SignalingCat. #6888;
RRID:AB_10829226
WB (1:1000)
AntibodyAnti-phospho-ULK1-S555
(rabbit polyclonal)
Cell SignalingCat. #5869;
RRID:AB_10707365
WB (1:1000)
AntibodyAnti-total-ULK1
(rabbit polyclonal)
Cell SignalingCat. #8054;
RRID:AB_11178668
WB (1:1000)
AntibodyAnti-β-actin
(mouse monoclonal)
Sigma-AldrichCat. #A5441;
RRID:AB_476744
WB (1:4000)
AntibodyAnti-mouse monoclonal IgG
(HRP-linked whole antibody)
GE-Healthcare LifescienceCat. #NA931;
RRID:AB_772210
WB (1:5000)
AntibodyAnti-rabbit monoclonal IgG
(HRP-linked whole antibody)
GE-Healthcare LifescienceCat. #NA934;
RRID:AB_2722659
WB (1:5000)
AntibodyGoat anti-guinea pig IgG (H+L)
(HRP-linked secondary antibody)
InvitrogenCat. #A18769;
RRID:AB_2535546
WB (1:5000)
AntibodyGoat anti-mouse IgG (H+L)
(cross-adsorbed, Alexa Fluor 488)
InvitrogenCat. #A-11001;
RRID:AB_2534069
IF (1:500)
AntibodyGoat anti-mouse IgG (H+L)
(cross-adsorbed, Alexa Fluor 594)
InvitrogenCat. #A-11005;
RRID:AB_2534073
IF (1:500)
AntibodyGoat anti-mouse IgG (H+L)
(cross-adsorbed, Alexa Fluor 647)
InvitrogenCat. #A-21235;
RRID:AB_2535804
IF (1:500)
AntibodyGoat anti-rabbit IgG (H+L)
(cross adsorbed, Alexa Fluor 488)
InvitrogenCat. #A-11008;
RRID:AB_143165
IF (1:500)
AntibodyGoat anti-rabbit IgG (H+L)
(cross adsorbed, Alexa Fluor 594)
InvitrogenCat. #A-11012;
RRID:AB_2534079
IF (1:500)
AntibodyGoat anti-rabbit IgG (H+L)
(cross adsorbed, Alexa Fluor 647)
InvitrogenCat. #A-21244;
RRID:AB_2535812
IF (1:500)
Commercial assay or kitPapain dissociation system (PDS)WorthingtonCat. #LK 003153In vitro cell cultures
Chemical compound, drugΔ9-tetrahydro-cannabinol (THC)THC Pharm GmbHDronabinolIn vivo experiments (10 mg/kg, i.p.);in vitro experiments (0.75 μM)
Chemical compound, drugRimonabant (SR141716)Cayman ChemicalCat. #9000484In vivo experiments: (3 mg/kg, i.p.)
Chemical compound, drugTemsirolimusLC LabsCat. #T-8040In vivo experiments (1 mg/kg, i.p.)
Chemical compound, drugTrehaloseMerck-CalbiochemCat. #90210In vivo experiments (10 g/L in drinking water)
Chemical compound, drugHU-210TocrisCat. #0966In vitro experiments (10 nM)
Chemical compound, drugHydroxychloroquineMerckCat. #509272In vitro experiments (0.1 mM)
Chemical compound, drugE64dEnzo Life SciencesCat. #BML-PI107-0001In vitro experiments (0.1 μM)
Chemical compound, drugPepstatin AEnzo Life SciencesCat. #ALX-260–085 M005In vitro experiments (10 ng/ml)
Software, algorithmGraph Pad
Prism 8.0
GraphPad Software IncRRID:SCR_002798Descriptive analysis and statistics
Software, algorithmIBM SPSSIBM CorporationRRID:SCR_002865Statistical power analysis
Software, algorithmImage JNIHRRID:SCR_003070Western blot and immune-microscopy image analysis
Software, algorithmTCS-SP8
Leica Application Suite X, LASX
LeicaRRID:SCR_013673SP8 AOBS confocal microscopy image capture
Software, algorithmACTITRACKUPG V2.7PanlabCat. #76–0610Motor activity analysis
OtherDAPI stainInvitrogenCat. #D1306;
RRID:AB_2629482
IF (1 µg/mL)
OtherRotaRod LE8200Harvard ApparatusCat. #LE8200 (76–0237)Motor coordination testing
OtherIR actimeter
(ActiTrack)
PanlabCat. #76–0127, #76–0131, #76–0134, #76–0125Motor activity testing

Animals

We used conditional mutant mice, generated by the Cre-loxP technology, in which the CB1 receptor gene (Cnr1) is absent either from D1R-expressing neurons (Cnr1fl/fl mice bred with Drd1aCre mice; referred to here as D1R-CB1R KO mice) (Monory et al., 2007) or from dorsal telencephalic glutamatergic neurons (Cnr1fl/fl mice bred with Neurod6Cre mice; referred to here as Glu-CB1R KO mice) (Monory et al., 2006), as well as their respective Cnr1fl/fl (referred to here as CB1R-floxed) littermates. We also used BAC transgenic mice expressing the tdTomato and EGFP reporter genes under the control of the Drd1a gene promoter and Drd2 gene promoter, respectively (Drd1a-tdTomato;Drd2-EGFP mice; colony founders kindly provided by Rosario Moratalla, Cajal Institute, Madrid, Spain) (Suárez et al., 2014). Wild-type C57BL/6N mice were purchased from Harlan Laboratories (Barcelona, Spain). Animal housing, handling and assignment to the different experimental groups were conducted essentially as described before (Bagetta et al., 2011). Throughout the study, animals had unrestricted access to food and water. They were housed (4–5 mice per cage) under controlled temperature (range, 20–22°C), humidity (range, 50–55%) and light/dark cycle (light between 8:00 am and 8:00 pm). Animals were habituated to housing conditions before the start of the experiments, were assigned randomly to the different treatment groups, and all experiments were performed in a blinded manner for genotype, pharmacological treatment and viral injection. All animals used in the experiments were male adults (ca. 8-week-old). Adequate measures were taken to minimize pain and discomfort of the animals, as well as the number of animals used in the experiments, on the basis of the 3Rs (replacement, reduction and refinement) principle. Mice were sacrificed either by intracardial perfusion with paraformaldehyde (and their brains subsequently excised for histological analyses) or by cervical dislocation (and their striata, or other brain regions, subsequently dissected for Western blot analyses). All the experimental procedures were performed in accordance with the guidelines and with the approval of the Animal Welfare Committee of Universidad Complutense de Madrid and Comunidad de Madrid (PROEX 209/18), and in accordance with the directives of the European Commission (2010/63/EU).

Drug treatments in vivo

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THC (THC Pharm GmbH, Frankfurt am Main, Germany) and SR141716 (rimonabant; Cayman Chemical, Ann Arbor, MI, USA) were stored in DMSO. Just before the experiments, solutions of vehicle [1% (v/v) DMSO in Tween-80/saline (1:80, v/v)], THC (10 mg/kg body weight) and/or rimonabant (3 mg/kg body weight) were prepared for i.p. injections. When rimonabant was used (Figure 5—figure supplement 1), mice were treated with rimonabant (3 mg/kg as a single i.p. injection) or vehicle for 20 min, and, subsequently, with THC (10 mg/kg as a single i.p. injection) or vehicle for 4 hr. Temsirolimus (LC Labs, Woburn, MA, USA) was prepared fresh in DMSO just before the experiments. Mice were treated with temsirolimus (1 mg/kg as a single i.p. injection) or its vehicle for 20 min, and, subsequently, with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr. Trehalose (Merck-Calbiochem, Barcelona, Spain) was directly added to the drinking water of the animals. Mice were given trehalose (10 g/L) or plain water ad libitum for 24 hr, and, subsequently, were treated with THC (10 mg/kg as a single i.p. injection) or its vehicle for 4 hr. Under these conditions, the addition of trehalose did not affect the volume of water that was drunk by the animals. The doses of temsirolimus and trehalose used were selected from both previous studies (Puighermanal et al., 2013; Rodríguez-Navarro et al., 2010) and pilot experiments on motor behavior.

Viral vectors

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The coding sequence of dominant-negative Raptor with a c-Myc tag (Myc-RaptorΔCT) was generated by PCR-mediated deletion of 1293 base pairs at the C-terminus (Hara et al., 2002) of wild-type Myc-tagged Raptor (Addgene, Watertown, MA; plasmid #1859) (Koketsu et al., 2008). Myc-RaptorΔCT or human HA-tagged p62 (Addgene; plasmid #28027) was subcloned in a CAG-DIO rAAV vector, to allow the Cre-dependent expression of the transgene, by using standard molecular biology techniques. The vectors used were of an AAV1/AAV2-mixed serotype and were generated by calcium phosphate transfection of HEK-293T cells (American Type Culture Collection, Manassas, VA) and subsequent purification, as described previously (Bellocchio et al., 2016). Wild-type and D1R-Cre mice were injected stereotactically with the rAAV vector into the dorsal striatum. Each animal received one bilateral injection at the following coordinates (to bregma): antero-posterior +0.5, lateral ±2.0, dorso-ventral −3.0 (Bellocchio et al., 2016). Mice were left untreated for 4 weeks to attain transgene expression before being subjected to the behavioral tests.

Neuronal cultures

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Primary striatal neurons were obtained from 0 to 1-day-old C57BL/6N mice using a papain dissociation system (Worthington, Lakewood, NJ) (Blázquez et al., 2015). Striata were dissected, and cells were seeded at 200,000 cells/cm2 on plates that had been pre-coated with 0.1 mg/mL poly-D-lysine, in Neurobasal medium supplemented with B27 and Glutamax. Cultures were maintained for 7 days in vitro to allow neuronal differentiation. They were subsequently incubated for 24 hr with THC (0.75 µM; THC Pharm GmbH) or HU-210 (10 nM; Tocris; Bristol, UK), alone or in combination with hydroxychloroquine (0.1 mM; Merck, Barcelona, Spain) or E64d (0.1 µM; Enzo Life Sciences, Barcelona, Spain) plus pepstatin A (10 ng/ml; Enzo Life Sciences), or vehicle [DMSO, 0.1–0.2% (v/v) final concentration], before they were fixed for immunomicroscopy. Within each neuronal preparation, incubations were conducted in triplicate for every vehicle or drug condition. The total number of experimental conditions assayed within each neuronal preparation depended on the cell yield of that particular preparation.

Immunomicroscopy

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Cells were cultured on coverslips and fixed in 4% paraformaldehyde. Coronal free-floating sections (30 μm-thick) were obtained from paraformaldehyde-perfused mouse brains. Samples were first incubated with 10% goat serum in PBS supplemented with 0.25% Triton X-100 for 1 hr at room temperature to block non-specific binding, and subsequently stained overnight at 4°C with antibodies against LC3 (1:300; Sigma-Aldrich, St. Louis, MO, #L7543), p62 (1:250; Enzo Life Sciences, #BML-PW9860-0025), LAMP1 (1:1000; Abcam, Cambridge, UK, #ab25245), DARPP32 (1:700; BD Biosciences, Franklin Lakes, NJ, #611520), phosphorylated ribosomal protein S6-S235/S236 [1:300; Cell Signaling, Danvers, MA, #2211; similar data were obtained in pilot experiments when an antibody directed against two other mTORC1/S6K-phosphorylated residues of ribosomal protein S6 (S240/S244) was used (1:800; Cell Signaling, #5364)] or c-Myc (1:500; Sigma-Aldrich, #11-667-149-001), followed by the corresponding Alexa Fluor-conjugated secondary antibodies (1:500; 1.5 hr, room temperature, darkness; Invitrogen, Madrid, Spain, #A-11001, #A-11005, #A-21235; #A-11008, #A-11012, #A-21244). Three washes (20 min each) with 1% goat serum in PBS supplemented with 0.25%Triton X-100 were conducted both between antibody incubations and before sample mounting. Nuclei were visualized with DAPI. Analysis of marker-protein immunoreactivity in the dorsal striatum was conducted in a 1-in-10 series per animal (from bregma +1.5 to −0.5 coronal coordinates). A total of 6–8 sections (comprising 2–3 fields per section) was analyzed per mouse brain. For LC3, data were calculated as number of cells with three or more LC3-positive dots. For p62, data were calculated as immunofluorescence intensity. For DARPP32, LAMP1, c-Myc and phosphorylated ribosomal protein S6, data were calculated as number of positive cells. For tdTomato and EGFP fluorescence in Drd1a-tdTomato/Drd2-EGFP mice, data were calculated as number of positive cells. Confocal fluorescence images were acquired using TCS-SP8 (Leica Application suite X, LASX) software and a SP8 AOBS microscope (Leica, Wetzlar, Germany). Inclusive fluorescence thresholds were set at an average of 105 (low) and 255 (high). Images were analyzed with ImageJ software (NIH, Bethesda, MA). All immunomicroscopy analyses relied on an unbiased quantification of ImageJ-positive pixels, and were conducted in a blinded manner for genotype, pharmacological treatment and viral injection.

Western blot

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Western blot experiments were conducted with antibodies raised against LC3 (1:4000; Sigma-Aldrich, #L7543), p62 [1:1000; Enzo Life Sciences, #BML-PW9860-0025; similar data were obtained in pilot experiments when a different anti-p62 antibody was used (1:1000; Progen, Heidelberg, Germany, #GP62-C)], phosphorylated S6K-T389 (1:1000; Cell Signaling, #9206), total S6K (1:1000; Cell Signaling, #9202), phosphorylated ULK1-S757 (1:1000; Cell Signaling, #6888), phosphorylated ULK1-S555 (1:1000; Cell Signaling, #5869), total ULK1 (1:1000; Cell Signaling, #8054) or β-actin (1:4000, Sigma-Aldrich, #A5441), followed by the corresponding HRP-linked secondary antibodies (1:5000; GE-Healthcare, Madrid, Spain, #NA931; GE-Healthcare, #NA934; Invitrogen, #A18769), as appropriate. Densitometric analysis was performed with Image J software (NIH).

Motor behavior

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Motor coordination analysis (RotaRod test) was conducted with acceleration from 4 to 40 r.p.m. over a period of 600 s in an LE8200 device (Harvard Apparatus, Barcelona, Spain) (Blázquez et al., 2011). Any mouse remaining on the apparatus after 600 s was removed, and its time was scored as 600 s. RotaRod performance was evaluated in two phases. First, before any pharmacological treatment, naive mice were tested on three consecutive days, for three trials per day, with a rest period of 40 min between trials. Data from the three trials conducted on the first day were not used in statistical analyses, as they merely reflect the initial contact of the animal with the RotaRod device (Hockly et al., 2003). Data from the three trials conducted on the second day plus the three trials conducted on the third day were averaged for each animal, so constituting the herein referred to as ‘pre-treatment’ RotaRod performance. Second, on the day of the pharmacological experiment, 4 hr after vehicle or drug treatment, mice were tested for three trials, with a rest period of 40 min between trials. Data from these three trials were averaged for each animal, so constituting the herein referred to as ‘post-treatment’ RotaRod performance. Hence, for each animal, its ‘post-treatment’ RotaRod performance was compared with its ‘pre-treatment’ RotaRod performance. Motor activity analysis was conducted in an automated actimeter consisting of a 22.5 × 22.5 cm area with 16 surrounding infrared beams coupled to a computerized control unit (ActiTrack; Panlab, Barcelona, Spain) (Blázquez et al., 2011). Four hours after vehicle or drug treatment, animals were recorded once for a period of 10 min, in which total distance travelled (cm), overall activity (counts), resting time (s), fast movements (counts) and stereotypic movements (counts) were measured.

Statistics

Unless otherwise specified, data are presented as mean ± SEM of the number of animals or independent neuronal preparations indicated in each case. Statistical comparisons were made by unpaired Student t-test, or by ANOVA followed by Tukey’s multiple comparisons test, as indicated in each figure legend. For clarity, only p values lower than 0.05 were considered statistically significant. The source data files include all raw numerical data as well as further details of the statistical analyses, which were carried out with GraphPad Prism 8.0 software (San Diego, CA). Power analysis was conducted with IBM SPSS software (IBM France, Bois-Colombes, France).

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Decision letter

  1. Joseph F Cheer
    Reviewing Editor; University of Maryland School of Medicine, United States
  2. Kate M Wassum
    Senior Editor; University of California, Los Angeles, United States
  3. Cece Hillard
    Reviewer
  4. Nephi Stella
    Reviewer; Univ. Washington, United States

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

Acceptance summary:

This study demonstrates the involvement of autophagy, a regulated cell mechanism that removes unnecessary components, in the impairment in motor coordination observed following administration of THC (one of the main psychoactive components of marijuana). The findings also reveal which cells within motor pathways of the basal ganglia are responsible for this effect.

Decision letter after peer review:

Thank you for submitting your article "Inhibition of striatonigral autophagy as a link between cannabinoid intoxication and impairment of motor coordination" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kate Wassum as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Cece Hillard (Reviewer #1); Nephi Stella (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.

Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in eLife, either of which would be linked to the original paper.

Summary:

This study demonstrates the involvement of autophagy in the THC-triggered impairment in motor coordination and that the mechanism occurs specifically in striatal D1 MSNs. The experimental design is thorough and uses validated pharmacological and genetic tools in established rodent model systems. The technical approaches are sound, the manuscript clearly written, and conclusions and interpretations based on convincing results. The study is likely to have an important impact on the field of cannabinoid research and neuroscience in general, providing an important foundation for future studies. The report's main shortcomings are that the data (with one exception) come from a single cannabinoid ligand (given at a single dose and analyzed at a single time point after administration), that only a single (albeit well-established) behavioral measure is examined, and that only male animals were studied. As such the paper requires significant tempering of the conclusions and a thorough acknowledgement of the study's aforementioned shortcomings.

Revisions for this paper:

1) The complete data set needs to be provided. In particular, there are multiple instances of "representative data" being shown. Bar/dot plots of the total data sets should be provided. This includes Figures 3B, 4B, 5B, 5E, 6A and B (immuno data).

2) Figure 1: For the analysis of LC3-II by western blots, in some cases, it looks as though the LC3-I band density is changing with the LC3-II bands. At a minimum, the authors should measure and report the effects of THC on LC3-I density and should consider looking at the ratio of II/I. Also, for the p62 blots, the expression is much higher in the cortex, hippocampus and cerebellum than in the striatum in the vehicle treated samples. This raises the possibility that the lack of THC effect in these tissues is a matter of signal to noise. Please compare blots that had closer to equivalent p62 band densities in the vehicle treated groups in order to conclude whether there is a brain regional effect of THC.

3) Please use a two-way ANOVA for Figure 2 (the comparisons between THC and HU).

4) Materials and methods. How was the IHC data gathered and quantified? Were individuals scoring images or was an unbiased quantification of positive pixels used (e.g. with Image J), or another approach? A detailed description of the counting methodology and parameters is required for this section.

5) Materials and methods. The rotarod results are difficult to interpret because methodological details and data calculation specifics are missing. Considering that the mice were tested for their RotaRod performance 4 h after acute THC treatment, I understand that the 3rd RotaRod trial was measured approximately 5 h 30 min after THC treatment. Why was the first trial excluded? Does one injection of THC not impair RotaRod? Was the THC-triggered impaired in RotaRod performance more pronounced during the 3rd trial compared to the2nd trial? Was the average THC response of the RotaRod trials during first day different than the 2nd and 3rd day? Was more than one injection necessary to get a pronounced THC impaired RotaRod 4-5 h after TTT? Please include day by day data and analysis to determine the precise number of injections (on average) required to trigger the autophagy response.

6) It is striking that an impaired locomotor activity and motor coordination (RotaRod) is still detectable 4-5 h after i.p. injection in light of THC's PK profile. In the classic cannabinoid tetrad test, impaired locomotion is typically measured 30-60 min after THC injection. Please provide a detailed explanation for the prolonged impairment exerted by THC on RotaRod performance observed at 4-5 h after treatment.

7) Figure 3A: RotaRod and following RotaRod histograms: The Y axis legend and units are unclear. Should this be labeled "Motor coordination" or "Latency to fall"? Should units be in seconds or % of vehicle performance? What is basal? Is it vehicle treated? Please label accordingly. Currently, results are expressed as "relative to basal": why is the vehicle group not at 1?

8) The authors need to justify the lack of inclusion of a CB1 receptor selective antagonist or inverse agonist (in addition of their use of site-selective CB1R knock-out mice), as many things can happen in a genetically modified mouse, not all of which we the authors have control upon.

9) The authors need to convincingly discuss the limitations of using a single fairly elevated dose (10 mg/kg), which far exceeds the circulating THC plasma levels observed in cannabis-intoxicated humans.

10) In light of findings that first-pass conversion of THC to THC-OH is several times higher in female than male mice, the authors need to justify the use of male animals only because this polymorphism is likely to underlie differences in the observed effects.

11) Please ensure full reporting of your statistical analyses in your results, including F and t statistics, degrees of freedom, exact p values, etc.

https://doi.org/10.7554/eLife.56811.sa1

Author response

Summary:

This study demonstrates the involvement of autophagy in the THC-triggered impairment in motor coordination and that the mechanism occurs specifically in striatal D1 MSNs. The experimental design is thorough and uses validated pharmacological and genetic tools in established rodent model systems. The technical approaches are sound, the manuscript clearly written, and conclusions and interpretations based on convincing results. The study is likely to have an important impact on the field of cannabinoid research and neuroscience in general, providing an important foundation for future studies. The report's main shortcomings are that the data (with one exception) come from a single cannabinoid ligand (given at a single dose and analyzed at a single time point after administration), that only a single (albeit well-established) behavioral measure is examined, and that only male animals were studied. As such the paper requires significant tempering of the conclusions and a thorough acknowledgement of the study's aforementioned shortcomings.

We would like to thank the reviewers very much indeed for their positive and constructive comments, which we frankly believe have helped to improve the quality of our study. As indicated, we have explicitly acknowledged the aforementioned shortcomings of the study in the manuscript (see Discussion, paragraph one). Nonetheless, we also provide in this point-by-point response some substantiation and improvement to those issues (see below).

Revisions for this paper:

1) The complete data set needs to be provided. In particular, there are multiple instances of "representative data" being shown. Bar/dot plots of the total data sets should be provided. This includes Figures 3B, 4B, 5B, 5E, 6A and B (immuno data).

We are sorry for this fault. As requested, we provide the complete data sets for those Western blot and immunofluorescence experiments, including the corresponding dot plots and statistical analyses (see Figures 3-6, as well as their legends and source data files).

2) Figure 1: For the analysis of LC3-II by western blots, in some cases, it looks as though the LC3-I band density is changing with the LC3-II bands. At a minimum, the authors should measure and report the effects of THC on LC3-I density and should consider looking at the ratio of II/I. Also, for the p62 blots, the expression is much higher in the cortex, hippocampus and cerebellum than in the striatum in the vehicle treated samples. This raises the possibility that the lack of THC effect in these tissues is a matter of signal to noise. Please compare blots that had closer to equivalent p62 band densities in the vehicle treated groups in order to conclude whether there is a brain regional effect of THC.

As requested, we show the data on the effect of THC on LC3-I levels and LC3-II/LC3-I ratios, which further support our previous data on LC3-II/β-actin ratios (Figure 1A). We have also evaluated the basal levels of LC3-I and p62 in the four brain regions under study, and no significant differences were found (Figure 1B). In addition, we provide less exposed blots. All this new information has been included in Figure 1, together with its legend and source data file, as well as in Results (paragraph one).

3) Please use a two-way ANOVA for Figure 2 (the comparisons between THC and HU).

Done (see legend and source data file for Figure 2).

4) Materials and methods. How was the IHC data gathered and quantified? Were individuals scoring images or was an unbiased quantification of positive pixels used (e.g. with Image J), or another approach? A detailed description of the counting methodology and parameters is required for this section.

We have specified that all immunomicroscopy analyses relied on an unbiased quantification of ImageJ-positive pixels, and were conducted in a blinded manner for genotype, pharmacological treatment and viral injections (Materials and methods, subsection “Immunomicroscopy”). We have also included further experimental details of the immunomicroscopy procedures (Materials and methods).

5) Materials and methods. The rotarod results are difficult to interpret because methodological details and data calculation specifics are missing. Considering that the mice were tested for their RotaRod performance 4 h after acute THC treatment, I understand that the 3rd RotaRod trial was measured approximately 5 h 30 min after THC treatment. Why was the first trial excluded? Does one injection of THC not impair RotaRod? Was the THC-triggered impaired in RotaRod performance more pronounced during the 3rd trial compared to the2nd trial? Was the average THC response of the RotaRod trials during first day different than the 2nd and 3rd day? Was more than one injection necessary to get a pronounced THC impaired RotaRod 4-5 h after TTT? Please include day by day data and analysis to determine the precise number of injections (on average) required to trigger the autophagy response.

We are sorry for the confusion that the wording of that section may have caused in the reviewers (see also point 7 below). This misinterpretation comes essentially from what “pre-treatment” and “post-treatment” RotaRod performance means for each animal. We have carefully clarified this issue now in the “Motor behaviour” subsection of the Materials and methods as follows:

“RotaRod performance was evaluated in two phases. […] Hence, for each animal, its “post-treatment” RotaRod performance was compared with its “pre-treatment” RotaRod performance.”

So, regarding the specific questions raised by the reviewers:

– Yes, the 3rd post-treatment trial was measured approximately 5 h 30 min after THC treatment.

– No, the first post-treatment trial was not excluded. As explained above, what we excluded were the trials conducted on the 1st pre-treatment day, as they merely reflect the initial contact of the animal with the RotaRod device.

– Yes, one single THC injection (as conducted throughout this study) indeed impaired (post-treatment) RotaRod performance.

– The THC-triggered impairment of RotaRod performance was similar during the 2nd and the 3rd (post-treatment) trials.

– Those three consecutive days correspond to the pre-treatment RotaRod trials, so prior to THC treatment.

– No, as mentioned above one single THC injection was sufficient to get a pronounced THC-induced (post-treatment) impairment of RotaRod performance.

– The pre-treatment and post-treatment data are detailed for each individual animal in the corresponding source data files.

6) It is striking that an impaired locomotor activity and motor coordination (RotaRod) is still detectable 4-5 h after i.p. injection in light of THC's PK profile. In the classic cannabinoid tetrad test, impaired locomotion is typically measured 30-60 min after THC injection. Please provide a detailed explanation for the prolonged impairment exerted by THC on RotaRod performance observed at 4-5 h after treatment.

We conducted the RotaRod test 4 hours after THC treatment precisely to avoid the strong distortion that acute catalepsy and motor impairment would produce on motor coordination if measured at shorter times. It is true that THC may disappear from the animal’s bloodstream by 1-2 hours after i.p. injection, but it is retained for longer time periods by – and hence it remains bioactive in – fatty tissues such as the brain. We have assessed the “cannabinoid tetrad” for many years in our labs and we consistently find that the remarkable hypolocomotor effect of 10 mg/kg THC, which – as the reviewers well say – peaks shortly after injection, declines progressively but still persists moderately 4 hours after injection (as in this study; see Figure 3—figure supplement 1 and Figure 4—figure supplement 1). Our THC administration protocol of one single i.p. injection of THC at 10 mg/kg is identical to that used by the Ozaita and Maldonado lab in Puighermanal et al., 2013, which reported a persistence of THC-evoked hypolocomotion, anxiety and analgesia 4 hours after acute injection. We have acknowledged the latter study in Results (paragraph one).

7) Figure 3A: RotaRod and following RotaRod histograms: The Y axis legend and units are unclear. Should this be labeled "Motor coordination" or "Latency to fall"? Should units be in seconds or % of vehicle performance? What is basal? Is it vehicle treated? Please label accordingly. Currently, results are expressed as "relative to basal": why is the vehicle group not at 1?

As suggested, we have re-labeled the y-axes of all RotaRod histograms with “Motor coordination”. We agree that this makes data representation clearer. Again, we are sorry for the confusion that our description of the RotaRod experiments may have caused to the reviewers. As mentioned in point 4 above, for each animal its “post-treatment” RotaRod performance was compared with its “pre-treatment” RotaRod performance, as it is widely reported in the field. “Basal” did not stand for “vehicle-treated,” but for “pre-treatment”. We understand that this may have been puzzling, and we apologize for it. So, we have replaced “basal” with “pre-treatment” throughout the text, figures and source data files. Hence, a value of “post-treatment” relative to “pre-treatment” (or “basal” in the former manuscript version) higher than 1 in the vehicle-treated, control mice simply denotes that, as it is well known in the field, the animals tend to improve their performance in the RotaRod test after consecutive trials.

8) The authors need to justify the lack of inclusion of a CB1 receptor selective antagonist or inverse agonist (in addition of their use of site-selective CB1R knock-out mice), as many things can happen in a genetically modified mouse, not all of which we the authors have control upon.

We agree with the reviewers. We have therefore evaluated whether the THC-induced impairment of motor coordination is affected by rimonabant. For this purpose, wild-type mice were injected with rimonabant (3 mg/kg, i.p.) or vehicle, and, 20 min later, with THC (10 mg/kg, i.p.) or vehicle. Four hours later, the RotaRod test was conducted. As shown in new Figure 5—figure supplement 1 (see also Results, subsection “Cannabinoid CB1 receptors located on the direct pathway, but not on cortical projections, are required for the THC-induced impairment of striatal autophagy and motor coordination in vivo”; Materials and methods, subsection “Drug treatments in vivo”; and figure legend), the THC-induced decrease of RotaRod performance was fully abrogated by rimonabant. Hence, this observation provides further support to the use of conditional CB1 receptor knockout animals to dissect the contribution of particular CB1 receptor subpopulations to the observed effects (Figure 5).

9) The authors need to convincingly discuss the limitations of using a single fairly elevated dose (10 mg/kg), which far exceeds the circulating THC plasma levels observed in cannabis-intoxicated humans.

This interesting question comes out very often in translational cannabinoid research. We agree that the dose of 10 mg/kg, as well alleged by the reviewers, is “fairly elevated”. However, we do not consider it a too high dose for a mouse. In fact, this dose is very frequently used to assess acute behavioral effects of THC as the “cannabinoid tetrad” (see, for example, Metna-Laurent et al., 2017). In our hands, a THC dose of 3 mg/kg produces mild effects in the “cannabinoid tetrad”, while a THC dose of 20 mg/kg leads to very strong cataleptic and motor-impairing effects that would preclude any neat evaluation of motor coordination. It should also be born in mind that, when extrapolating an animal dose to the potentially equivalent human dose, pharmacological and toxicological endpoints for systemically-administered drugs are usually assumed to scale much closer between animal species when doses are normalized to body surface area rather than to body weight. Thus, when applying these conversion factors for the definition of human equivalent doses from animal experiments (see, for example, FDA guidelines in https://www.fda.gov/regulatory-information/search-fda-guidance-documents/estimating-maximum-safe-starting-dose-initial-clinical-trials-therapeutics-adult-healthy-volunteers), an experimental dose of 10 mg/kg THC in mice would translate into 0.8 mg/kg THC in humans, which equals a total mass of 56 mg THC for a 70-kg person. This would be in turn equivalent to an estimated 0.5-0.6 g of consumed cannabis product with ~10% THC content, which falls within the range of heavy cannabis use. We frankly believe that these pieces of information support a reasonable choice of dosing for the THC administration experiments included in our study (see Results, paragraph one).

10) In light of findings that first-pass conversion of THC to THC-OH is several times higher in female than male mice, the authors need to justify the use of male animals only because this polymorphism is likely to underlie differences in the observed effects.

We agree with the reviewers. We have therefore evaluated whether the THC-induced impairment of motor coordination found in male mice also occurs in female animals. For this purpose, wild-type adult C57BL/6N female mice were injected with THC (10 mg/kg, i.p.) or vehicle. Four hours later, the RotaRod test was conducted as described in the Materials and methods section. As shown in the accompanying figure, THC decreased RotaRod performance by 40% (n = 5 animals per group; **p = 0.0035 from vehicle-treated group by unpaired Student t-test; t = 4.078; F(4,4) = 2.018; power = 0.155). This effect is well equivalent to that exerted on male mice under identical experimental conditions (see Figures 3 through 6 in the manuscript). Hence, although we cannot rule out that certain differences may occur between male and female mice in other parameters studied, an overt absence of sex dimorphism is evident in the main behavioral trait on which our work relies.

Author response image 1
Author response table 1
Motor coordination (time to fall, s)
Raw DataVehicleTHC
Pre-treatmentPost-treatmentPost-treatment/Pre-treatmentPre-treatmentPost-treatmentPost-treatment/Pre-treatment
931011.08113710.63
911311.431131120.99
791221.541011051.05
721301.8164480.75
1001431.4480801.00
Mean871251.4694830.88
SEM5.056.960.129.6611.620.08
CI72.98106.101.1467.3850.920.66
101.00144.701.78121.00115.501.11

11) Please ensure full reporting of your statistical analyses in your results, including F and t statistics, degrees of freedom, exact p values, etc.

Done. All that information is collected in the source data files.

https://doi.org/10.7554/eLife.56811.sa2

Article and author information

Author details

  1. Cristina Blázquez

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  2. Andrea Ruiz-Calvo

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  3. Raquel Bajo-Grañeras

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  4. Jérôme M Baufreton

    Centre National de la Recherche Scientifique (CNRS) and University of Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2623-6375
  5. Eva Resel

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Data curation, Investigation, Methodology, Project administration
    Competing interests
    No competing interests declared
  6. Marjorie Varilh

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  7. Antonio C Pagano Zottola

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  8. Yamuna Mariani

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  9. Astrid Cannich

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  10. José A Rodríguez-Navarro

    Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  11. Giovanni Marsicano

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  12. Ismael Galve-Roperh

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3501-2434
  13. Luigi Bellocchio

    Institut National de la Santé et de la Recherche Médicale (INSERM) and University of Bordeaux, NeuroCentre Magendie, Physiopathologie de la Plasticité Neuronale, Bordeaux, France
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration, Writing - review and editing
    For correspondence
    luigi.bellocchio@inserm.fr
    Competing interests
    No competing interests declared
  14. Manuel Guzmán

    1. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto Universitario de Investigación Neuroquímica (IUIN) and Department of Biochemistry and Molecular Biology, Complutense University, Madrid, Spain
    2. Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    mguzman@quim.ucm.es
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7475-118X

Funding

Spanish Ministerio de Ciencia, Innovación y Universidades (SAF2015-64945-R)

  • Manuel Guzmán

Spanish Ministerio de Ciencia, Innovación y Universidades (RTI2018-095311-B-I00)

  • Manuel Guzmán

Spanish Ministerio de Ciencia, Innovación y Universidades (SAF2016-78666-R)

  • José A Rodríguez-Navarro

Fondation pour la Recherche Médicale (DRM20101220445)

  • Giovanni Marsicano

Fondation pour la Recherche Medicale (DPP20151033974)

  • Giovanni Marsicano

Human Frontier Science Program (RGP0036/2014)

  • Giovanni Marsicano

H2020 European Research Council (ERC-2010-StG-260515)

  • Giovanni Marsicano

H2020 European Research Council (ERC-2014-PoC-640923)

  • Giovanni Marsicano

H2020 European Research Council (ERC-2018-AdG-786467)

  • Giovanni Marsicano

Region Nouvelle Aquitaine

  • Giovanni Marsicano

Agence Nationale de la Recherche (ANR-16-CE37-0010-01)

  • Giovanni Marsicano

Agence Nationale de la Recherche (ANR 18-CE16-0001-02)

  • Giovanni Marsicano

Fondation pour la Recherche Médicale (ARF20140129235)

  • Luigi Bellocchio

Agence Nationale de la Recherche (ANR-10-LABX-0043)

  • Giovanni Marsicano

Agence Nationale de la Recherche (ANR-18-CE14-0029-01)

  • Giovanni Marsicano

Agence Nationale de la Recherche (ANR-19-CE14)

  • Luigi Bellocchio

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

Acknowledgements

This work was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU/FEDER; grants SAF2015-64945-R and RTI2018-095311-B-I00 to MG, and SAF2016-78666-R to JAR-N). AR-C was supported by a contract from the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU/FEDER; Formación de Personal Investigador Program). RB-G was supported by a contract from the Spanish Ministerio de Ciencia, Innovación y Universidades (MCIU/FEDER; Juan de la Cierva Program). GM and LB were supported by INSERM. GM was also supported by Fondation pour la Recherche Medicale (grants DRM20101220445 and DPP20151033974), Human Frontiers Science Program (grant RGP0036/2014), European Research Council (Endofood grant ERC-2010-StG-260515, CannaPreg grant ERC-2014-PoC-640923, and MiCaBra grant ERC-2018-AdG-786467), Region Nouvelle Aquitaine, and Agence Nationale de la Recherche (ANR Blanc MitObesity grant ANR-18-CE14-0029-01, ANR LabEx BRAIN grant ANR-10-LABX-0043, ANR Blanc ORUPS grant ANR-16-CE37-0010-01, and ANR Blanc CaCoVi grant ANR 18-CE16-0001-02). LB was also supported by Fondation pour la Recherche Medicale (grant ARF20140129235) and Agence Nationale de la Recherche (ANR Blanc mitoCB1-fat grant ANR-19-CE14). We are indebted to E García-Taboada, L Rivera, A Gaudioso, P García-Rozas, and MJ Asensio for expert laboratory assistance; D Gonzales, N Aubailly, and all the personnel from the animal facilities of the NeuroCentre Magendie; M Biguerie from the technical service of the NeuroCentre Magendie; all the personnel from the Bordeaux Imaging Center; and V Morales for continuous help.

Ethics

Animal experimentation: All the experimental procedures were performed in accordance with the guidelines and with the approval of the Animal Welfare Committee of Universidad Complutense de Madrid and Comunidad de Madrid (PROEX 209/18), and in accordance with the directives of the European Commission (2010/63/EU). Adequate measures were taken to minimize pain and discomfort of the animals, as well as the number of animals used in the experiments, on the basis of the 3Rs (replacement, reduction and refinement) principle.

Senior Editor

  1. Kate M Wassum, University of California, Los Angeles, United States

Reviewing Editor

  1. Joseph F Cheer, University of Maryland School of Medicine, United States

Reviewers

  1. Cece Hillard
  2. Nephi Stella, Univ. Washington, United States

Publication history

  1. Received: March 10, 2020
  2. Accepted: July 14, 2020
  3. Version of Record published: August 10, 2020 (version 1)

Copyright

© 2020, Blázquez et al.

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

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